This publication was produced at the request of the United States Department of Agriculture. It was 
prepared independently by Asian Social Project Services Inc.
Foreign Agricultural 
Service, United States 
Department of Agriculture
PHILIPPINES Food for Progress
Building Safe Agricultural Food Enterprises
Baseline Evaluation
4/9/2021
DISCLAIMER: This publication was produced at the request of the United States Department of 
Agriculture. It was prepared by an independent third-party evaluation firm. The author’s views 
expressed in this publication do not necessarily reflect the views of the United States Department of 
Agriculture or the United States Government.
Baseline Study for the Building Safe Agricultural Food 
Enterprises (B-SAFE) Project in the Philippines
Program: Food for Progress
Agreement Number: FCC-492-2019/015-00-A
Funding Year: Fiscal Year 2019
Project Duration: October 1, 2019 – September 30, 2023
Implemented by: Winrock International
Evaluation Authored by: ASIAN SOCIAL PROJECT SERVICES INC.
[Dr. Ernesto O. Brown, Team Leader]
iii
Table of Contents 
List of Acronyms ......................................................................................................................... vi
Executive Summary...................................................................................................................... 1
Project Background and Purpose............................................................................................................ 1
Evaluation Questions.............................................................................................................................. 2
Methodology and Limitations................................................................................................................. 2
Findings, Conclusions, and Recommendations....................................................................................... 3
1. Introduction and Purpose......................................................................................................... 8
1.1. Project Context................................................................................................................................ 8
1.2. Project Description.......................................................................................................................... 8
1.3. Purpose of the Evaluation............................................................................................................... 9
2. Evaluation Design and Methodology ................................................................................... 11
2.1. Evaluation Questions .................................................................................................................... 11
2.2. Situational Analysis Framework.................................................................................................... 12
2.3. Sampling and Data Collection Methods........................................................................................ 13
2.4. Data Processing and Analysis Methods......................................................................................... 14
2.5. Limitations of the Study ................................................................................................................ 15
3. Findings.............................................................................................................................. 15
3.1. Indicators....................................................................................................................................... 15
3.2. Findings on Value Chain Assessment (Situational Analysis) ......................................................... 22
4. Conclusions ........................................................................................................................ 47
5. Recommendations.............................................................................................................. 48
Annexes..................................................................................................................................... 51
Annex 1. Bibliography ........................................................................................................................... 51
Annex 2. B-SAFE Baseline Indicator Table: Proportions and Means..................................................... 53
Annex 3. Selection of Sample Clusters Using Systematic Sampling...................................................... 58
Annex 4. List of Organizations for Key Informant Interviews............................................................... 62
Annex 5. Survey Questionnaires........................................................................................................... 63
Annex 6. Guide questions for key informant interviews.................................................................... 158
Annex 7. Terms of Reference for Baseline Study................................................................................ 158
Annex 8. Conflict of Interest Statement ............................................................................................. 183
List of Appendices.................................................................................................................... 184
Rice Appendices.................................................................................................................................. 184
Corn Appendices................................................................................................................................. 188
Hogs Appendices................................................................................................................................. 191
iv
Chicken Appendices............................................................................................................................ 201
Milkfish Appendices............................................................................................................................ 212
Coco Sugar Appendices....................................................................................................................... 225
 
v
List of Figures 
Figure 1. B-SAFE Results Framework ...................................................................................................... 9
Figure 2. Framework of the baseline study .......................................................................................... 13
Figure 3. Rice value chain, Bukidnon, 2021 .......................................................................................... 23
Figure 4. Value chain of corn, Bukidnon, 2021 ..................................................................................... 27
Figure 5. The supply chain of hogs and the three identified value-chain maps................................... 30
Figure 6. Broiler value chain in Batangas.............................................................................................. 34
Figure 7. Supply chain of milkfish in Luzon........................................................................................... 38
Figure 8. Value chain map of coco sugar .............................................................................................. 42
List of Tables 
Table 1. B-SAFE indicators with estimated baseline values.................................................................... 3
Table 2. B-SAFE indicators with baseline values set at zero. .................................................................. 4
Table 3. Indicator description, measurement and disaggregates ........................................................ 10
Table 4. Sample sizes by commodity and province .............................................................................. 14
Table 5. Estimated number of individuals in the agriculture system who have applied improved 
management practices or technologies ............................................................................................... 17
Table 6. Number of individuals using improved packaging, equipment, transportation, or cold 
storage .................................................................................................................................................. 19
Table 7. Number of farms/firms/laboratories with GAP, GMP, HACCP, or ISO certification ............... 20
Table 8. Value of annual sales of farms and firms................................................................................ 21
Table 9. Volume of commodities sold by farms and firms ................................................................... 21
Table 10. Number of host agencies with risk management plan ......................................................... 22
Table 11. Percentage of postharvest losses, rice, Bukidnon ................................................................ 24
Table 12. Awareness, practice, certification and willingness to adopt GAP, rice farmers, Bukidnon.. 24
Table 13. Percentage of postharvest losses, corn, Bukidnon ............................................................... 28
Table 14. Food safety and productivity related trainings attended by corn farmers and traders, 
Bukidnon............................................................................................................................................... 29
Table 15. Assistance needed by corn farmers, Bukidnon..................................................................... 29
vi
List of Acronyms
ACRONYM FULL TERM
AMR Antimicrobial resistance
ASEAN Association of Southeast Asian Nations
ASF African Swine Fever
ATI Agricultural Training Institute
BAFS Bureau of Agriculture and Fisheries Standards
BAI Bureau of Animal Industry
BPI Bureau of Plant Industry
BFAR Bureau of Fisheries and Aquatic Resources
B-SAFE Building Safe Agricultural Food Enterprises
CAO City Agricultural Office
CSO Civil Society Organization
DA Department of Agriculture
DENR Department of Environment and Natural Resources
DOCS Day-old Chicks
DOH Department of Health
DOST Department of Science and Technology
FAW Fall Armyworm
FDA Food and Drug Administration
FFPR Food for Progress
FNRI Food and Nutrition Research Institute
FPA Fertilizer and Pesticide Authority
FPSQ Farm Production Survey Questionnaires
GAP Good Agricultural Practice
GAHP Good Animal Husbandry Practices
GAQP Good Aquaculture Practices
GHP Good Hygienic Practice
GMP Good Manufacturing Practice
GOP Government of the Philippines
GSP Good Storage Practice
HACCP Hazard Analysis and Critical Control Points
IPM Integrated Pest Management
IPPC International Plant Protection Convention
ISN Impasugong Samahang Nayon
ISO International Organization for Standardization
ITCPH International Training Center on Pig Husbandry
KIGQ Key Informant Guide Questions
KII Key Informant interview
LAMPCO Linabu Agrarian Multi-Purpose Cooperative
LGU Local Government Unit
LRME Locally Registered Meat Establishments
NCBP National Committee on Biotechnology of the Philippines
NMIS National Meat Inspection Service
NSIC National Seed Industry Council
OIE World Organization for Animal Health
OPAG Office of Provincial Agriculturist
PAO Provincial Agricultural Office
PNS Philippine National Standard
PVO Provincial Veterinary Office
vii
RBB Rice Black Bug
RFP Request for Proposal
RFO Regional Field Office
SME Small and Medium Enterprises
SPS Sanitary and Phytosanitary 
TA Technical Assistance
TPSQ Trader/Processors Survey Questionnaires
UBRA United Broiler Raisers Association
UNIBAT United Batangas Hog Raisers Association
US United States
USDA United States Department of Agriculture
1
Executive Summary 
Project Background and Purpose 
The Building Safe Agricultural Food Enterprises (B-SAFE) is a four-year project implemented by Winrock 
International and funded by the Food for Progress (FFPr) program of the United States Department of 
Agriculture (USDA). B-SAFE has two strategic objectives that are aligned with USDA’s FFPr Strategic 
Objectives:
• Increase agricultural productivity by improving the Sanitary and Phytosanitary (SPS) Standards in 
production and management of supply chains; and
• Expand trade of agricultural products by improving the Government of Philippines (GOP) regulatory 
agencies’ capacity to manage risk-based systems, promote awareness of biotechnology, enhance 
regulatory standards and processes, enhance domestic and export market linkages, and build the 
capacity of the private sector to leverage investment.
The focus of B-SAFE is on six commodities in selected provinces in the Philippines: rice and corn in 
Bukidnon, hogs and broiler chicken in Batangas, milkfish in Pangasinan, and coco sugar in Davao del Sur 
and Misamis Oriental. The baseline study, therefore, establishes the baseline situation for these 
commodities in the selected provinces. The specific objectives of the study were as follows:
• Establish a baseline as points of comparison to support measurement of program impacts as part of 
future project evaluation activities;
• Validate targets for performance indicators to ensure realistic target setting;
• Conduct a situational analysis as basis for assessing program design; and
• Identify and recommend responses to risks and constraints that may pose challenges to planned 
project implementation.
The baseline study focused on twelve FFPr standard indicators (SI) and two custom indicators (CI) listed 
in Annex 1. The study estimated the baseline for the following four (4) standard indicators and two (2) 
custom indicators. The baseline values of the disaggregates of these indicators were also calculated. 
• SI-4: Number of individuals in the agriculture system who have applied improved management 
practices or technologies with USDA assistance
• SI-11: Number of host government or community-derived risk management plans formally 
proposed, adopted, implemented, or institutionalized with USDA assistance
• SI-18: Value of annual sales of farms and firms receiving USDA assistance
• SI-19: Volume of commodities sold by farms and firms receiving USDA assistance
• CI-1: Number of individuals using improved packaging, equipment, transportation, or cold 
storage as a result of B-SAFE investment
• CI-2: Number of farms/firms/ laboratories with GAP, GMP, HACCP, or ISO certification as a result 
of USDA assistance
In addition to establishing the baseline values of the indicators, the study carried out a situational analysis 
designed to: (1) map value chains and establish SPS conditions, postharvest losses, and risks; (2) assess 
2
the organizational performance and risk management capacity of host government agency partners and 
communities related to food safety; (3) describe the existing conditions at baseline; and (4) identify areas 
for collaboration among value chain actors. Using probit model analysis, the study explored the factors 
that would likely explain the adoption of improved technologies and practices by producers.
Evaluation Questions 
The evaluation questions addressed to potential B-SAFE beneficiaries and stakeholders were intended to 
generate the baseline estimates for the B-SAFE indicators and inform the baseline situation related to: (1) 
level of postharvest losses, SPS conditions and risks; (2) organizational performance and risk management 
capacity of host government agency partners and communities; and (3) potential collaboration among 
value chain actors.
The questions addressed to the farm household baseline survey were on size of operation (e.g. area 
planted, number of animals raised, size of fish cages, number of production cycles, etc.); sources of inputs; 
farm practices and technologies, especially in relation to food safety (e.g. GAP, HACCP, GAHP, etc.); farm 
performance (e.g. yield, volume and value of production, etc.); postharvest and marketing practices; 
access to support services such as extension, credit, etc., socio-economic and demographic characteristics 
of the farmers and problems encountered especially related to food safety, among others. 
The questions addressed to the traders and processors were on size of operation (volume and value of 
procurement); handling practices/technologies and standards used especially in relation to food safety; 
major markets of the products; etc. The questions addressed to value chain enablers (e.g. provincial and 
municipal local governments, trade associations, business service providers), which were asked through 
key informant interviews (KIIs), were on understanding of food safety, regulatory policies and framework, 
level of implementation and monitoring of food safety standards, facilities available, programs 
implemented, risk management plans, trainings attended on food safety and recommendations for 
improvement related to food safety, etc. 
Methodology and Limitations 
The study used a mixed methods design which combined both quantitative and qualitative tools. For the
quantitative approach, the study surveyed the potential stakeholders and beneficiaries of the six 
commodity value chains, namely the producers and traders/processors. The sample size was established 
using the Cochran formula with 95% confidence level and 7.5% margin of error. Total sample size for the 
survey covering the six commodities was 2,008. To determine the respondents in the study, a two-stage 
cluster design (barangays as clusters) with listing operation using fractional interval systematic sampling 
was employed. In addition to the survey and as part of value chain mapping, the study also gathered 
primary data through 29 KIIs of key value chain players covering production, trading/processing as well as 
value chain enablers such as trade associations, local government units (LGUs) and NGAs, among others.
Three sets of research instruments were used in the study. These include i) Farm Production Survey 
Questionnaires (FPSQ); ii) Trader/Processors Survey Questionnaires (TPSQ); and iii) Key Informant Guide 
Questions (KIGQ). The FPSQs and TPSQs were tailored to the commodity under consideration while the 
KIGQs were tailored to the type of key informants (i.e., LGUs, trade associations, business service 
providers). Research instruments are provided in Annex 4 and 5.
As a major limitation, the study was done at the height of the pandemic which limited the mobility of the 
study team. Nevertheless, the survey was still conducted face-to-face, although the KIIs were done mostly 
through virtual means.
3
Findings, Conclusions, and Recommendations 
It was established from the data gathered that for the six commodities covered, 99.51% of potential B￾SAFE beneficiaries have applied at least one improved management practice or technology, 16.46% have 
used improved packaging, 36.94% have used improved equipment, 21.25% have used improved 
transportation, and 1.43% have used improved cold storage. The value of annual sales of farms and firms 
amounted to USD 3,477,421,750, which was generated from the sales of 1,429,181 MT of products. It was 
also found that there are 3,463 farms/firms/laboratories with GAP, GMP, HACCP, or ISO certification and 
16 host government or community-derived risk management plans either formally proposed, adopted, 
implemented or institutionalized (Table 1). The indicators for which baseline values were set at zero are 
given in Table 2.
Table 1. B-SAFE indicators with estimated baseline values
Indicator Title Baseline Value
SI-4: Number of individuals in the agriculture system who 
have applied improved management practices or 
technologies with USDA assistance
Total estimate: 88,050
Percent of total population: 99.51%
CI-1: Number of individuals using improved packaging, 
equipment, transportation, or cold storage as a result of 
B-SAFE investment
Disaggregation by technology type (Multiple Response)
• Packaging Packaging Total estimate: 14,561
Packaging Percent of total 
population: 16.46%
• Equipment Equipment Total estimate: 32,682
Equipment Percent of total 
population:
36.94%
• Transportation Transportation Total estimate: 18,800
Transportation Percent of 
total population: 21.25%
• Cold storage Cold Storage Total estimate: 1,265
Cold Storage Percent of total 
population:
1.43%
SI-18: Value of annual sales of farms and firms receiving 
USDA assistance
Total estimate, in USD: 3,477,421,750
Average Sales per Individual, 
in USD: 39,494
SI-19: Volume of commodities sold by farms and firms 
receiving USDA assistance
Total estimate, in MT: 1,429,181
Average Volume per 
Individual, in MT: 16.23
CI-2: Number of farms/firms/ laboratories with GAP, GMP, 
HACCP, or ISO certification as a result of USDA 
assistance Number: 3,463
SI-11: Number of host government or community-derived 
risk management plans formally proposed, adopted, 
implemented or institutionalized with USDA assistance Number: 16
4
Table 2. B-SAFE indicators with baseline values set at zero.
Indicator Title Baseline Value
SI-9: Number of technologies, practices, and approaches under various phases of 
research, development, and uptake as a result of USDA assistance Baseline is zero.
SI-12: Percent of USDA-assisted organizations with improved performance Baseline is zero.
SI-13: Number of public-private partnerships formed as a result of USDA assistance Baseline is zero.
SI-14: Value of new USG commitments and new public and private sector 
investment leveraged by USDA to support food security and nutrition Baseline is zero.
SI-17: Number of policies, regulations and/or administrative procedures in each of 
the following stages of development as a result of USDA assistance Baseline is zero.
SI-21: Number of individuals who have received short-term agricultural sector 
productivity or food security training as a result of USDA assistance Baseline is zero.
SI-22: Number of individuals participating in USDA food security programs Baseline is zero.
SI-23: Number of individuals benefiting indirectly as a result of USDA assistance Baseline is zero.
Disaggregating the results by improved management practices and technologies, the study found that 
there are important practices and technologies which are not being applied by a significant proportion of 
potential beneficiaries, hence could be good entry points for B-SAFE:
• Among rice and corn farmers in Bukidnon, only 45% and 38% respectively, are using sustainable 
practices and technologies. There are no rice or corn farmers who have engaged in consolidated 
farming;
• Among hog raisers in Batangas, there is low application (only 3%) of improved practices on 
postharvest handling and storage, especially those with privately owned and operated 
slaughterhouses (low application of sanitation, use of UV lamps for flies, storage freezers, etc.). 
Carcass chillers and blast freezers are not being used. In addition, only 14% are involved in value added 
processing;
• Among broiler growers in Batangas, there is low application (only 46%) of climate adaptation practices 
such as natural ventilation, blower and cooling pads. Only 12% of producers are applying good 
postharvest handling and storage such as sanitation of crates and animal handling facilities and only 
23% are into value-added processing;
• Among milkfish growers in Pangasinan, the study found that while 64% of grow out operators are 
adopting the recommended stocking densities, the accompanying necessary method of feeding is not 
being applied. Moreover, while 77% of milkfish growers are aware of the need to acclimatize the 
fry/fingerling stock, only half of them is practicing it; and
• Among coco sugar producers in Davao and Misamis Oriental, only 3% are practicing improved 
marketing and distribution. This includes better product packaging, labeling and promotion.
On the application of improved packaging, equipment and transportation, the study highlights the 
following:
• Application of improved packaging is very low among producers of rice in Bukidnon (13%), corn in 
Bukidnon (24%), broiler chicken in Batangas (2%), and coco sugar in Davao and Misamis Oriental 40%
5
• Only 3% of broiler chicken growers and 0.27% of hog raisers in Batangas use improved equipment; 
and
• Only 8% of traders use dressing machines for broiler chicken in Batangas.
The study found very limited number of farms and firms with Good Agriculture Practices (GAP), Good 
Manufacturing Practice (GMP), Hazard Analysis and Critical Control Points (HACCP) or International 
Organization for Standardization (ISO certification), regardless of commodities. This is not surprising,
especially for products sold in their raw or unprocessed forms, as the market has not yet significantly 
incentivized compliance to these standards. Compliance to standards is higher among processors as 
products become more differentiated (such as in the case of coco sugar) and for large commercial farms 
such as in the case of most hogs, broiler chicken and milkfish growers. The study highlights the following:
• There is only 1 rice farm in Bukidnon with GAP certification. In addition, there are no corn farms in 
Bukidnon that are GAP certified;
• The survey found that most rice and corn farmers apply only certain components of GAP and there is 
no conscious effort to comply with all the requirements. In most cases, the GAP compliant practices 
being applied by farmers were actually part of their traditional practices, which coincidentally happen 
to be the same practices prescribed under GAP; 
• With hogs in Batangas, the estimated baseline number of farms/firms/laboratories with GAP, GAHP,
GMP, HACCP, or ISO certification was 26;
• For broiler chickens in Batangas, 9.21% of respondents claimed to be Good Animal Husbandry 
Practices (GAHP)-certified. The proportion of producers who are aware of GAHP is 32%, and those 
practicing GAHP but not all its components is 30%;
• In milkfish, there were 6 producers with certification for Good Aquaculture Practices (GAqP) and three 
processors with HACCP certification; and 
• There are 62 producers and 31 traders of coco sugar that have standard certifications. 
The baseline situation analysis of the six value chains highlights the following:
• Postharvest losses are high: 7.2% per year for rice from harvest to final sale; 8% per year for corn from 
harvest, shelling, drying and storage and another 2% during milling, storage to final sale; production 
and postproduction losses in hogs are due mainly to African Swine Fever (ASF) and can reach as high 
as 70%; production and postproduction losses in broiler chicken are due mainly to avian diseases such 
as cough/cold and threat of avian flu; and 8.7% in coco sugar particularly due to rejected sap resulting 
from delayed delivery;
• The technical capacity of potential B-SAFE host government partners in addressing the various food 
safety, quality and productivity risks is generally adequate, but support may be needed to augment 
financial capacity, especially in providing trainings, facilities and equipment support to potential 
beneficiaries;
• The important areas for collaboration are on promoting and capacitating potential beneficiaries to 
comply to the relevant SPS standards, reducing production and postproduction losses and ensuring 
the application of more sustainable practices.
6
The study provides the following specific recommendations, which B-SAFE may act given project 
parameters.
Rice and Corn in Bukidnon
1. Facilitate trainings for farmers on GAP and assist them in complying with and certifying to the 
standards. This may also necessitate provision of assistance in the conduct of farm area assessment, 
building farm storage facilities for fertilizer and chemical inputs and improved farm equipment for 
threshing and drying (to avoid pavement drying), among others, to reduce contamination and 
postharvest losses.
2. Establish models of consolidated farming to facilitate compliance to standards, greater effectiveness 
in combatting risks of pest infestation (e.g., black bug in rice and fall armyworm (FAW) in corn), 
adoption of more sustainable practices and realize the benefits of economies of scale. As exploratory 
steps, B-SAFE may examine the potential of building on existing collaborations and models such as the 
Lead Firm Model of collaboration being practiced by the Acosta Rice Mill in Maramag, Bukidnon for 
rice and the Farm Clustering Model being pursued by the Impasugong Samahang Nayon for corn in 
Bukidnon.
3. Support the effort of local government agencies and LGUs in pest monitoring and surveillance against 
black bug in rice and FAW in corn. While there is local technical capacity on this, financial as well as 
facilities and equipment support are needed.
Hogs and Broiler Chicken in Batangas
1. In hogs, work with the LGUs and the Department of Agriculture (DA) in the repopulation program to 
rebuild the industry devastated by ASF. Collaboration may be in the following: a) work with the 
International Training Center on Pig Husbandry (ITCPH) in providing genetic materials for artificial 
insemination (AI) and semen through its program on AI Sa Barangay where AI training and equipment 
are provided; b) link with LGUs and DA, such as the Tanauan City LGUs in requiring beneficiaries of the 
repopulation program to apply for GAHP certification, or if not possible, to ensure food safety 
practices in their farms. 
2. In hogs, promote a model of Locally Registered Meat Establishments (LRMEs) with the private sector 
to showcase good practices. LRMEs play an important role in ensuring food safety of meat and meat 
products, and their number is greater than the National Meat Inspection Service (NMIS) accredited 
facilities. 
3. In hogs, facilitate access to cold storage and transport facilities for cooperatives such as Soro-soro 
Ibabao Development Cooperative (SIDC), organizations such as United Batangas Hog Raisers 
Association (UNIBAT), and farmers and traders/retailers. This may be in the form of cold storage 
rooms, large freezers, and refrigerated vans and similar facilities that will allow for the transport of 
pork to Metro Manila and other areas. This is also in preparation for the plan of the DA to move 
slaughterhouses out of the national capital to minimize transport of live animals. 
4. In broiler chicken, facilitate access to appropriate facilities and equipment for primary processing of 
chicken for smallholder and independent growers. This could include provision of poultry dressing 
machines and related equipment; vacuum drying equipment; cold storage facilities such as blast
freezers, chillers, and freezers; refrigerated vehicles; and others. 
5. In broiler chicken, promote model LRMEs with the private sector to cater to producers and traders 
who have limited access to NMIS accredited poultry dressing plants. 
7
Milkfish in Pangasinan
1. Partner with the Bureau of Fisheries and Aquatic Resources (BFAR) Region 1 and the LGUs to increase 
access to extension services and training on food safety among the traders/processors. Similarly, 
training programs on productivity improvement for producers may be packaged and implemented 
with particular attention to water management, effluent discharge, and other food safety concerns. 
2. Provision of assistance to traders and processors in getting BFAR, Hazard Analysis and Critical Control 
Points (HACCP) and Good Manufacturing Practice (GMP) certification as all these entail time, effort 
and resources. Likewise, technical assistance in packaging and labeling of manufactured products 
should be provided particularly to small processors in coordination with the Department of Trade 
and Industry.
3. Encourage the provision of public and private investment for local hatchery establishment to ensure 
a fry supply free of contaminants. 
5. Support organizing community level milkfish processing projects focusing on deboning and 
marinating, packaging, and labeling of the products, and link the projects to major market centers. 
6. Lobby for the expansion of community fish landing terminal in Bani to service fishpond and cage 
culture operator. 
7. Coordinate with the Cold Chain Association of the Philippines (CCAP) for the establishment of blast 
freezing facilities in the province.
Coco Sugar in Davao and Misamis Oriental
1. Help in the development of a grading system to encourage farmers to achieve better quality products 
and conduct of capacity building to achieve product quality development and pursue the concept that 
“Food Safety and Quality is the Product Standard”.
2. Spearhead the formulation of an International Product Standard and Trading System for coco sugar in 
agreement with other member countries of the International Coconut Community (ICC) to protect the 
product position in the global market. 
3. For coco sap tappers, facilitate access to equipment such as pH meters and facilities such as common 
service facility for the boiling of coco sap.
Cross-Cutting Recommendations
1. Initiate and support the development of market models that will incentivize farmer’s compliance to 
food safety and quality standards. Especially for products sold in primary form, there is still generally 
no premium price for products produced following existing product standards. 
2. Support consumer and producer awareness campaigns of government entities such as the Food and 
Nutrition Research Institute (FNRI), Department of Agriculture (DA), and Food and Drug 
Administration (FDA) and civil society organizations (CSOs) on the importance of food safety, quality 
and reduced postharvest losses and wastage in the food system.
8
1. Introduction and Purpose 
1.1. Project Context 
This study aimed to establish the baseline for the B-SAFE Project, a four-year program implemented by 
Winrock International and funded by USDA. 
The establishment of a baseline is necessary in any development project. It serves as a crucial reference 
to the context prior to project interventions, provides data that assists with realistic target setting and 
validation, identifies risks and constraints, and may help assess the appropriateness of project design and 
provide data against which to evaluate program accomplishments. An accurate baseline necessitates 
thorough understanding of the project’s goals and objectives, theory of change, scope of its activities, 
strategic interventions, and its direct and indirect beneficiaries. 
The baseline study depicts the situation before the project, from which the progress of the B-SAFE project 
may be tracked. The ex-ante situation should be with reference to the project’s performance indicators 
both in terms of outputs and outcomes.
1.2. Project Description 
The B-SAFE project is focused on contributing to the following FFPr Strategic Objectives:
• Increase agricultural productivity by improving the SPS standards in production and management of 
supply chains; and
• Expand trade of agricultural products by improving the GOP’s regulatory agencies to manage risk-based 
systems, promote awareness of biotechnology, enhance regulatory standards and processes, enhance 
domestic and export market linkages, and build the capacity of the private sector to leverage 
investment.
The B-SAFE theory of change is that if the GOP and the private sector use risk-based management 
approaches to guide their use of relevant SPS-related technical assistance that build capacity; and if the 
GOP and private sector become stronger at capturing information and decision making to meet SPS and 
regulatory requirements for export and import markets, in market situations that change quickly; and if 
the GOP and private sector adopt and invest in SPS systems and have adequate facilities and equipment 
to use; then agricultural products will have increased trade that meet SPS standards for the US, ASEAN, 
international, and domestic markets.
B-SAFE’s goal is to develop and adopt evidence-based international standards to improve the trade of 
safe, wholesome food and agricultural products. This is anchored on USDA’s FFPr Strategic Objectives SO1
Increased Agricultural Productivity and SO2 Expanded Trade of Agricultural Products and their respective 
intermediate and foundational results (see Figure 1. B-SAFE Results Framework).
B-SAFE will implement five key project activities, three of which are to be implemented with public sector 
SPS regulatory agencies (Activities 1 and 2) and biotechnology regulatory agencies (Activity 3) of the DA 
and FDA at the national government level and appropriate LGUs. The approximate number of direct 
beneficiaries from the public sector is 11,500 persons. Activities 4 and 5 are implemented with private 
sector supply chain stakeholders including private sector trade associations and agribusinesses with the 
incentives and resources to invest in SPS compliant supply chains, training service providers, and business 
service providers. The approximate number of direct beneficiaries from the public sector is 26,000 
9
persons. Assistance for supply chains will addressing commodity-specific issues involving six baseline 
commodities in four selected provinces, namely in Batangas (hogs and broilers), Davao del Sur and 
Misamis Oriental (coconut sap sugar), Bukidnon (rice and corn), and Pangasinan (milkfish). Activity 5 on 
cold chain facilities improvement complements the supply chain work for perishable products namely 
meat products, milkfish, and coco sugar. B-SAFE expects to impact approximately 45,688 indirect 
beneficiaries. 
Figure 1. B-SAFE Results Framework
1.3. Purpose of the Evaluation 
Principal Functions of the Evaluation
The study aimed to establish the baseline situation for the B-SAFE project. The four principal functions 
of the evaluation were as follows:
• Establish a baseline as points of comparison to support measurement of program impacts as part of 
future project evaluation activities;
10
• Validate targets for performance indicators to ensure realistic target setting;
• Conduct situational analysis as basis for assessing program design. Such analyses are those relevant 
to target beneficiaries’ knowledge and capacities; access to quality and utilization of inputs and 
infrastructure; value chain diagrams; and, organizational capacity; and
• Identify and recommend responses to risks and constraints that may pose challenges to planned 
project implementation.
Indicator Measurement
A major focus of the analysis of the study are the following 12 FFPr standard indicators and two custom 
indicators (see Table 3). Of the fourteen outlined indicators, the study aimed to measure the quantitative 
baseline values of four standard indicators and the two custom indicators, with their respective 
disaggregates. Especially for SI-4 and CI-1, an individual is considered an adopter if he adopted at least 1 
of the improved technology/practices (in the case of SI-4) or improved packaging, equipment,
transportation or cold storage (in the case of CI-1).
Table 3. Indicator description, measurement and disaggregates
No. Indicator Title Measurement Disaggregates
SI-4 Number of individuals in the agriculture 
system who have applied improved 
management practices or technologies with 
USDA assistance 
Baseline values of 
indicator and 
disaggregates were 
calculated
Commodity; value chain 
actor; age; management 
or technology 
type/practices
SI-9 Number of technologies, practices, and 
approaches under various phases of 
research, development, and uptake as a 
result of USDA assistance
Baseline is zero. Category of research;
phase of development
SI-11 Number of host government or community￾derived risk management plans formally 
proposed, adopted, implemented or 
institutionalized with USDA assistance
Baseline values of 
indicator and 
disaggregates were 
calculated
Type; phase of 
development
SI-12 Percent of USDA-assisted organizations with 
improved performance
Baseline is zero. Numerator; denominator;
Type of organization
SI-13 Number of public-private partnerships 
formed as a result of USDA assistance
Baseline is zero. Type of partnership
SI-14 Value of new USG commitments and new 
public and private sector investment 
leveraged by USDA to support food security 
and nutrition
Baseline is zero. Type of investment
SI-17 Number of policies, regulations and/or 
administrative procedures in each of the 
following stages of development as a result 
of USDA assistance
Baseline is zero. Stage
SI-18 Value of annual sales of farms and firms 
receiving USDA assistance
Baseline values of 
indicator and 
disaggregates were 
calculated
Commodity; type of 
producer/firm; sex; age
SI-19 Volume of commodities sold by farms and Baseline values of Commodity by type of 
11
No. Indicator Title Measurement Disaggregates
firms receiving USDA assistance indicator and 
disaggregates were 
calculated
producer/ firm; sex; age
SI-21 Number of individuals who have received 
short-term agricultural sector productivity 
or food security training as a result of USDA 
assistance
Baseline is zero. Sex; duration; type of 
Individual; type of training
SI-22 Number of individuals participating in USDA 
food security programs
Baseline is zero. Sex; age; type of 
individual; size
SI-23 Number of individuals benefiting indirectly 
as a result of USDA assistance
Baseline is zero. None
CI-1 Number of individuals using improved 
packaging, equipment, transportation, or 
cold storage as a result of B-SAFE 
investment
Baseline values of 
indicator and 
disaggregates were 
calculated
Technology type; sex
CI-2 Number of farms/firms/ laboratories with 
GAP, GMP, HACCP, or ISO certification as a 
result of USDA assistance
Baseline values of 
indicator and 
disaggregates were 
calculated
Type; phase of 
development
Baseline Commodities
The study covered the following commodities and provinces: rice and corn in Bukidnon; hogs and broiler 
chicken in Batangas; Milkfish in Pangasinan and coco-sugar in Davao del Sur and Misamis Oriental. The 
commodities and locations were preselected by B-SAFE.
2. Evaluation Design and Methodology 
This study was designed to collect data to establish a baseline for a future performance evaluation; no 
control group was included, and no counterfactual was assessed. The design is non-experimental using a 
mix of household survey data to calculate descriptive statistics and Key Informant Interviews to provide 
qualitative data. Findings from this baseline study will be used to set targets for indicators, understand 
the context in which potential B-SAFE beneficiaries are operating, and, ultimately, provide values against 
which progress will be measured. 
2.1. Evaluation Questions 
The evaluation questions addressed to potential B-SAFE beneficiaries and stakeholders were intended to 
generate the baseline estimates for the B-SAFE indicators and answers to the B-SAFE evaluation questions 
related to: (1) level of postharvest losses, SPS conditions and risks; (2) organizational performance and 
risk management capacity of host government agency partners and communities; and (3) potential 
collaboration among value chain actors.
The questions addressed in the farm household baseline survey were on size of operation (e.g. area 
planted, number of animals raised, size of fish cages, number of production cycles, etc.); sources of inputs; 
farm practices and technologies, especially in relation to food safety (e.g. GAP, HACCP, GAHP, etc.); farm 
12
performance (e.g. yield, volume and value of production, etc.); postharvest and marketing practices; 
access to support services such as extension or credit; socio-economic and demographic characteristics 
of the farmers; and problems encountered especially related to food safety. 
The questions addressed to the traders (i.e., market functionaries) and processors include size of 
operation (volume and value of procurement); handling practices/technologies and standards used 
especially in relation to food safety; and major markets of the products. The questions addressed to value 
chain enablers (e.g., provincial and municipal local governments, trade associations, business service 
providers), which were asked through key KIIs, were on understanding of food safety, regulatory policies 
and framework, level of implementation and monitoring of food safety standards, facilities available, 
programs implemented, risk management plans, trainings attended on food safety and recommendations 
for improvement related to food safety. 
2.2. Situational Analysis Framework 
The value chain framework (Figure 2) was used to integrate the elements of the study. The analysis 
involved mapping the operators and functions along the value chain to provide context to the baseline 
and the calculated ex-ante values of the project’s indicators. The study carried out situational analyses of 
the respective value chains of the study’s selected baseline commodities. It (1) analyzed potential 
collaboration among chain actors; (2) assessed the risk management capacities of host local government 
agency partners and communities in the targeted project sites; (3) estimated the level of postharvest loss 
and examined the sanitary and phytosanitary conditions along value chains of each targeted commodity; 
(4) established the current state of adoption/use of improved management practices or technologies by 
agricultural producers and other value chain actors; (5) assessed the current organizational performance 
of targeted beneficiary organizations; and (6) specified the potential partners’ capacities and gaps in terms 
of meeting compliance to GAP, GMP, HACCP, or ISO certification standards.
13
Figure 2. Framework of the baseline study
2.3. Sampling and Data Collection Methods 
The study used a mixed method design which combined both quantitative and qualitative tools. For 
quantitative approach, the study surveyed the potential stakeholders and beneficiaries of the six 
commodity value chains, namely the producers and traders/processors. The sample size was established 
using the following sampling formula: 𝑛𝑙 =
𝑍
2𝑝𝑞
𝑒
2
; 𝑛𝑠 =
𝑛𝑙
1+ (
𝑛𝑙−1
𝑁
)
; where 𝑛𝑙
is the sample size; Z is the 
normal distribution value at 95% confidence level; p is the standard deviation (assumed as 0.5); q= 1-p; 
and e is the margin of error (7.5%). For a small population (i.e., sample size > 5% of the population), the 
sample size was adjusted using the formula for 𝑛𝑠
. Due to the complex design, the calculated sample size 
was adjusted for design effect (2 was used). Total sample size calculated for the survey covering the six 
commodities was 2,008 (Table 4). The total sample size was allocated between producers and 
traders/processors using 0.9 and 0.1 as weights (using information from Briones, 2016 on relative 
proportions of agribusiness actors). 
To determine the respondents in the study, a two-stage cluster design (barangays as clusters) with listing 
operation using fractional interval systematic sampling was employed (details shown in Annex 2. Selection 
of sample clusters using systematic sampling). In addition to the survey and as part of value chain 
mapping, the study also gathered primary data through KIIs (29 KIIs were conducted) of key value chain 
14
players covering production, trading/processing as well as value chain enablers such as trade associations, 
LGUs and NGAs, among others (Annex 3. List of organizations for key informant interviews). Three sets of 
research instruments were used in the study. These included i) Farm Production Survey Questionnaires 
(FPSQ); ii) Trader/Processors Survey Questionnaires (TPSQ); and iii) Key Informant Guide Questions 
(KIGQ). The FPSQs and TPSQs were tailored to the commodity under consideration while the KIGQs were 
tailored to the type of key informants (i.e., LGUs, trade associations, business service providers). Research 
instruments are provided in Annexes 4. Survey Questionnaires and 5. Guide questions for key informant 
interviews. 
Table 4. Sample sizes by commodity and province
 1/ From 2012 census of agriculture (latest census data). 
2.4. Data Processing and Analysis Methods 
The data were cleaned, encoded, and inputted to DevResults, Winrock’s monitoring and evaluation 
database, for the calculation of the indicators’ baseline values. The process involved calculating first the 
probability weights then the sample weights following the procedures outlined in the Sampling Guide for 
Beneficiary Based Sampling (Stukel and Friedman, 2016).
Probit models were also formulated and estimated to determine the factors affecting the adoption of 
select technologies of interest to B-SAFE.
Commodity/
Province Population 1/
Initial
Sample 
Size
Adjusted 
for Small 
Population
Adjusted 
for 
Design 
Effect
Final 
Calculated 
Sample 
Size 
(Producers)
Final 
Calculated 
Sample 
Size 
(Traders/ 
Processors)
Actual 
Number 
of 
Producers 
Surveyed
Actual 
Number of 
trader 
/Processors 
Surveyed
Total Producer Trader
Rice/ 
Bukidnon 8333
 
7,500 
 
833 171 171 342 308 34 330 36
Corn/ 
Bukidnon 38333
 
34,500 
 
3,833 171 171 342 308 34 330 36
Hogs/ 
Batangas 28000
 
25,200 
 
2,800 171 171 342 308 34 330 36
Chicken/ 
Batangas 7546
 
6,791 
 
755 171 167 334 301 33 192 36
Milkfish/ 
Pangasinan 3270
 
2,943 
 
327 171 162 324 292 32 300 33
Coco Sugar/ 
Davao del 
Sur and 
Misamis 
Oriental 3000
 
2,700 
 
300 171 162 324 292 32 186 17
Total 
88,482 
 
79,634 
 
8,848 
 
1,026 1,004 2008 1809 199 1668 194
15
2.5. Limitations of the Study 
As a major limitation, the study was done at the height of the pandemic which limited the mobility of the 
study team. As a result, the actual number of surveyed producers was only 1668 (short by 141). This is 
due to the fact that many coco sap tappers ceased from supplying for coco sugar (they are now supplying 
for alternative products). The lower samples for coco sugar will not affect the integrity of estimates for 
this commodity as the actual number of surveyed respondents was almost a complete enumeration. 
There were difficulties encountered in surveying the growers of broiler chicken. It was estimated that the 
shortfall in the number of samples would have minimal effect and would just raise the margin of error for 
the broiler chicken survey by at most 1%. 
3. Findings 
3.1. Indicators 
This section presents the estimated baseline values for the indicators by commodity and indicator 
disaggregates. The baseline values were established by determining each individual sample weight (the 
inverse of the probability weight) of each individual survey respondent. The calculation of baseline values 
of indicators was automated using DevResults.
3.1.1 Improved Management Practices and Technologies 
(Baseline for Indicator SI-4: Number of individuals in the agriculture system who have applied 
improved management practices or technologies)
Application of improved management practices and technologies varied widely by commodity and specific 
farm activities. There are certain technologies and practices that are extensively applied, but there are 
others that only few farmers have utilized. Table 5 shows that majority (85%) of rice farmers in Bukidnon 
have applied improved crop genetics by planting hybrid rice. Nearly all (90%) of corn farmers in Bukidnon 
have likewise applied new production technologies such as the use of high yielding varieties of corn. 
Interestingly, most of these adopters have planted the genetically modified BT corn as it can effectively 
control the corn borer. Some farmers plant plain hybrid corn, which has higher yield than open-pollinated 
corn. Soil related fertility management and soil conservation is being practiced by 76% of the rice farmers 
and 53% of the corn farmers. The practice of sustainable farming is not quite as popular with only 45% of
rice farmers and 38% of corn farmers who have been implementing it. Only a few of the rice and corn 
farmers in Bukidnon are into consolidated farming and value-added processing. 
Most (90%) of the hog farmers in Batangas have applied improved agricultural practices, which include 
breed selection, farm record keeping, proper handling of animals, and use of tools to minimize animal 
stress. Almost all (98%) of them practice proper livestock management through regular sanitation and 
disinfection of pens, proper water drainage, and application of standard biosecurity measures. There is 
also a significant number (90%) of farmers who have applied natural resource and ecosystem 
management such as proper waste management and pest and disease management. The use of tunnel 
vent is a common climate mitigation practice among 84.5% of the hog farmers. However, the survey 
revealed that postharvest handling and storage are not widely practiced particularly for farmers with 
privately owned and operated slaughterhouses. Some of these disregarded practices are proper 
sanitation, use of UV lamp for flies, and proper use of storage freezer. Carcass chiller and blast freezer are 
not being used. Only 14% of hog producers are involved in value added processing.
16
About 89% of broiler chicken producers practice improved cultural management specifically feed quality 
control, safe use of antibiotics, and pest and disease management. Other practices applied by the 
producers are natural resource management or sustainable practices (91%), water management (86%), 
and climate mitigation especially the use of tunnel vent (83%). On livestock management, 89% practice 
proper hygiene and sanitation, biosecurity measures, and use of probiotics and prebiotics. Less than half 
(46%) applied climate adaptation practices such as natural ventilation, blower, and cooling pads. Only 12% 
of producers practice good postharvest handling and storage such as sanitation of crates and animal 
handling facilities and only 23% are into value-added processing.
In milkfish production, the study found that 64% of grow out operators have adopted the recommended 
stocking densities but not the necessary method of feeding. Of this, 45% were using semi-intensive 
stocking, 29% were using extensive, and 25% were using intensive stocking density. The same stocking 
densities are recommended in cage culture but only 12% have adopted the recommendation and used 
intensive stocking rate. Acclimatization of the stock (fry or fingerling) is another important aspect in 
milkfish production, but only 77% of the surveyed producers are aware of the technology yet only half of 
them have applied it.
For coco sugar, 90% applied cultural management practices, 88% followed natural resources or ecosystem 
management and 95.16% practice improved post-harvest handling and storage. Only 3.32% practice 
improved marketing and distribution. Postharvest handling and storage are practiced by 95.16% of 
producers and traders while only 5.88% conduct value-added processing.
Another level of disaggregation is by sex and age of value chain actors. The study showed that in the case 
of rice, 57% of those who applied improved management practices or technologies were male and 43% 
were females, and the large majority (97%) were 30 years old and above. In the case of corn, 51% of 
producers who applied improved practices or technologies were male and 96% were more than 30 years 
old. In the case of hogs, 63% of producers who applied improved practices or technologies were male and 
99% were more than 30 years old. In the case of chicken, 62% of producers who applied improved 
practices or technologies were male and 96% were 30 years old and above. In the case of milkfish, 72% of 
producers who applied improved practices or technologies were male and 100% were 30 years old and 
above. In the case of coco sugar, 93% of producers who applied improved practices or technologies were 
male and 87% were 30 years old and above.
17
Table 5. Estimated number of individuals in the agriculture system who have applied improved management practices or technologies
# Description
Rice Corn Hogs Chicken Milkfish Coco Sugar
Producer Trader Total Producer Trader Total Producer Trader Total Producer Trader Total Producer Trader Total Producer Trader Total
1
No. of individuals 
adopting improved crop 
genetics 7,045 0 7,045 28,122 0 28,122 NA NA NA NA NA NA NA NA NA 0 0 0
Percent of total 84.54% 0.00% 84.55% 73.36% 0.00% 73.36% NA NA NA NA NA NA NA NA NA 0.00% 0.00% 0
2
No. of individuals 
adopting improved 
agricultural practices 7,500 0 7,500 34,186 0 34,186 25,200 0
25,200 6,721 0 6,721 2,708 0 2,708 2,700 0 2,700
Percent of total 90.00% 0.00% 90.00% 89.18% 0.00% 89.18% 90.00% 0.00% 90.00% 89.06% 0.00% 89.06% 82.81% 0.00% 82.81% 90.00% 0.00% 90.00%
3
No. of individuals 
adopting improved 
livestock/poultry 
management NA NA NA NA NA NA 25,200 2,333 27,533 6,721 0 6,721 NA NA NA NA NA NA
Percent of total NA NA NA NA NA NA 90.00% 8.33% 98.61% 89.06% 0.00% 89.06% NA NA NA NA NA NA
4
No. of individuals 
adopting wild-caught 
fisheries management NA NA NA NA NA NA NA NA NA NA NA NA 1,050 0 1,050
NA NA NA
Percent of total NA NA NA NA NA NA NA NA NA NA NA NA 32.10% 0.00% 32.10% NA NA NA
5
No. of individuals 
adopting improved 
aquaculture management NA NA NA NA NA NA NA NA NA NA NA NA 2,766 0 2,766 NA NA NA
Percent of total NA NA NA NA NA NA NA NA NA NA NA NA 84.60% 0.00% 84.60% NA NA NA
6
No. of individuals 
adopting improved 
natural resource or 
ecosystem management 
(i.e. sustainable practices) 3,773 0 3,773 14,636 0 14,636 25,200 0
25,200 6,155 0 6,155 1,609 0 1,609 2,627 0 2,627
Percent of total 45.27% 0.00% 45.27% 38.18% 0.00% 38.18% 90.00% 0.00% 90.00% 81.56% 0.00% 81.56% 49.20% 0.00% 49.20% 87.58% 0.00% 87.58%
7
No. of individuals 
adopting pest and disease 
management 7,500 0 7,500 33,559 0 33,559 25,200 0 25,200 6,721 0 6,721 1,324 0 1,324 0 0 0
Percent of total 90.00% 0.00% 90.00% 87.55% 0.00% 87.55% 90.00% 0.00% 90.00% 89.06% 0.00% 89.06% 40.50% 0.00% 40.50% 0.00% 0.00% 0.00%
8
No. of individuals 
adopting soil-related 
fertility and conservation 6,295 0 6,295 20,386 0 20,386 NA NA NA NA NA NA NA NA NA NA NA NA
Percent of total 75.55% 0.00% 75.55% 53.18% 0.00% 53.18% NA NA NA NA NA NA NA NA NA NA NA NA
9
No. of individuals 
adopting irrigation 5,682 0 5,682 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA
Percent of total 68.18% 0.00% 68.18% 0.00% 0.00% NA NA NA NA NA NA NA NA NA NA NA NA NA
10
No. of individuals 
adopting agriculture 
water management-non￾irrigation based 5,432 0 5,432 12,232 0 12,232 21,687 0 21,687 5,801 0 5,801 2,551 0 2,551 NA NA NA
Percent of total 65.18% 0.00% 65.18% 31.91% 0.00% 31.91% 77.45% 0.00% 77.45% 76.87% 0.00% 76.87% 78.00% 0.00% 78.00% NA NA NA
18
# Description
Rice Corn Hogs Chicken Milkfish Coco Sugar
Producer Trader Total Producer Trader Total Producer Trader Total Producer Trader Total Producer Trader Total Producer Trader Total
11
No. of individuals 
adopting climate 
mitigation 7,113 0 7,113 30,213 0 30,213 23,673 0
23,673 5,624 0 5,624 0 0 0 0 0 0
Percent of total 85.36% 0.00% 85.36% 78.82% 0.00% 78.82% 84.55% 0.00% 84.55% 74.53% 0.00% 74.53% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%
12
No. of individuals 
adopting climate 
adaptation/climate risk 
management 7,204 0 7,204 31,154 0 31,154 17,869 0
17,869 3,466 0 3,466 0 0 0 0 0 0
Percent of total 86.45% 0.00% 86.45% 81.27% 0.00% 81.27% 63.82% 0.00% 63.82% 45.94% 0.00% 45.94% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%
13
No. of individuals 
adopting improved 
marketing and 
distribution 68 25 93 209 0 209
 
153 0
153 1,521 0 1,521 0 0 0 29 71 100
Percent of total 0.82% 0.30% 1.12% 0.55% 0.00% 0.55% 0.55% 0.00% 0.55% 20.16% 0.00% 20.16% 0.00% 0.00% 0.00% 0.97% 2.35% 3.32%
14
No. of individuals 
adopting improved post￾harvest handling and 
storage 6,568 808 7,376 34,186 3,833 38,019 76 856 932 920 0 920 628 327 955 2,555 300 2,855
Percent of total 78.82% 9.70% 88.52% 89.18% 10.00% 99.18% 0.27% 3.06% 3.33% 12.19% 0.00% 12.19% 19.20% 10.00% 29.20% 85.16% 10.00% 95.16%
15
No. of individuals 
adopting value-added 
processing 0 732 732 0 0 0
 
 
1,451
 
2,489 3,940 990 713 1,703 245 327 572 0 176 176
Percent of total 0.00% 8.79% 8.79% 0.00% 0.00% 0.00% 5.18% 8.89% 14.07% 13.13% 9.59% 22.57% 7.50% 10.00% 17.50% 0.00% 5.88% 5.88%
Note: +/- 7.5% Margin of Error; Coco sugar is based on complete enumeration
3.1.2 Adoption of Improved Packaging, Equipment, Transportation and Cold Storage 
(Baseline for Custom Indicator CI-1: Number of individuals using improved packaging, equipment, transportation, or cold storage)
Improved Packaging. The application of improved packaging is very low among producers of rice (13%), corn (24%), chicken (2%), and coco sugar 
(40%). Improved packaging is not applicable to hogs as live animals are sold by growers. Harvested rice and corn are traditionally packed in sacks. 
However, the good agricultural practice of ensuring that recycled sacks are clean is not generally being practiced. Very few rice and corn traders 
also apply improved packaging, such as ensuring clean packaging materials and proper labeling. In the case of dressed broiler chicken, the 
traditional practice is packing it in unsealed plastics. Use of improved packaging material is high (90%) among milkfish growers and traders. At the 
milkfish production site, the harvests are packed in Styrofoam or metal container (locally termed “bañera”) filled with ice. Processed fish (e.g.,
deboned) are packed in well-sealed plastics.
Improved Equipment. The application of improved equipment is relatively high among producers of rice (75%), corn (62%) and milkfish (72%) 
(Table 6). In the case of rice producers, this includes the use of mechanized technologies such as tractors, mechanical transplanters and combine 
harvesters, although most of these are through the custom hiring service. For corn, improved equipment includes the use of chemical sprayers
19
and corn shellers, among others. In broiler chicken, about 3% use improved equipment. In the case of hogs, about 2% of producers and 25% of 
traders use improved equipment.
Improved Transportation and Cold Storage. All hog traders have used improved practices in transportation, particularly the use of vehicles and 
proper handling and restraining of animals and tools to minimize stress during transport. Approximately 8% of traders use dressing machines as a 
form of improved equipment. For coco-sugar, 24.20% of producers and traders use improved transportation while none used any cold storage 
facilities or improved equipment.
Table 6. Number of individuals using improved packaging, equipment, transportation, or cold storage
# Description
Rice Corn Hogs Chicken Milkfish Coco Sugar
Producer Trader Total Producer Trader Total Producer Trader Total Producer Trader Total Producer Trader Total Producer Trader Total
1
No. of individuals 
adopting Improved 
Packaging 818 303 1,121 7,318 1,859 9,177 0 0 0 141 0 141 2,609 327 2,936 885 300 1,185
Percent of total 
population 9.82% 3.63% 13.45% 19.09% 4.85% 23.94% 0.00% 0.00% 0.00% 1.88% 0.00% 1.88% 79.80% 10.00% 89.80% 29.52% 10.00% 39.52%
2
No. of individuals 
adopting Improved 
Equipment 6,250 25 6,275 22,582 1,162 23,743 76 0 76 177 63 240 2,021 327 2,348 0 0 0
Percent of total 
population 75.00% 0.30% 75.30% 58.91% 3.03% 61.94% 0.27% 0.00% 0.27% 2.34% 0.83% 3.18% 61.80% 10.00% 71.80% 0.00% 0.00% 0.00%
3
No. of individuals 
adopting Improved 
Transportation 3,454 480 3,934 9,827 2,556 12,383 305 700 1,005 248 0 248 177 327 504 479 247 726
Percent of total 
population 41.45% 5.76% 47.21% 25.63% 6.67% 32.30% 1.09% 2.50% 3.59% 3.28% 0.00% 3.28% 5.40% 10.00% 15.40% 15.97% 8.24% 24.20%
4
No. of individuals 
adopting Cold storage 0 0 0 0 0 0 76 0 76 283 0 283 579 327 906 0 0 0
Percent of total 
population 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.27% 0.00% 0.27% 3.75% 0.00% 3.75% 17.70% 10.00% 27.70% 0.00% 0.00% 0.00%
 Note: +/- 7.5% Margin of Error; Coco sugar is based on complete enumeration
3.1.3 Farms, Firms and Laboratories with GAP, GMP, HACCP, or ISO certification 
(Baseline for CI-2: Number of farms/firms/ laboratories with GAP, GMP, HACCP, or ISO certification)
The study found very limited number of farms and firms with GAP, GMP, HACCP or ISO certification, regardless of commodities (Table 7). This is 
not surprising especially for products sold in primary form as the market has not yet significantly incentivized compliance to the standards. 
Compliance to standards is higher among processors as products become more differentiated (such as in the case of coco sugar) and for large 
commercial farms such as in the case of most hogs, broiler chicken and milkfish growers.
In Bukidnon, the survey found only 0.32% GAP certified rice farms and none for corn. There were 49 corn producers who claimed they were 
applying GAP, but none is certified. To be certified for GAP, farmers must apply the complete package of practices prescribed under this 
20
certification. The survey found that most farmers apply only certain components of the package, and there was no conscious effort to comply with
all the requirements. In most cases, the GAP compliant practices being applied by farmers were actually part of their traditional practices which 
happened to be the same practices prescribed under GAP.
In the case of hogs, the estimated baseline proportion of farms/firms/laboratoriesthat are HACCP certified is 0.91%. While 33% of farms are aware 
of the GAHP, survey results showed that 45% are actually practicing components of GAHP without realizing them. For broiler chicken, the standard 
applicable to raising poultry is embodied in PNS/BFAR 84:2016 Code of GAHP for Chickens – Broilers and Layers. Survey results of broiler farms 
revealed that 10.94% of respondents claimed to be GAHP-certified. The proportion of producers who are aware of GAHP is 32%, and those 
practicing GAHP but not all its components is around 30%. Almost all respondents are willing to adopt the standard. About 4.69% of farmers 
reported that they have HACCP-certification.
In the case of milkfish, there were 6 producers with certification for GAP and three processors with HACCP certification. Two of these three HACCP 
milkfish processors are actually the largest seafood processors in the Philippines, namely the Anjo Farms in San Fabian and Korea-Philippines 
Seafood Processing Complex in Dagupan, Pangasinan. 
The standard for coco sugar is provided in PNS/BAFPS 76:2010 for Coconut Sap Sugar which establishes the system of grading and classifying 
commercial coconut sap sugar obtained from fresh sap tapped from unopened inflorescence of coconut trees. Other standards are on GAP, HACCP, 
Organic Agriculture (OA), and FDA. The baseline survey was able to document 62 producers and 4 traders that have standard certifications. All 62 
producers certified OA, while some traders are HACCP and FDA certified.
Table 7. Number of farms/firms/laboratories with GAP, GMP, HACCP, or ISO certification
Certification
Rice Corn Hogs Chicken Milkfish Coco Sugar
Producer Trader Producer Trader Producer Trader Producer Trader Producer Trader Producer Trader
GAP 23 0 0 0 NA NA NA NA NA NA 0 0
% 0.30 0.00 0 0.00 NA NA NA NA NA NA 0.00 0.00
GAHP NA NA NA NA 535 0 743 0 NA NA NA NA
% NA NA NA NA 2.12 0 10.94 0.00 NA NA NA NA
GAqP NA NA NA NA NA NA NA NA 59 0 NA NA
% NA NA NA NA NA NA NA NA 2.00 0.00 NA NA
HACCP 0 0 0 0 229 467 318 0 0 0 0 2
% 0.00 0.00 0.00 0.00 0.91 16.67 4.69 0.00 0.00 0.00 0.00 11.76
Organic Agriculture 0 0 0 0 0 0 0 0 0 0 62 0
% 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 33.33 0.00
ECC 0 0 0 0 0 78 0 0 0 0 0 0
% 0.00 0.00 0.00 0.00 0.00 2.78 0.00 0.00 0.00 0.00 0.00 0.00
NMIS 0 0 0 0 0 700 0 147 0 0 0 0
% 0.00 0.00 0.00 0.00 0.00 25 0.00 19.44 0.00 0.00 0.00 0.00
FDA 0 0 0 0 0 0 0 0 0 99 9 2
% 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 30.31 0.00 11.76
 Note: +/- 7.5% Margin of Error; Coco sugar is based on complete enumeration
21
3.1.4 Volume and Value of Annual Sales of Farms and Firms 
(Baseline for Indicator SI-19: Annual volume of production; and SI-18: Annual Value of sales of 
farms and firms)
The baseline value of total annual sales (Table 8) of rice producers in Bukidnon was estimated at USD 
51,381,182 or an average annual sale of USD 6,851 per producer per year. For corn, the baseline total 
annual sale was USD 138,215,028 or USD 4,018 per individual. The total value of annual sales of producers 
for hogs in Batangas is USD 670,308,388 or USD 26,600 per individual grower, while that for broiler chicken 
is USD 463,126,838 or USD 68,911 per grower. There are many large commercial growers of hogs and 
broiler chicken in Batangas, which explains the large values of sales. For milkfish in Pangasinan, the 
baseline total annual value of sales from producers is USD 367,982,355 or USD 131,157 per individual 
grower. Production of milkfish is typically in large commercial operation, which explains the large value of 
sales per individual operator. For coco sugar in Davao del Sur and Misamis Oriental, total value of sales is 
USD 39,920,759 or USD 14,785 per individual. 
The baseline values were generated from the baseline volume of production shown in Table 9. The data 
reflect the volumes of production per year per individual producer. In the case of rice and corn where 
there are two cropping cycles per year, the indicated volume may be divided by two to get the volume 
per cropping cycle, which may be further divided by the average farm size to get the volume per hectare. 
Using 1.5 and 1.2 as the respective average rice and corn hectarage in Bukidnon, the estimated baseline 
yield per hectare is 3.4 MT for rice and 3.6 MT for corn. The Philippines Statistics Authority (PSA) data on 
rice and corn from 2010 to 2020 showed that average yield may fluctuate between 3.5 MT/ha to 4.5 
MT/ha for irrigated rice and 2.8 MT/ha to 3.2 MT/ha for rainfed rice. For yellow corn, the average yield in 
the Philippines may fluctuate from 3MT/ha to 4MT/ha. The estimated baseline for rice and corn in 
Bukidnon are very close to the actual values, attesting to the accuracy of the baseline estimation process 
employed in the study.
Table 8. Value of annual sales of farms and firms
Commodity
Producer Trader Total
Total Annual 
Sales, in USD
Average 
Sales per 
Individual, in 
USD
Total Annual 
Sales, in USD
Average Sales per 
Individual, in USD
Total Annual 
Sales, in USD
Average Sales per 
Individual, in USD*
Rice 51,381,182 6,851 79,086,014 94,907 130,467,197 15,656.68
Corn 138,215,028 4,018 157,709,634 41,142 295,924,662 7,719.84
Hogs 670,308,388 26,600 904,168,109 332,171 1,574,476,497 56,231.30 
Chicken 463,126,838 68,911 374,838,104 525,957 837,964,942 111,047.56 
Milkfish 367,982,355 131,157 190,742,586 583,311 558,724,941 170,863.89 
Coco Sugar 39,920,759 14,785 39,942,751 133,143 79,863,511 26,621.17 
Note: +/- 7.5% Margin of Error; Coco sugar is based on complete enumeration
*Computed as the total value of sales divided by the value chain population presented in Table 4.
Table 9. Volume of commodities sold by farms and firms
Commodity
Producer Trader Total
Total 
Volume,
in MT
Average 
Volume per 
Individual,
in MT
Total Volume, 
in MT
Average Volume 
per Individual, in 
MT
Total Volume, in 
MT
Average Volume 
per Individual, in 
MT*
Rice 77,040 10.27 53,461 64.16 130,501 15.66
22
Commodity
Producer Trader Total
Total 
Volume,
in MT
Average 
Volume per 
Individual,
in MT
Total Volume, 
in MT
Average Volume 
per Individual, in 
MT
Total Volume, in 
MT
Average Volume 
per Individual, in 
MT*
Corn 298,113 8.67 267,800 69.86 565,913 14.80
Hogs 118,707 4.71 306,695 112.67 425,402 15.20
Chicken 108,915 16.21 58,535 82.13 167,450 22.20
Milkfish 90,804 32.36 36,924 112.92 127,728 39.06
Coco Sugar 7,878 2.92 4,309 14.36 12,187 4.06
Note: +/- 7.5% Margin of Error; Coco sugar is based on complete enumeration
*Computed as the total volume of sales divided by the value chain population presented in Table 4.
3.1.5 Food Safety Risk Management Plans Implemented for the Industry
(Baseline for Indicator SI-11: Number of host government or community-derived risk 
management plans formally proposed, adopted, implemented, or institutionalized)
The baseline study found there were 16 host government or community-derived risk management plans 
formally proposed, adopted, implemented, or institutionalized (Table 10).
Table 10. Number of host agencies with risk management plan
RMP Phase Community Government Total
Adopted 1 0 1
Implemented 1 7 8
Institutionalized 0 5 5
Proposed 0 2 2
Total 2 14 16
3.2. Findings on Value Chain Assessment (Situational Analysis) 
This section presents the value chain analysis by commodity focusing on the value chain maps; level of 
postharvest loss, SPS conditions and risks; organizational performance and risk management capacity of 
potential B-SAFE partners such as host government agencies and communities; and potential for 
collaboration among value chain actors.
3.2.1 Rice in Bukidnon
The rice value chain in Bukidnon is depicted in Figure 3. The various nodes include input provision, 
production, aggregation, milling/processing and various stages of trading up to final sales to consumers. 
Input provision and production are the upstream part of the chain. 
23
Figure 3. Rice value chain, Bukidnon, 2021
Input Provision. The major players are the seed growers, agri-input suppliers, private companies, and 
government organizations, particularly the DA which has been distributing hybrid and certified seeds as 
part of its support to farmers. There are farmers who also grow their own seeds. Among the popular 
inbred seeds in Bukidnon are RC 18, RC 216, RC 15 and RC 222, the genetic material of which are either 
from the local office of the DA or Philippine Rice Research Institute (PhilRice). A popular inbred sourced 
from agri-supply dealers is RC 358. For hybrid seeds, the popular ones include LP 937, TH 82, and US 88, 
all from DA and the M11 hybrid from PhilRice.
Production. Land preparation is done by farmers either using animal, machine or a combination of animal 
and machine labor. For machine labor, especially in the case of smallholder rice producers, this is usually 
through the custom hiring services. Large rice producers often have their own farm machineries. Cultural 
management include fertilizer application and pesticide spraying. Most farmers mainly use inorganic 
fertilizer. Other farmers use organic fertilizer such as bagasse from the sugar central which is applied 
before planting. In addition, 2 bags of 46-0-0, then 2 bags of 16-20-0 are applied at flowering stage. 
Carbonized rice hull is also used, which is effective in controlling snails. Foliar fertilizer is used after 
flowering. Rice is harvested after 100 to 110 days, dried to 14% moisture content mostly using solar dryers,
while others, especially the large ones, use mechanical dryers. About 4 metric tons is produced per 
hectare with about 5 percent losses from harvesting to drying. There are commonly two cropping cycles 
per year. 
Aggregation. Paddy traders dominate the aggregation part of the value chain buying as much as 56% of
total output. Other players at the paddy aggregation stage include agents/assemblers, cooperatives, and 
the local National Food Authority (NFA), albeit the volume that passes through this channel is small. 
Milling. Large rice millers who buy paddy, mill this and sell rice to wholesalers in various parts of the 
province and even outside the province dominate the processing stage of the value chain. There are also 
smaller custom millers who just offer milling services to farmers. Rice from Bukidnon is sold and consumed 
mostly in the province, but a significant portion is also sold to other provinces and reaches as far as Manila. 
24
Government Rice Procurement. For the government rice procurement through the NFA, there are five 
existing warehouses in Bukidnon. The NFA Warehouse in Aglayan, City of Malaybalay has a capacity of 
50,000 bags, the warehouse located in Valencia has 100,000-bag capacity and another in Kalilangan with 
50,000 bags. There are three NFA Warehouses located in Maramag: the Musuan Triplex has a capacity of 
500,000 bags, Maramag-Main with 100,000 bags and Maramag Annex with 250,000 bags.
Level of Postharvest Losses, SPS Conditions and Risks
Postharvest Losses. – Based on the survey, the level of annual postharvest losses in rice in Bukidnon is 
about 3.2 percent from harvest to drying. 
Based on KIIs, it is estimated that another 4 
percent is lost in milling and trading (Table
11). Thus, total losses from harvest to final 
sale to consumer can be around 7.2 percent.
This approximates the losses reported in 
earlier studies (Dela Cruz, R. and G. Calica, 
2016). Post-production losses occur during 
threshing and drying (especially using 
pavement in drying) while in milling it is primarily due to spillage and machine inefficiency. Decay and pest 
infestation are the major causes of losses during storage.
Food Safety Risks. – There are food safety risks along the entire rice value chain that should be given 
adequate consideration. Contaminants in rice include agricultural chemicals, foreign materials such as 
glass, metal, sticks, stones, and unwanted grains. In addition, the rice might be contaminated with insects, 
molds, mycotoxins, or bacteria. The Bureau of Agriculture and Fisheries Standards (BAFS) prescribes a 
national standard for rice. The standard moisture content should be 14% or lower to prevent bacterial 
and molds infestation. For heavy metals, the maximum safety levels for rice were set for arsenic (0.20-
0.35 mg/kg), cadmium (0.40 mg/kg), lead (0.20 mg/kg), and for aflatoxin (20 ug/kg). The maximum residue 
limits for pesticides was also set for microbial contaminants such as Bacillus cereus at 100 CFU/g (Food 
Safety Measures for Rice: Memorandum Circular 2020). Examples of maximum residue limits for common 
pesticides include bentazone (0.10mg/kg), and carbosulfan (0.20mg/kg). 
GAP Awareness and Adoption. – The primary SPS for rice is PNS/BAFS 141:2019 which is the Code of 
Good Agricultural Practices for Rice. It prescribes a set of good practices in all operations including farm 
location, environment, structures and facilities, farming practices, worker’s health, and farm 
management. However, only 0.30 % of rice farms in Bukidnon are GAP certified. About half of the 
surveyed farmers claimed to be aware of GAP and 32% claimed they were adopting GAP practices (Table 
12). When asked if they are willing to adopt GAP, majority (76%) of the surveyed farmers answered in the 
affirmative. This begs the question of why there is very limited GAP certification despite the various 
programs to promote GAP.
Table 12. Awareness, practice, certification, and willingness to adopt GAP, rice farmers, Bukidnon
Awareness/Practice/Certification Number Reporting Percentage
Aware of GAP
Yes 166 50.3
No 161 48.8
Practicing GAP
Yes 105 31.8
No 207 62.7
Table 11. Percentage of postharvest losses, rice, Bukidnon
Cropping Harvest to 
Drying (%) 1/
Milling to Final 
Sale (%) 2/ Total
1st 1.83 2 3.83
2nd 1.37 2 3.37
Annual 3.20 4 7.20
1/ Values are based on farm survey; 2/ Values are based on KIIs
25
Awareness/Practice/Certification Number Reporting Percentage
GAP Certified
Yes 7 2.1
No 315 97.9
Willing to Adopt GAP
Yes 251 76.1
No 76 23.0
The study found that those who claimed to be adopting GAP are often just practicing a few components 
of it, which happened to be their traditional practices. It was obvious that farmers did not know that
GAP is a package of good practices and that adoption of just one or two components of it would not merit 
certification. On area assessment for instance, which is integral to the GAP package of best practices, a 
majority (58%) of farmers do not know how to do the assessment (Rice Appendix Table 1). A large 
majority (65%) also lack knowledge on agricultural water management. More information campaigns and 
even trainings would be needed to improve farmer’s understanding of the GAP standard. 
Factors Affecting GAP Adoption. – To enhance the chance of success of promoting GAP, the study 
examined what characteristics of farms/farmers would have greater likelihood of adopting GAP 
certification. This was done by specifying and estimating a Probit model relating willingness to adopt with 
some farmer’s and farm’s characteristics. Results showed that farmers are more likely to adopt GAP if 
they own their farm; the farm is irrigated; they have access to agricultural insurance; farm-to-market 
roads are in good condition; and if the farmer is a member of a farmers’ organization (see Rice Appendix 
Table 2 for the probit model and results). 
Organizational Performance and Risk Management Capacity of Host Government Agency Partners and 
Communities 
Organizational Performance. – From the KIIs, there were at least 3 government institutions with risk 
management plans being implemented: the Provincial Agricultural Office (PAO) of Bukidnon, the DA 
Regional Field Office of Region 10 (DA RFO 10), and the City Agricultural Office (CAO) of Valencia City. The 
Bukidnon provincial and city LGUs are promoting GAP and OA as part of their food security programs. 
Trainings on GAP are conducted in collaboration with the Agricultural Training Institute (ATI). On GAP 
certification, the PAO provides coaching/advise and technical guidance while the Municipal LGUs, 
specifically the Municipal Agricultural Office (MAOs) assist farmers in having their farms certified. Despite 
these initiatives, only 2.1 % of rice farms are GAP certified.
Other Food Safety/Quality Risks. – Other production and food safety/quality risks identified in Bukidnon 
include rice black bug (RBB) infestation and improper branding of rice (rice presented/sold as organic). In 
response, local agencies and government units have implemented various initiatives. For RBB infestation, 
the regulatory division of DA RFO 10 undertakes the following: (a) continuous monitoring of RBB
infestation; (b) dissemination of information to farmers and public, including the results from surveillance 
and monitoring of RBB; (c) training and information dissemination on Integrated Pest Management (IPM); 
(d) conduct of ocular inspection and surprise farm visits; and (e) promotion of synchronized planting in 
irrigated rice areas threatened by RBB, as practiced in most areas in the cities of Valencia and Malaybalay.
Synchronized planting is practiced by farmers in contiguous areas/ farm lots included in lateral irrigation 
canals and organized by the National Irrigation Administration, whose farmer members own the farms 
near or around the canals. Current practice of synchronized planting with improved or scheduled release 
of water for irrigation 14 days before and 14 days after planting, enables farmers to plant/harvest rice 
twice a year.
26
The CAO - Valencia also has rice monitoring teams conducting ocular inspection, monitoring, and reporting 
of pest incidence and providing advice to farmers. The CAO conducts massive information dissemination 
before the full moon for farmers to be vigilant in protecting their crops. Once infested, farmers are advised 
to get rid of RBB using the solar dryers which are converted to covered court with lights that attract RBB. 
It also distributes bio-control agents such as Trichogramma spp. for stem borers and green muscardin. 
The CAO supports the Bantay Peste Brigade (Pest Guards) composed of trained farmers on IPM in rice, 
corn, vegetables in upland/lowland areas, and monitors pest infestation in the barangays.
The PAO promotes and implements IPM in rice to prevent RBB infestations. Budgets for IPM trainings at 
the local levels are sourced from DA’s Rice Competitiveness Enhancement Fund. Topics include the 
PalayCheck system in rice production as developed by PhilRice, cultural practices in management of RBB, 
and use of rice varieties resistant to tungro, among others. The PAO also conducts Information, Education 
and Communication (IEC) campaign on the importance/ benefits of IPM to discourage farmers from 
applying toxic chemicals and pesticides in their farms.
In the case of organic rice, an important issue is the practice of some farmers to claim their produce as 
organic although their farms have no OA certification. To address this, the CAO established an internal 
control system for still-to-be certified claims of organic rice, calling the output of these farms as 
“organically grown rice”. The certifiers for first-party organic certification visit/monitor the farms and 
output of farmers and conduct surprise visits.
Risk Management Capacity. – The technical capacity of local agencies and LGUs in Bukidnon to deal with 
the identified risks appears adequate. From the KIIs, the major limitation is with the budget needed to 
fund the field personnel involved in GAP promotion and pest monitoring, training support for farmers on 
GAP, OA and other food safety concerns, and provision of assistance to farmers and communities in terms 
of needed pre and postharvest facilities and equipment. This includes support to farm storage facilities 
(GAP requires farms to have storage areas for farm inputs, pesticides, etc.), mechanical dryers to minimize 
losses especially during inclement weather and to minimize use of pavement in drying. The DA has been 
providing support to DA RFO 10, LGUs and farmers associations from the Rice Productivity Enhancement 
Fund under the Rice Tariffication Law. However, the support is still inadequate to meet the needs of the 
farmers.
Potential Collaboration Among Value Chain Actors
Among Local Government Agencies and LGUs. – Partnerships and collaboration among DA agencies and 
DA RFO 10 are implemented through the DA’s national banner programs. Collaboration exists among DA,
ATI, National Irrigation Administration, Fertilizer and Pesticide Authority (FPA) and LGUs; and among DA 
RFO 10, Department of Science and Technology (DOST), Department of Health (DOH), and FDA. 
Among Government Agencies and the Private Sector. – The LGUs and the private sector companies and 
farmers’ associations collaborate in many areas, including the following: inter-agency collaboration on 
food safety at the regional level (DA, DOST, DOH, FDA, etc.) and on training and orientation on GAP and 
OA; education of farmers on the dangers of chemicals; provision of farm inputs such as seeds, biocontrol 
agents, fertilizers and farm machinery; assistance to farmers‘ association in the establishment of Rice 
Processing Center, organic certification through first party certification (or Participatory Guaranty System) 
and marketing support through Organic Trading Post. The DA’s assistance to cooperatives in terms of 
postharvest machineries/equipment are well acknowledged but not sufficient to address the needs of 
farmers. For seed production, the provincial DA also collaborate with the Bukidnon Seed Growers 
Association, MU Seed Net, Hybrid Seeds Companies and PhilRice CMU are partners for seed production. 
The Provincial Local Government Unit (PLGU) also provides such facilities as: Techno Demo Center, 
Technology Livelihood Development Center, Mini Nursery, and Vermi Compost Demo. On the other hand, 
27
the Municipal and City Local Government Units (M/CLGUs) provide the soils laboratory, Bio-N mixing 
plant, nurseries, and vermi compost.
Among Private Entities. – One collaboration uncovered in the KIIs was the case of a lead firm model of 
value chain collaboration. This is an interesting model especially for its potential to pave the way for 
consolidated rice farming. The collaboration is between a large rice miller (the Acosta Rice Mill in 
Maramag, Bukidnon) and about 35 small rice farmers. The rice miller organized 35 small rice farmers (total 
of 60 hectares) and provides them with PhP15,000 loan every cropping season. She also provides all the 
production inputs as an in-kind loan. She hired agricultural technicians as extension workers to work 
closely with the farmers, supervise all the technical aspects of production and ensure that inputs are 
properly applied. She encourages minimal use of inorganic inputs and pesticides although the farms are 
still employing conventional (not organic) production systems. The farmers provide the needed labor and 
manage their own farms. The harvest is sold to the miller. The model appears successful as the miller 
reported during the KII that the farms have been generating high yields and lower production cost, 
therefore higher profits for the farmers and for her.
This may be considered as a lead firm model of value chain collaboration. Large private firms in the value 
chain which exert much influence on the smaller players may be tapped to lead value chain improvement 
measures, especially in ensuring food safety and productivity of the entire value chain.
3.2.2 Corn in Bukidnon
The value chain map of corn in Bukidnon is shown in Figure 4. The value chain functions include input 
provision, production, and aggregation at the barangay and municipality levels, primary and secondary 
processing, trading, and final sales.
Figure 4. Value chain of corn, Bukidnon, 2021
Input Provision. The major inputs in producing yellow corn in Bukidnon are seeds, fertilizers, and 
chemicals. The popular brands of seeds are Pioneer, Bioseed, Evogene and Maharlika. Seeds of Pioneer 
and Bioseed are registered at the National Seed Industry Council (NSIC) as genetically modified organisms, 
while the others are not but are also resistant to corn borer and glyphosate herbicide. Fertilizer and 
pesticides are easily sourced from a large number of agro-chemical dealers/stores all over the province.
28
Production and Post-Production. This stage includes land preparation (i.e. plowing and harrowing), 
planting, nutrient management, water management and pest management (including weeds), among 
others. The crop is harvested 95-120 days after planting. Post-production practices include shelling, drying 
and storage.
Aggregation. There are many types of yellow corn traders in Bukidnon depending on scale of procurement 
and business set-up. Relatively small traders are known as barangay or village level traders while the larger 
ones are known as municipal/provincial traders. An important intermediary or facilitating agency of the 
yellow corn supply chain in Bukidnon is the cooperative-processor. An example of this is the Farm 
Cooperative Incorporated, which owns and operates several postharvest facilities such as mechanical 
driers and trucks. It offers drying and trucking services to its farmer members for a fee. 
Marketing. Dried corn is sold by farmers and traders to local feed millers. These feed millers, such as 
BMeg, CJ Feeds, and Mambatangan Milling Corporation have business operations in the province of 
Bukidnon. Others are sold outside Bukidnon, such as the Bounty Agro Ventures and Pronatural Feed 
Corporation, which are operating in Cagayan de Oro City.
Level of Postharvest Losses, SPS Conditions and Risks
Postharvest Losses. – Based on the survey, the level of annual postharvest losses in corn in Bukidnon is 
about 8 percent from harvest to drying and storage. It was also learned, albeit from KIIs that another 4 
percent is lost in milling and trading (this is just an estimate). Post-production losses occur during 
threshing and drying 
(especially using 
pavement in drying) while 
in milling it is primarily due 
to spillage and machine 
inefficiency. Decay and 
pest infestation are the 
major causes of losses 
during storage (Table 13).
The estimated losses 
approximate those 
reported in earlier studies (Dela Cruz, R. and G. Calica, 2016)
Food Safety Risks. – The main food safety risk in corn is aflatoxin. This is a group of highly poisonous and 
carcinogenic compounds which are produced by strains of the fungi, Aspergillus flavus Link and Aspergillus 
parasiticus Speare. The Code of Practice for the Prevention and Reduction of Aflatoxin Contamination in 
Corn (PNS/BAFS 27:2018) was developed to provide uniform guidance for all corn stakeholders, as well as 
serve as common reference for compliance to GAP for corn, both for human and animal consumption. 
Other food safety concerns include the lack of separate structure for the safe storage of farm inputs such 
as pesticides and fertilizers; improper use of herbicide especially for the round-up ready genetically 
modified corn, which is a concern in terms of pesticide residues and adverse effect to the environment 
especially in sloping areas due to soil erosion and landslides; and the use of ‘sigue-sigue’ seeds (cross 
pollinated genetically modified corn with the traditional varieties), with round-up ready genes from 
genetically modified corn but did not pass the usual regulatory system. 
The relevant standards and regulations on corn are the GAP Corn, OA Certification, and the Philippine 
National Standards for Corn Grits (PNS/BAFPS 15: 2004). The GAP Corn is a consolidated safety and quality 
Table 13. Percentage of postharvest losses, corn, Bukidnon
Cropping
Harvesting, 
Milling, Drying 
and Storage 
(%) 1/
Milling, 
Storage, 
Transport to 
Final Sale (%) 2/
Remarks
1st 4 1 to 3 Major losses occur during shelling 
and drying (especially during 
inclement weather). Storage losses 
are due mainly to rat infestation or 
when the pile gets wet.
2nd 4 1 to 3
Annual 8 2 to 6
1/ Values are based on farm survey; 2/ Values are based on KIIs
29
standards for the production, harvesting and on-farm postharvest handling and storage of corn. The OA 
Certification is a set of production and handling practices prescribed for those who would like to produce 
and market organic corn. The PNS/BAFPS 15:2004 prescribes the classification of corn grits based on 
physical characteristics and practices existing in the sector. It includes sections on the essential 
composition and quality features, classification and grading, sampling and methods of analysis, 
determination of moisture content, packing, marking, contamination, and hygiene (Corn Appendix Table 
1).
There is no GAP certified farm in Bukidnon. Certification of farms for GAP is based on a package of 
practices that have to be complied. While some farmers claim that they are applying GAP, they usually fail 
during inspection as there are components in the package which have not been adopted. The Bureau of 
Plant Industry (BPI) has a GAP inspection team for the GAP certification; they pre-assess, monitor, and 
inspect the farms that are applying for GAP certification.
The reasons for low adoption of GAP among 
corn farmers is similar to those of rice 
farmers. There were a very limited number 
(only 7.3%) of corn farmers who have 
attended GAP trainings (Table 14), and very 
few have also attended trainings on OA and 
Farmer Field Schools where GAP and other 
food safety compliant production practices 
are discussed.
Other Risk Factors in Corn Production. – An important risk factor in corn production is the FAW infestation. 
The pest is an enormous threat as it could devastate an entire production. However, the problem remains 
under control due to the effort of the DA RFO 10 on surveillance, monitoring and timely control measures. 
Synchronizing production may be necessary for more effective control. Consolidated farming is not yet 
being practiced but may prove to be a viable measure in the future to synchronize operations, especially 
on pest management and to avail of economies of scale.
Assistance Needed by Corn Farmers. – A large 
majority (70%) of corn farmers in Bukidnon 
expressed their need for trainings and farm 
demonstrations on GAP and other practices 
that can improve productivity. A significant 
percentage also said they need assistance for 
the procurement of corn shellers (21%); 
seeds, chemicals, and fertilizer (16.7%) and 
tractors (14.5%). There were also those 
(14.5%) who need agricultural loans to 
finance their operation (Table 15).
Organizational Performance and Risk Management Capacity of Host Government Agency Partners and 
Communities and Potential Collaboration Among Value Chain Actors
Table 14. Food safety and productivity related trainings 
attended by corn farmers and traders, Bukidnon
Trainings Attended by Corn 
Farmers (n=191) Number Percent of 
population
 GAP 14 7.3
 Organic Agriculture 12 6.3
 Farmer Field School 33 17.3
 Food Handling 18 35.3
Table 15. Assistance needed by corn farmers, Bukidnon
Assistance Needed Number Percent of 
Population
Seeds/Chemicals/Fertilizer 55 16.7
Training/Farm Demonstration 231 70.0
Shellers 68 21.0
Tractor 48 14.5
Agricultural Loans 48 14.5
Crop Insurance 8 2.4
Dryer 25 7.6
30
Corn and rice farmers face almost identical production and post-production challenges as well as food 
safety and quality risks. Hence in Bukidnon, the local government agencies and local government units 
always place these commodities under a single program. The possible government agency partners of B￾SAFE will therefore be the same for the two commodities. The discussion on organizational performance 
and risk management capacity of host government agency partners in rice (see earlier section) also applies 
for corn. As supplementary information though, this section highlights the role of PhilMaize and its 
representative organization in Bukidnon, which is the Impasugong Samahang Nayon (ISN).
PhilMaize and ISN. PhilMaize is a national corn farmers association which significantly contributed to the 
formulation of GAP in corn production seven years ago. In Bukidnon, its member cooperative is ISN. This 
cooperative organized a cluster of 350 hectares of adjacent corn farms from its 250 members. The 
cooperative provides post-harvest facility, up to date market information, and gives advice to members 
to improve their capacity. The farmer members of the cluster still manage their own farms, but much 
coordination and synchronization of activities is realized as a result of clustering. There is still no 
consolidated farming model for corn in Bukidnon, albeit this model may pave the way for widespread 
adoption in the province.
3.2.3 Hogs in Batangas
The hogs value chain in the province of Batangas is made up of four major nodes: input suppliers, 
producers, traders and processors, and consumers (Figure 5).
Figure 5. The supply chain of hogs and the three identified value-chain maps
Input suppliers. The chain starts with input suppliers, which are the feed mills and breeder farms. Feed 
constitutes 65% to 80% of the cost of production while breeding stock or piglets account for 15-25%. 
31
About three fourths of hog raisers source their feed from commercial feed millers which are members of 
the Batangas Feed Millers Association; 23% from cooperatives and associations who operate their own 
feed mills; and 2% have their own feed mills. A small number of smallholder farmers give swill feeds 
sourced from within the locality or neighborhood. Farmers use both AI and natural breeding practices. 
Semen for AI for may come from ITCPH, AI centers of LGUs, and in Europhil Swine Genetics in Ibaan as the 
main commercial source. Producers source other inputs such as biologics from agrovets and agrodealers.
Pig Producers. Smallholder farmers are either independent producers or members of producer 
organizations or cooperatives which help in providing technical support, input supplies, logistics, and 
market facilitation, among others. Backyard raisers who are members of cooperatives, such as the SIDC 
serve as contract growers, locally dubbed as the ‘paiwi’ system. The cooperatives provide farmers with 
the grower stock, sometimes with other inputs such as feed and other supplies, and buys back the 
market/finishing hogs, sells the animals, and takes their share, which is usually about 40 to 50% of net 
income. Large hog raisers are independent producers, contract growers or integrators. Some are 
members of hog raisers association, such as the UNIBAT or connected to large companies. Integrators are 
those involved in hog production and post-production operations such as trading and primary or 
secondary meat processing activities. Majority of the farmers use improved breeds, while only 5% use 
native breeds.
Traders and Processors. Majority (94%) of farmers sell their hogs live to traders, while the rest venture 
into direct selling of carcass and meat cuts (Hogs Appendix Table 1). Survey data showed that 75% of 
traders slaughter the hogs in abattoirs within the province before distributing them within the province 
(Hogs Appendix Table 2). Other traders are agents or animal haulers who transport live animals to other 
parts of the province, neighboring provinces, and Metro Manila.
Pork Trading Standards and Regulations. A number of standards for meat quality and safety have been 
set by the government, including the PNS for Organic Agriculture; Good Animal Husbandry Practices; Pork 
Cuts; and Slaughtering Hogs Grading. Regulations are also in place such as the Rules and Regulations on 
Hygienic Handling of Newly Slaughtered Meat in Meat Markets; Guidelines on Good Hygienic Slaughtering 
Practices of LRMEs; Rules and Regulations on Humane Handling in the Slaughter of Animals for Food; and 
the Meat Inspection Code of the Philippines.
Level of Postharvest Loss, SPS Conditions and Risks
African Swine Flu. – ASF is a devastating and highly contagious hemorrhagic viral disease of domestic and 
wild pigs of all ages. Mortality can be as high as 100%, and there is currently no vaccine or any form of 
treatment. The Bureau of Animal Industry (BAI) has formulated the ASF Contingency Plan of 2019 to 
prevent and counter the spread of ASF. The Plan spells out protocols for risk analysis, preventive 
strategies, early warning, and control and eradication, among others. Survey results have shown that 
affected farms can lose up to 70% of their hogs due to the disease.
Compliance to GAHP. – While the survey results showed that many are aware of GAHP in production, 
trading, and processing, many are not practicing them. Regular inspections by LGU Veterinary Offices are 
needed to ensure biosecurity measures are in place in the backyard farms, as well as ensuring that they 
adopt GAHP. According to the KII in Tanauan, more than 50% of livestock growers in the area are now 
GAHP certified. They are targeting a 75% milestone with the DA Repopulation Program. Before the end of 
2021, they target to repopulate all farms, with 75% following GAHP. 
Movement of animals and the threat of ASF. – To ensure disease-free animals, the Provincial LGU 
conducts the following activities: accreditation and certification of farms in close coordination with BAI; 
weekly monitoring of farms, with BAI issuing certification on ASF/disease free status of farms; issuance of 
32
veterinary clearance and veterinary health certificates as well as shipping permits for animal transactions 
going out of the province; and issuance of trader’s pass and temporary veterinary license to transport 
carriers. At the local level, Bantay ASF sa Barangay program is being implemented. The Barangay Animal 
Health Workers conduct disinfection and monitoring of biosecurity measures of the farms in their 
jurisdiction. Checkpoints are set up in entry/exit points, supported by disinfection systems.
Discrepancies in veterinary clearances, certificates and passes. – Cases of false documentations and forged 
signatures are reported in check points. These are reported to BAI and the National Veterinary Quarantine 
Services to validate the certificates. Confiscated products are returned to their originating locations. 
Contamination in slaughtered meat. – The NMIS regularly inspects meat brought to NMIS accredited 
slaughterhouses. They are sometimes accompanied by LGUs, where random checks for the presence of 
E. coli and salmonella on meat are done before they are released. Another potential source of 
contamination are the LRMEs regulated by LGUs which are visited thrice a year. Filipino consumers also 
prefer “warm” or freshly slaughtered meat. However, meat should be consumed 8-10 hours after 
slaughtering when all the blood has been drained from the meat.
Transport and storage of meat products. – The ITCPH points out the need for cold chain facilities to be 
managed by cooperatives, as many of the hog raisers are members of cooperatives. With the “rebooting” 
of the swine industry after the ASF, the government is planning to relocate slaughterhouses from the 
National Capital Region to Central and Southern Luzon, thus transporting carcasses instead of live animals. 
According to ITCPH Head and concurrent DA National Livestock Program Lead, DA is looking at Batangas 
to be a “showcase of something vibrant and new farm to table concept.” The concept will follow a contract 
growing model wherein a group of farmers with an aggregated pig population of 600 in an all-in all-out 
operation and complete with bio-secure facilities will have their pigs slaughtered and processed in AAA
slaughterhouses and meat cutting facilities before being brought to Metro Manila.
SPS and food safety issues related to the adoption of GAHP. – The survey inquired on the level of farmer 
awareness, current adoption, and willingness to adopt specific GAHP requirement. Results show that 
there is a high level of awareness on these specific GAHP, and in some cases, farmers are not even aware 
that they are already practicing these, particularly the use of probiotics, water quality monitoring, and 
animal handling (Hogs Appendix Table 3). For those who are not adopting, however, there is a low level 
of willingness to adopt, most notably on waste management with Environmental Compliance Certificate
permit and food assurance system, among others. The same trend is also observed for traders (Hogs 
Appendix Table 4).
The probability of hog farmers adopting ASF management, biosecurity measures and GAHP certification 
was determined using probit regression (Hogs Appendix Tables 5, 6 and 7). Results show that 
independent growers or those without contractual arrangements and those raising hogs with improved 
breed are more likely to adopt ASF management practices. For biosecurity measures, the variables likely
to affect adoption are age, education, and improved breed. Finally, adoption of GAHP practices is affected 
by level of inventory of hogs, particularly weanlings to finish; distance of farm to the markets and access 
to agriculture insurance and sex, with males more likely to adopt than females. 
Organizational Performance and Risk Management Capacity of Host Government Agency Partners and 
Communities (related to food safety; agency partners)
DA Regional Office 4. – The DA Regional Office conducts assessments, inspection, and monitoring for food 
safety to ensure farms practice GAHP. The DA RegionalOffice has a Regulatory Division which takes charge 
of farm registrations, quality control and inspection of food safety with Quality Control inspectors who 
conduct monitoring and surveillance of animal diseases and early warning. It also has an Integrated 
33
Laboratory Division and a Feed Lab that tests feed samples submitted to monitor adulteration of feeds. 
The DA National Strategic Plan on Food Safety has been drafted but not yet cascaded to the local level. 
There is low level of funding for the DA Regional Office, hence no separate budget for food safety 
implementation and the activities are lumped along with the other programs, projects, and activities. 
Several staff have undergone trainings on PNS, and these learnings have been cascaded to LGUs, but there 
has been no training specific for food safety. The DA staff are also deputized by BAI to perform regulatory 
function as Regional Inspectors, Provincial Animal Feed and Biological Control Officer, Regional Welfare 
Officer and GAP inspectors. These Inspectors are trained on GAP, GAHP, antimicrobial resistance (AMR) 
practices and inspects commercial and non-commercial manufacturers to ensure Good Animal Feeding 
Program, inspect livestock facilities and establishments, monitor compliance to standards and 
environmental laws.
National Meat Inspection Service – NMIS is the government regulatory agency in-charge of inspection and 
regulation of “AA” or “AAA” slaughterhouses and meat cutting plants to ensure proper implementation 
of ante-mortem and post-mortem inspections, and the hygiene and sanitation. The NMIS evaluates the 
slaughterhouses in terms of adequacy of facilities and operational procedures to ensure that the meat 
processed therein are eligible for sale in the target markets depending on the classification of the 
slaughterhouse or dressing facilities. Non-accredited slaughterhouses are regulated by the Local 
Government Units through their city or municipality veterinary offices. The NMIS operates at the regional 
level. In Region 4A where Batangas is located, there are 88 meat establishments being handled by 38 
NMIS meat inspectors. Twelve of these are meat establishments are found in Batangas.
Provincial and City/Municipal LGU. – The Provincial Veterinary Office (PVO) of Batangas has four divisions 
dealing with animal health services, animal regulatory services, animal planning and production, and 
administration. It implements regulatory functions for animals, meat and LRMEs; accreditation and 
certification of farms; and issuance of veterinary health certificates, shipping permits, trader’s pass, 
veterinary clearance. The Office also conducts orientation on animal welfare for transportation carriers 
and meat inspectors as part of BAI requirements for permits of transport carriers, including treatment of 
animals going into slaughterhouses.
The PVO implements the Bantay ASF, an information dissemination on ASF in all LGUs. This is done 
through conduct of monthly meat handling seminars in all municipal LGUs; issuance of guidelines on 
BalikBaboy program in support of DA’s repopulation program, together with the city and municipal LGUs; 
implementation of the DA Repopulation Program which includes orientation on ASF, clustering all 
backyard farms and testing them, depopulate if needed and repopulate. The commercial farms conduct 
their own testing, depopulation, and repopulation.
The city and municipal veterinary offices also implement ordinances on meat inspections and animal 
treatment. The Tanauan City LGU implements the repopulation of pigs covering their jurisdiction, Lipa 
City, and other sentinel areas. The City conducts trainings on GAHP and GMP for farmers and producers. 
In 2020 it formulated the LGU Plan on Food Safety which includes trainings on meat inspections, 
distribution of plastic chopping boards and scabbards for meat dealers. The LGU has four meat inspectors 
and ensures that their personnel are trained on GMP for slaughterhouses.
International Training Center on Pig Husbandry. – The ITCPH is the focal agency for all swine training and 
extension. It is the training arm for swine of the DA-Agricultural Training Institute. It offers both short￾and long-term courses on pig farming. It promotes improved techniques and technologies in farm 
biosecurity, feeds and feeding management, artificial insemination, management of breeders and 
fatteners and other services. ITCPH conducts two trainings on pig husbandry every year for extension 
workers and other government entities using a standard module. One of its programs is the AI sa Barangay 
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which involves two boars and equipment (microscope, spermiodensimeter, refrigerator, etc.) per site, 
serving as a techno-demo farm and venue for training of farmers. The program is being implemented in 
70-80 barangays in the country. Each barangay is required to have a 200-sow level.
Potential Collaboration Among Value Chain Actors
Based on the value chain analysis, the potential areas of collaboration among the value chain actors may 
revolve around 1) the repopulation program of government which will open opportunities to introduce 
technologies and practices related to SPS and food safety; 2) Pork-in-a box scheme, which will lessen
transportation of live animals and facilitate preparations for the eventual relocation of slaughterhouses 
outside of the National Capitol Region; 3) capability building of regulatory agencies, LGU and stakeholders; 
and 4) formulation of a Food Safety Plan. Actionable and more detailed recommendations are provided 
in the recommendations.
3.2.4 Broiler Chicken in Batangas
The chicken value chain in the province of Batangas is made up of four major nodes: input suppliers, 
producers, traders and processors, and consumers (Figure 6).
Figure 6. Broiler value chain in Batangas
Input Suppliers. – The broiler supply chain starts with input suppliers to broiler farms. These are the feed 
mills and breeder farms which supply feeds and day-old chicks (DOCs) to broiler producers. Producers 
revealed that 91% of them use 45-days (Cobbs) type of chicks, 3% use 30-35 days maturing chicks, and 
the rest use the chicks supplied by their contractors (Chicken Appendix Table 1). Majority (82%) source 
their chicks from registered hatcheries, 3% use chicks from their own farms/hatcheries, 7% from poultry 
or veterinary stores, and 4% from agents. and 4% use the chicks provided to them by the integrators 
whom they have contract growing arrangements with, such as Bounty Chicken, Magnolia, San Miguel, 
Integra, and YCP.
Feed constitutes 65 to 80% of the production cost while the DOCs account for 20 to 25%. Some broiler 
farms use commercial feed, but most of the big commercial broiler farmers/producers have their own 
feed mills or have their feed mixed by feed millers through toll mixing arrangements. An IT company also 
provides forecasting services to dressing plants that helps them program its operations.
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Producers. – Most broiler producers in Batangas province are commercial raisers, where about 90% are 
classified as non-smallholder producers. Some of them are independent producers, while many are 
contract growers of either big companies or traders. About 83% of producers sell live chickens, while the 
rest undertake primary processing (dressing) (Chicken Appendix Table 2). Producers sell their live 
chickens directly to consumers (33%), processors (25%), public markets (13%), and traders (8%), and the 
remaining are under contract with integrators (21%). Producers sell dressed chicken to public markets 
(85%) and processors (15%). In this node of the chain, the stall owners and processors do the dressing of 
the chicken within their own facilities.
Traders and Processors. – Traders and processorstake care of the post-production operation of the broiler 
supply chain. Traders are either agents or animal haulers (viajeros) that bring chickens to dressing plants, 
take the dressed chickens and pass them to the retailers in various public markets of Batangas and 
neighboring provinces before reaching their target consumers. Processing operations involve primary 
processing such as dressing of chickens, cutting, and packaging; as well as secondary processing such as 
marinating or adding of other ingredients or preservatives. From the survey, data show that 83% of traders 
sell the chicken in dressed form while 17% of traders bring live chicken to stall owners in public markets 
(Chicken Appendix Table 3).
Level of Postharvest Loss, SPS Conditions and Risks
Supply of DOCs. – The problem on the supply of pork because of the ASF outbreak in the Philippines 
resulted in a shift in demand for poultry meat. The increase in demand for chicken meat led to 
corresponding increase in broiler production. Consequently, the demand for DOCs increased and the cost 
went up by 250%, from PhP20 to as much as PhP50 per chick. 
The survey revealed several SPS issues on chicks brought to the farm such as crippled chicks (39%), 
mortality (26%), diarrhea (17%), and other forms of sickness (13%). To address these, the practices of 
producers include culling (47%), use of antibiotics (26%), isolation (15%), and cleaning/showering (10%) 
(Chicken Appendix Table 4).
Diseases in production. – In the course of broiler production, the main risks are sickness, particularly 
cough/cold as reported by 67% of respondents, risk of avian flu (17%), and feed adulteration (12%). Floods 
and typhoons (30%) and earthquakes (9%) were also reported. Other important risks identified were the 
Taal Volcano eruption, increase in the prices of inputs (particularly the chick), output price stability, and 
government support (Chicken Appendix Table 5).
Use of growth prominent in chicken. According to a study in Batangas by Pabuayon et al (2017) contract 
growers follow the medications and health programs which usually include antibiotic supplementation in 
water and the inclusion of growth promotant (AGP in feeds) for fast growth and early harvest of broilers. 
Small-scale raisers who buy mixed feed could also avail of feeds with AGPs. Although the PNS for 
Veterinary Drug Residues in Food: Maximum Residue Limits (MRLs) has been issued, government 
regulatory agencies have limited capacity to monitor and test samples in sufficient sampling quantities to 
ensure safety of local meat products.
Lack of modern facilities for postharvest processing. – Majority of smallholder processors still use 
traditional methods of dressing chickens such as scalding, use of knives and tweezers; packing in plastic 
bags without vacuum sealing; use of styro boxes and ice for storage; and transporting live animals by 
binding their feet and hanging them in tricycles and jeepneys.
Lack of accredited dressing facilities for independent commercial growers. – Most if not all AAA dressing 
plants in Batangas have exclusive contracts with big integrator companies. Independent commercial 
growers and smallholder players find their way to LRMEs where food safety standards are not always 
36
followed and monitored. Based on survey results, many producers and traders do traditional methods of
dressing using their own facilities. 
Lack of cold storage facilities. – Most of the time, the blast and storage freezers in the dressing plants are 
being operated beyond its capacity, hence the desired freezing condition is not usually met.
Other food safety issues. – KIIs surfaced a number of issues, including 1) the difficulty of broiler producers 
in complying with GAHP certification due to the strict provisions such as the discharge permit; 2) organic 
methods being more expensive than conventional methods; 3) standards are not mandatory; 4) need to 
clearly define the definitions and application of food safety law relative to size of farms; 5) no subsidy and 
incentives for GAHP certified farms; 6) real inventory of livestock and poultry farms, as the real numbers 
are not reported by raisers; not all raisers are registered and this has implications in monitoring of 
diseases; 7) inadequate resources or regulatory agencies, particularly lack of mobility for monitoring and 
the lack of training on food safety; 8) political favor, where repeat offenders are friends/relatives of local 
executives who get away with their offenses; 9) lack of cold chain facilities such as refrigerated vans(small 
producers have small storage facilities for slaughtered and fabricated meats); and 10) political support for 
food safety implementation where priorities change with changes in leadership.
Based on the survey, the major risk factors reported by producers are diseases especially cough and colds 
(67%), natural calamities such as volcanic eruption (40%) and typhoon/floods (30%), feed adulteration 
(12%), avian flu (17%) and other factors such as increase in prices of inputs (20%), lack of government 
support (20%) and price instability (20%).
SPS and food safety issues related to adoption of GAHP. – When asked about level of awareness and 
practices of GAHP in general, only around 30% of respondents said they are aware and are practicing this. 
However, when asked about the technologies or individual GAHP practices, it turned out that there is a 
high level of awareness and adoption, particularly for feeding standards and technologies, food safety 
assurance systems including feed quality control, food defense systems and use of antibiotics, water 
management, disease management program, hygiene and sanitation and biosecurity measures in general. 
Lower awareness and adoption are for those pertaining to use of pre and probiotics, animal genetics and 
breed selection, avian flu management (no reported cases), availability of operations manual, use of 
vehicle dip, shower, and downtime and personal protective equipment, as well as the use of tunnel 
ventilation in poultry houses. Willingness to adopt for those who are not currently adopting the GAHP 
component technology or practice is high, except for tunnel vent where only about 50% of expressed 
willingness (Chicken Appendix Table 6).
For traders, they are aware of the practice of recording with 68% practicing this. Traders also practice 
proper handling of animals and sanitation of crates, but only about 18% use BAI accredited transportation 
facilities (Chicken Appendix Table 7).
The probability of broiler growers adopting avian flu management, biosecurity measures and GAHP 
certification was determined using probit regression (Chicken Appendix Tables 8, 9, and 10). The factors 
affecting probability of producers adopting avian flu management practices are household monthly 
income, distance to market, access to extension services, access to insurance and having traders as their 
major markets. The likelihood of adopting biosecurity measures is affected by years in school, monthly 
household income and access to credit, while adoption of GAHP is likely to affected by years in chicken 
production, and access to insurance.
37
Organizational Performance and Risk Management Capacity of Host Government Agency Partners and 
Communities (related to food safety; agency partners)
DA Regional Office 4. – The structure for organizational performance and risk management capacities for 
broiler under DA Regional Office 4 is similar to that described for hogs. The DA Regional Office conducts 
assessments, inspection, and monitoring for food safety to ensure that the broiler farms practice GAHP. 
Its Regulatory Division also takes charge of the broiler farm registrations, quality control and food safety 
through its Quality Control Inspectors who conduct monitoring and surveillance of diseases and early 
warning, including avian flu. The same Integrated Laboratory Division and Feed Lab test feed samples. 
As mentioned in the discussion under hogs, the DA has no specific plan that implements the Food Safety 
Act, as their National Strategic Plan for Food Safety has not been cascaded to the LGUs so that it can be 
harmonized. Also, the DA staff have undergone trainings on PNS for broiler chicken, and this has been 
shared with the LGU counterparts. Deputation by BAI to perform regulatory functions is also the same for 
chicken: Regional Inspectors, Provincial Animal Feed and Biological Control Officer, Regional Welfare 
Officer and GAP inspectors are trained on GAP, GAHP and AMR. These trainings help in the 
implementation of their functions to inspect manufacturers to ensure good animal feeding program, 
inspect facilities and establishments, and monitor compliance to standards and environmental laws.
National Meat Inspection Service. – The mandate of NMIS also covers poultry dressing plants (PDPs). As 
such, the Agency performs the same functions for PDPs as they do for slaughterhouses and meat cutting 
plants. There are two PDPs in Batangas that are under the jurisdiction of NMIS. As mentioned, the 38 
Meat Inspectors of NMIS in Region 4A monitor 88 meat establishments all over Region 4A.
Provincial, City, and Municipal LGUs. – The structure and functions of the Office of the Veterinary Office 
of Batangas encompass livestock and poultry. Thus, the details mention under the section on hogs are 
also applicable for broilers. The Divisions on animal heath, regulatory, and animal planning and production 
also in charge of the chicken. As mentioned, the PVO implements regulatory functions for animals, meat 
and LRMEs, accredits and certifies farms, issues veterinary health certificates, shipping permits, trade 
passes, veterinary clearances, monitors compliance of LRMEs to food safety standards and collects meat 
samples for testing. The LGUs are also mandated under the Food Safety Act to issue business permits to 
operators who comply with the Sanitation Code, GMP and HACCP.
Potential Collaboration Among Value Chain Actors
Based on the value chain analysis, the potential areas of collaboration among the value chain actors may 
revolve around 1) provision of facilities and equipment for chicken primary processing, including model
LRMEs and cold storage facilities; 2) capability building of regulatory agencies, LGU and stakeholders; and 
3) formulation of a Food Safety Plan. Actionable and more detailed recommendations are provided in the 
recommendations.
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3.2.5 Milkfish in Pangasinan
Key players in the value chain are the input suppliers, producers, traders, and processors (Figure 7).
Figure 7. Supply chain of milkfish in Luzon
Input suppliers. – Inputs are fry sourced from local hatcheries and dealers of imported fry from Indonesia. 
The brood stock and fry hatchery of the BFAR provide the seed stock to existing hatcheries in Sual, Infanta,
and Lingayen which then supply fry to nursery and grow-out operators in the province. Most producers 
(78%) use fry for stocking. They use locally bred fry (81.5%), while 18 % used the imported fry sold by fry 
dealers in the area. One producer used both locally bred and imported fry (Milkfish Appendix Table 1).
Two major feed millers (San Miguel and Cargill) are the sources of aquafeeds. Fertilizers such as urea and 
14-14-14, lime and organic pesticides like teeseed powder are purchased from local agrochemical stores. 
BFAR provides aquaculture extension and training services. Most producers surveyed (88%) have not 
attended BFAR-sponsored productivity improvement trainings. 68% have no access to extension services 
and 96% have not attended training related to food safety. One forth has access to formal credit (Milkfish 
Appendix Table 2).
Producers. – Grow-out pond and cage operators are the main producers of the milkfish value chain. 
Twenty five percent practice extensive stocking density (1,500-3000 fingerlings/ha) in their fishpond 
operation, 37% follow semi-intensive (3,001-10,000/ha), and 35% use intensive (10,001-20,000/ha) 
stocking. Extensive stocking is dependent on endogenously/naturally supplied nutrients like plankton and 
algae produced through fertilization, but this is practiced by only 14%. Majority (68%) provide both natural 
and external feeds while 11% use external feeds alone. In semi-intensive stocking, fish production is 
dependent on the endogenously supplied nutrients and externally supplied fish feed. This is practiced by 
47% while 24% provide external feeds alone. Intensive stocking is completely dependent on externally 
supplied feeds but only 11% use this practice; majority (78%) use both natural and external feeds, and the 
rest rely on naturally supplied nutrients. 
Fry are reared in nursery ponds until they reach the fingerling size. Ponds are acclimatized for an hour, 
usually in early morning to ensure that the temperature and salinity of water is suited to the fry. Manual 
observation, checking of temperature and taste test of water quality are likewise conducted (Milkfish 
Appendix Table 3). Stocking density is 25-30 pieces/square meter of fry and survival rate is 63% for 
39
imported fry, 67% for locally produced fry, and 69% for fry gathered from the wild (Milkfish Appendix
Table 4). Industry experts like Mr. Wilfredo Yap of the PCAARRD Fisheries Experts’ Pool and Santeh 
Foundation and Dr. AisaSalayo of SEAFDEC Aquaculture Department calculate the mortality at 40-50%. 
Fry mortality can be attributed to the water quality in the pond and the condition of the fry upon arrival. 
Twenty-four percent reported that they handle their stocks delicately to avoid mortality while 29% opt to 
just replace their stock. Duration of rearing from fry to fingerling is 30 days or until the stock reach the 
desired size of 30-40 grams. While the stocks are in the nursery, rearing ponds are being prepared 
simultaneously. Twenty percent of operators prefer to buy fingerlings from a local nursery as it is more 
convenient. The stock is reared for about 5 months until it reaches its full marketable size. Full grown 
milkfish are classified as small (250 grams and below), medium (300 grams) and large (500 grams and 
above).
There was low awareness of GAqP except for pond preparation (96%), soil conditioning (74%) and natural 
food production (72%) (Milkfish Appendix Table 5). More than one third (37%) are aware that water 
quality should be regularly monitored to ensure suitability and safety. The survey indicated that 62% of 
producers have problem on poor water quality (Milkfish Appendix Table 6). For a few (4.1%), water 
quality is monitored through observation. No one indicated using an equipment or quick test kit to 
measure water quality. Other mitigating measures to improve water quality is by draining and changing 
the water (34%), proper water management and sanitation (16%) as it is a common practice among the 
caretakers in the province to relieve themselves right in the fish farms since they believe that human 
waste contributes to the production and growth of planktons and lablab much like organic fertilizer; 
proper water management (9.8%); checking the dikes and screen to ensure that suitable water free from 
waste enter the farm (9.2%) and use of water pumps (11%). Others do nothing (2.3%) while an equal 
proportion (2.3%) pre harvest their stock to avoid losses; There are those who wait for the rainfall (2.9%) 
or just let the water in to improve the water quality (8.1%). 
On water management, 57% are aware of the use of pumps to improve water quality. One fifth (20%) are 
aware of the importance of aeration and 38% of them practice it. Most of them are not aware nor do they 
practice effluent discharge. Only 11% discharged ammonia build up in the pond, 30% are aware of the 
importance of dissolved oxygen which at a lower level could result to fish kill, 23.7 % are aware of 
monitoring water temperature and half of them are practicing it. Presence of predator is reported by 
many (67%). Diseases may also affect the stock (Milkfish Appendix Table 7). Symptoms like bruises and 
white spots, lack of appetite, and gasping are observed and these can happen not only during grow out 
stage (as reported by 34%) but also during fry to fingerling stage (34%), fingerling stage (30%), and 
fingerling to grow out stage (3%). Deformities were reported by 47%. Overall, the probable cause of 
mortality in milkfish is the quality of water (reported by 40%), climate change (23%), predators like snakes 
and birds (28%), temperature of water (14.3%) and lack of oxygen (12%)(Milkfish Appendix Table 8). 
The likelihood of producers adopting improved practices were statistically tested using probit analyses 
(Milkfish Appendix Table 9). Results of the probit analysis on management of pests and diseases showed 
that producers’ willingness to adopt disease control measures is positively correlated with years in school, 
age of farmers, farm size, proximity of farms to brackish ponds, and if farms are using imported fries 
(Milkfish Appendix Table 10).
Overall, grow out pond operators incurred operational expenses per cycle of P83,095/ha, cage operator, 
P29,955/cage and nursery operator, P95, 630/ha. Feeds are the biggest expenditure item, 47% for pond 
operation, 70% for cage culture and 52% in nursery operation (Milkfish Appendix Table 11). Production 
per cycle is 2,005.63 kg/ha in grow out pond of which 92% are sold, 1,154.06 kg in cage operation of which 
88% are sold and 70,752 pieces of fingerlings. Net income is biggest in nursery operation, P222,754/ha. 
Pond and cage operation generated an income of P86,596/ha and P68,484.49/cage, respectively.
40
Buyers. – Milkfish trading involved the brokers, traders, retailers, and processors. Grow out operators sold 
the produce either to brokers/consignaciones, traders (wholesalers) or directly to consumer. Processors 
source their milkfish requirement from any of these buyers. As observed during the survey in Dagupan 
which is the major trading center in the province, the produce is delivered to the trading post by boats 
coming from Binmaley while those from other towns are delivered by trucks. Binmaley, Bolinao, Lingayen, 
Alaminos and Dagupan and the main supply areas of milkfish which are brought to their respective public 
markets (BAS, 2014). Supplies from Bani and Sual were sold in Alaminos and Lingayen, respectively. 
Outside destinations were the provinces of La Union, Benguet, Ilocos Norte, Abra, Isabela, Zambales, 
Tarlac and Metro Manila. 
The grow out operators usually entrust their produce to brokers who in turn pass on the fish to the traders 
on credit. Brokers get 4-5% commission from producers upon payment by traders. Brokers in the province 
handle about 75% of the total milkfish fresh harvest, rest by traders who directly purchase from 
producers. 
Processing Facilities. – There are over 100 establishments engaged in milkfish processing in the province, 
five are exporters to Asian countries, the United States, EU, and Middle East as halal foods. Anjo Farms in 
San Fabian and Korea-Philippines Seafood Processing Complex in Dagupan are the biggest in the area. 
Anjo Farms Incorporated primarily deals with seafood processing, shrimp paste production, and milkfish 
processing. The product lines are shown in (Milkfish Annex 1).
Accredited ice plants in the province are registered with DA. Among these are Pangasinan Cold Storage 
and Pamar Foods Inc. Ice Plant & Cold Storage both located in Calasiao, Urdaneta City Ice Plant and Cold 
Storage, Pangasinan Ice plant And Cold Storage Inc. the Kenwood Cold Storage/San Vicente Dressing Plant 
in Alaminos, and Kabayan Ice plant & cold storage in Labrador. 
While cold storage facilities are present for use by producer, results of the probit analysis show that age, 
ethnicity, household size, grow out operation and sea cage operation, along with origin of the fry may 
significantly influence the adoption of cold storage services in the locality. The younger the producer and 
the smaller the household size, the more likely is the adoption of cold storage services. Ethnicity, pond 
operation and fry origin have positive influence on adoption (Milkfish Appendix Table 12).
Level of Postharvest Loss, SPS Conditions and Risks
Fresh milkfish delivered at the trading post are iced in metal containers. These are quickly sorted by size 
and immediately passed on to traders who then have their purchase hauled to their delivery trucks to 
minimize losses. The trading post bustles with activities as brokers, sorters, traders, porters with carts, 
and sellers/suppliers of crushed ice are making their respective transactions. The post is operated round 
the clock but not all brokers operate at the same time. This is to stabilize the price and not to compete 
with each other. Cleanliness is observed in the trading post especially during this pandemic but there may 
be sanitation issues with presence of laborers who sleep in their carts within the vicinity as well as business 
establishments operating near the post. 
The 33 traders are also processors of deboned and marinated milkfish. Not all are practicing GAqP. Pre￾chilling is reported by 64%, icing by 45%, use of refrigerated van by 58%, labeling by 70%, and use of rigid 
wooden containers when shipping in commercial cargo trucks by 70% (Milkfish Appendix Table 13). They
sell frozen prime cuts prepared under controlled conditions. They use cold storage facilities. No one 
however can afford canning and bottling operation. All sourced ice from ice plants in their area, practice 
grading and sorting, minimize contact in dirty spaces and prevent physical damage of their purchase 
milkfish.
41
Transportation is the major marketing cost incurred by traders which is estimated at 15 to 20 percent of 
total marketing cost. The study conducted by German and Catabay in Dagupan indicates that volume of 
ice, volume of milkfish and type of water in the container being used by brokers and the timing/selling 
period are important considerations in trading and marketing of milkfish.
Organizational Performance and Risk Management Capacity of Host Government Agency Partners and 
Communities (related to food safety; agency partners)
BFAR Region 1 and the local government units at the provincial, municipal, and city levels have the 
capacity to implement food safety regulations in their respective localities. There are personnel/officers 
responsible for mandated tasks, operating on limited budget (BFAR Region 1) but regularly allocated 
(LGUs). 
BFAR Region 1. – Two units are involved: 1) the Fisheries Management Regulatory and Enforcement 
Division which takes care of enforcement, patrolling, surveillance of commercial fishing vessels, and 
coastal resources management and 2) the Fisheries Inspection and Quarantine Unit which focuses on food 
safety, fish inspection, quarantine and certification. 
It implements the registration of aqua farms/hatcheries/nurseries and the monitoring of antibiotic 
residues and conduct analysis as part of production-related activities. In implementing food safety 
regulations during processing, the regional office conducts monitoring and inspection of processing 
plants, fishing boats, and cold storage facilities. For marketing, it monitors and ensures compliance to food 
safety requirements including those of importing countries.
Food safety monitoring during primary production stages is implemented by Fish Health Officers trained 
on the registration system and how to process registration of aqua farms, inspection of aqua feed millers 
on use of banned antibiotics and aflatoxins. Monitoring of major aquaculture farms on harmful algal 
bloom are undertaken by Fish Health Officers who maintain the laboratory and conduct sampling, 
testing/analysis on red tide at the BFARs Marine Biotoxin Laboratory. Inspection of processing 
plants/establishments, fishing boats, and cold storage facilities are conducted by Fish Inspectors trained 
on food safety regulations such as GAqP, HACCP as well as on the requirements of importing countries 
such as Halal food international certification, and the BFAR Region 1 designated Certifying Officers certify 
fish products sold in local markets and assigned Quarantine Officers to monitor and inspect in border 
posts (airports, seaports) to ensure no entry or no introduction of adulterated food/related products that 
may affect consumer health and safety.
A Risk Management Plan is in place and a functioning alert system for the introduction of outside species 
as part of bio-security measures on food safety. There is also a stricter processing of documentation 
requirements from importing countries, e.g. health certification, product analysis, sampling, etc. before 
imported products (live, processed, frozen) are brought in, risk assessments are also conducted before 
new species are introduced into the country. There is also a BFAR program on legislated hatcheries to 
produce milkfish and not depend on Indonesia fry. In BFAR’s list of registered farms, there are very few 
importers, only from Binmaley and Lingayen.
The Provincial Agriculture Office (PAgO)-Fishery Division is adequately manned by 19 staff. They were 
trained by BFAR Region 1 on good aquaculture practices GAQP, technology and management practices in 
bangus culture including salient features of the Food Safety Act. The Fisheries and Aquatic Resources 
Management Councils, with a functional core team at the provincial level and active municipal councils, 
support the over-all work of the PAgO and MAO. The PAgO budget for 2021 for fishery/food production 
is Php 6 Million and another Php 2.5 Million is reserved for coastal resources management including sea 
fishing and bangus culture. The target beneficiaries are the marginalized fishpond operators.
42
Potential Collaboration Among Value Chain Actors
With inadequate supply of fry, potential collaboration among value chain players may revolve around fry 
hatchery establishment and operation by the private sector with BFAR providing the seedstock. It has 
already established a program to support existing hatcheries by increasing its brood stock inventories and 
initiates dispersal programs where eggs and/or yolkfish can be distributed in small hatchery operations. 
Public investment is needed to establish integrated brood stock and hatcheries in major milkfish 
production areas to ensure continuous supply of eggs and larvae at early stages of milkfish value chain. 
This will guarantee continuous supply of fry to other subsequent enterprises such as hatchery, nursery 
and grow out production.
3.2.6 Coco Sugar in Misamis Oriental and Davao de Sur
The key players in the coconut sap sugar industry are sap collectors (tappers), processors such as 
cooperatives and farmers associations, private companies who both process and market the product, and 
traders (consolidators/integrators, retailers, and exporters). Tappers are usually members of 
cooperatives, associations, or employed by private companies. The recent entry of another product 
derived from coconut sap syrup has changed the landscape of the industry. This particular product is coco 
aminos, a food seasoning similar to soy sauce. As such, four value chains have been identified in Misamis 
Oriental and Davao del Sur as presented in the map below (Figure 8).
Figure 8. Value chain map of coco sugar
Input Suppliers Producers Traders /Processors Consumers
Tappers Cooperative/Association
(coconut sap sugar)
Retailers/Distributor
Consolidators/Integratorss
Local Consumers
Foreign- Based Consolidator
Exporter Foreign Consumers
Tappers Local Consumers
Tappers
Cooperative/Association
(Coconut sap sugar) Retailer/Distributor
Cooperative/Association
Cocosugar Cocosyrup
Processor-Exporter –
(Private Firm)
Cocoaminos
Foreign Market
Retailer/Distributor
Local Consumers
Tappers Producer/Processor/Exporter (Private Firm)
(Cocosugar and coco aminos)
Foreign Market
Fresh sap or cooked 
into syrup
Fresh sap or cooked 
into syrup
Fresh sap or cooked 
into syrup
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The first value chain is derived from the supply chain map prepared by Philippine Coconut Authority (PCA). 
It involves tappers who bring the sap to the processing plant of cooperatives/associations. The processed 
product (coco sugar) is brought to consolidators/integrators who then sell it to retailers and foreign-based 
consolidators. Retailers sell the product to local consumers. 
The second value chain involves cooperatives/associations, e.g., Linabu Agrarian Multi-Purpose 
Cooperative (LAMPCO), whose members do the tapping and sell the sap to the coop/association for 
processing into coco sugar. The produce is directly exported to other countries and also sold in part to 
local retailers. 
In the third value chain, the cooperative/association produces both coco syrup and coco sugar. Coco syrup 
is sold to a private firm, in particular the Spythe Global Enterprises, which processes the syrup into coco 
aminos for export. Coco sugar is for local consumption sold through the retailers. Spythe Global, 
established in 2006, used to be the major coco sugar producer in Mindanao. It decided to shift to coco 
aminos three years ago due to competition and increasing number of coco sugar producers in Misamis 
Oriental. Today, many tappers in the study areas have also been selling sap through the intermediaries
which process and export coco aminos. Tappers find it convenient to sell sap for coco amino production 
as it requires an 8 to 12-hour interval for sap collection compared to 4 hours required in coco sugar 
production. 
The fourth value chain involves tappers and a private firm (e.g., Lao Integrated Farm, Inc.) which is a 
central processing hub in Davao del Sur for coco sugar, coco syrup, coco aminos and other coconut by￾products like coco honey, coco teriyaki, and chocolate with coco sugar sweeteners. The firm exports these 
products to the United States and Germany.
The tappers collect toddy with the help of laborers who clean the trees to be tapped and carefully bending 
the unopened inflorescence to be tapped. Average daily sap collection is 29 liters. Almost half of the 
tappers (49%) cook the sap to syrup in improvised ovens in their home. The cooked syrup is then sold to 
their cooperative/association for processing into coco sugar. For fresh sap, processors require the sap to 
have a pH not lower than 5. In the processing of syrup, a temperature at least more than the boiling point 
at 120 degrees centigrade is required. This will be undergoing heat evaporation until the syrup has a Total 
Soluble Solid of 75-79 degrees Brix to have a longer shelf life prior to processing into coconut sap sugar. 
In all these processes, more than half (53%) of the surveyed respondents in Misamis Oriental and Davao 
del Sur, are not aware of the practices and certification requirements for coco sugar set by Philippine 
National Standards. About 38% are adopting the standards and 24% are organic certified. About 80% are 
willing to adopt the standards, 42% are into sap production, 43% are producing syrup and the rest are 
producing both. Production of syrup per day among them is 14 liters on the average.
Level of Postharvest Loss, SPS Conditions and Risks
All tappers, having been trained by the PCA, comply to sanitation requirement on the use of clean knives, 
use of opaque plastic as container of collected sap, and collection of sap every 4-5 hours for coco sugar 
production. Rejection however is still experienced by 16%. Average rejection rate is 8.7% due to weather 
condition which delayed the delivery of sap to processing area (27%), two producers reported 
fermentation, one each reported contamination, yellowish color, and oversupply of sap in the processing 
center. Half of the tappers are aware that the sap should not be acidic yet only 15% of them use the pH 
meter. While they would like to use a pH meter, it is not available in their area. They rely on odor and 
color to in determining sap acidity. 
Boiling the sap into syrup is practiced by 60% of tappers. The scam is removed to avoid formation of dark 
residues as reported by 81% yet about 19% of them do not. They say it adds to the weight of the syrup 
44
and eventually to the finished product, though it actually darkens the product. The syrup is delivered to 
the cooperative/association’s processing area and this is where tappers may experience rejection of their 
syrup. Tappers use improvised oven with no thermometer since cooking is done their kitchen. They say 
they already know and are familiar with the consistency of syrup when this is already cooked. Tappers 
who are members of the cooperative/ association in the community also sold sap for coco aminos no 
matter what the acidity is. Intermediaries of the processing firm can purchase any volume no matter the 
quality of the sap, e.g., higher acidity, which in a way may incentivize the tappers to focus more on 
collection of sap for coco aminos rather for coco sugar. 
Despite the preference of tappers to practice heat evaporation using their own method, most of them 
(91%) practice proper waste disposal. About 80% are aware of the need to sanitize the sap delivery room 
if there is one in the processing site. Their usual practice is to deliver the sap or syrup in the cooking area 
of the cooperative or association or directly to the cooking bin for immediate processing. Almost all 
sanitize their sap containers. On the other hand, the 17 traders surveyed mostly comply to GMP and 
HACCP systems wherein 14 of them sanitized the sap delivery room and all practiced the proper waste 
disposal and sanitation of containers. 
Probit analysis on adoption of PNS show that producers are more likely to adopt PNS regardless of what 
they produce, either sap or syrup. They are less likely to adopt if the condition of the road is poor. They 
are also less likely to adopt if the product goes to the trader. They are more likely to adopt if the product 
directly goes to the market. If they have access to extension, credit, and insurance, the more likely that 
they will adopt the standards (Coco sugar Appendix Table 1).
All producers/tappers do not perform grading and classification of their product (Coco sugar Appendix 
Table 2). Majority (66%) do not comply with standard on packaging as almost all (99%) use plastic bags. 
Less than five percent rejection is reported by 98% and this is caused by overcooking, fermentation, 
oversupply, and contamination. Producers (94%) deliver their product to the buyers and the mode of 
payment is mostly in cash (60%). Among traders, packaging standards are compiled in the handling and 
storing the packaging materials (16 traders), use of prescribed food grades (17) and the prescribed 
condition of the packaging areas (14). For handling and storage, 13 adhere to the appropriate storage 
facility for finished products and 14 on transport of product from processing plant to market. 
The road from the farm to the buyer/market is fairly good and distance is about 9 km hence these are not 
much of a constraint. Most of the producers are challenged by the low yield of sap and fermentation (Coco 
sugar Appendix Table 3). Limited number of dwarf coconut trees is reported by 22% and the high risk in 
collecting sap due to tall trees is reported by one third of them. Generally, the producers do not have 
suggestions on mitigating measures on the problem low sap yield. A few suggested applying organic 
fertilizer (Coco sugar Appendix Table 4). The producers have less concern on mitigating risk factors like 
high labor cost and price competitiveness. Almost all (99%) who need assistance and support on coco
sugar business would suggest the provision of working capital while 77% need technical assistance (Coco 
sugar Appendix Table 5).
There are 12 reported coco sugar processors in Misamis Oriental and five in Davao del Sur. Spythe Global 
used to be the biggest processor/trader but shifted to coco amino production three years ago. One of the 
owners, Ms. LA Adalia cited the increasing number of coco sugar producers in the province as its main 
reason for the shift. Instead of competing with them, Spythe Global has found another product that can 
be manufactured out of coco sap. It was able to get a big contract in the United States to supply coco 
aminos produced in its Cagayan de Oro manufacturing plant. These are shipped to its warehouse in 
Valenzuela, Bulacan and from there, exported to the U.S. 
45
Spythe Global maintains its own coconut farm and at the same time partners with other plantation 
owners/tappers who are willing to supply them with quality sap. With the change in priority of Spythe 
Global, tappers who used to supply coco sap for coco sugar production to the company shifted to 
supplying the raw material for coco aminos which is rather convenient to them. This change has been 
observed in Medina and Balingasag. Whether for coco sugar or syrup production, the price received by 
the tappers for coco sap remains the same at P28/gallon. Ms. Adalia says it used to be P27 before the 
pandemic.
Despite this, however, all other coco sugar processors in Misamis Oriental continue producing coco sugar. 
In fact, the LAMPCO, a producer and exporter of coco sugar, is renewing its organic certification of their 
coco sugar processing enterprise with EcoCert with a financial support of Php 206 thousand from the 
provincial government. The Department of Trade and Industry (DTI) also requires LAMPCO to remove the 
logo of its original certifier in its labels and packaging materials but this too entails some cost. LAMPCO 
hopes to resume exporting as soon as it gets a new organic certification and the logo of the certifying 
body. On the other hand, Tup-on Integrated Farmers Association in Medina is involved in both coco sugar 
and coco syrup processing. Its members are grouped into two - the coco sap collectors and the coco 
sugar/syrup processing group. They were trained by PCA in 2018 on coco syrup processing. There are 80 
coco sap collectors in Medina attached to Tup-on Integrated of which 30 comes from six barangays in 
Medina. They supply coco sap syrup to Spythe Global and sell coco sugar to local traders.
In Davao del Sur, Lao Integrated Farms Inc. (LIFI), the biggest processor and trader/exporter in the region, 
similarly produce coco aminos but its major product is still coco sugar. The farm has a pool of tappers who 
regularly collect the coco sap which are processed to coco aminos and coco sugar. 
In terms of marketing according to PCA, retailers of coco sugar comprise a small percentage of traders in 
coco sugar marketing considering that the bulk of the produce is targeted for export. There are local 
brands in the country at a retail price of P300/kg. According to PCA, retailers purchased unbranded coco 
sugar from consolidators for P200/kg. They provide their own branding and labels and do their own 
promotion. With this, product branding and labelling has to level up to be at par to the commercially 
available sweeteners or even highly competitive being a natural and organic coconut-based high value 
product line.
Results of the Probit analysis on adoption of improved packaging show that producers are more like to 
the adopt improved packaging if they are younger, have higher incomes, the road condition is better, and 
have access to insurance. They are less likely to adopt if the distance of their farm area is far from the 
market (Coco sugar Appendix Table 6).
Organizational Performance and Risk Management Capacity of Host Government Agency Partners and 
Communities (related to food safety; agency partners)
PCA and LGUs have strengths and some inadequacies to fully implement the food safety regulations as 
per Food Safety Law of 2013. In general, the inadequacies are in terms of budget and staff (number and 
competency). PCA is Chair of the Philippine National Standards for coco-sugar Technical Working Group 
of the BAFS. Its strengths are in coconut production and technology development; weakness is in trade 
and marketing. It knows the technologies involved in the production/processing in the whole value chain 
and is familiar with the hazard analysis critical control points (HACCP) in processing such as collection of 
sap, collection of syrup, and the actual cooking of sugar. It is already working on the FDA-cited capacity 
gaps and has already come up with the PCA Transformation Roadmap to be firmed up in March 2021 that 
include building the capacity of PCA Trade and Market Development Department, the Product 
Development Division and Quality Laboratory Division in order to ensure quality of coconut-based 
processed foods. 
46
In Davao del Sur, the Office of the Provincial Agriculturist (OPAg) has 3-4 staff involved in organic 
agriculture. Its P15 M budget does not include fund support for coco sugar production but OPAg has a 
designated focal person for coco sugar to join government agencies such as DA/ATI, DTI, PCA in the 
conduct of regular monitoring and plant visits every 2 weeks to the coco sugar processing plant at LIFI. 
OPAg coordinates all field trips and tours at LIFI since it is registered as ATI learning site, DTI agri tourism 
site, and DA organic farms. In Misamis Oriental, the OPAg is composed of 60 staff focused on commodities 
– each person assigned on a commodity, including one Food Technologist trained on food safety (former 
work in mango processing), focused on FDA research on coco water. An OA Program Coordinator with 1 
staff to assist implementation of OA program activities. OPAg convenes quarterly meetings of Organic 
Practitioners Team.
Major risk factors include food adulteration, poor product quality, use of chemicals in coconut farms, as 
well as mislabeling or claims as organic produce. PCA and LGUs act and plan accordingly. On food 
adulteration and poor product quality, deputation of PCA by FDA is planned and targeted for 
implementation in March 2021 so PCA can inspect the plants and monitor compliance. PCA plans to be 
strict in giving license and apply sanctions /penalty for non-compliance. In addition, PCA reported the 
need for a marketing strategy that will highlight the clean processing of coco sugar from the Philippines 
and make it more competitive in the international market. 
For the certification of coco sugar processing, OPAg Misamis Oriental endorses individual processors to 
DA. In Medina, the farmers’ association ensures that no chemicals are used in coconut production areas; 
reject coco sap which are not processed within 4 hours after collection and delivered in coco sugar 
processing plant as they will result to poor quality coco sugar. President of Tup-on Integrated FA (trained 
by PCA) serves as quality control officer in ensuring quality of coco sap and quality of coco sugar produced. 
In Davao del Sur, MAO Bansalan monitors and inspects coconut farms on use of chemicals especially 
during meetings held in areas where coco-sap is collected with specific advice to farmers to not use 
pesticides; however, frequency of monitoring is not regular.
Potential Collaboration Among Value Chain Actors
One successful model of collaboration is that of LIFI and the Office of the MAO of Bansalan, OPAg Davao 
del Sur, DA, ATI, PCA and DTI. During the start-up of LIFI, the MLGU/MAO of Bansalan assisted in 
developing the project proposal and business plan and provided the necessary endorsements to DA 
Region 11 for fund support and technology assistance in the coco sap sugar processing. DA National also 
provided equipment support and the improvement of farm to market roads in Bansalan in coordination 
with the Provincial LGU. LIFI is now the only company engaged in large-scale/commercial processing of 
coco sugar in Bansalan. Other than coco sap sugar, LIFI also has other processed coconut by products e.g.,
coco honey, coco teriyaki, turmeric, chocolate with coco sugar sweeteners. The sweetener used in all LIFI’s 
bakery products is coco sugar. It is duly registered and certified farm by the PLGU/OPAg and DA with 
international certification for export of its coco sugar under the brand name Donnabelle.
There are 12 coco sap collectors (with varying numbers of coconut trees in their farms) supplying to LIFI. 
They are organized into an association and are now in the process of transforming it to Toddy Collectors’ 
Cooperative. LIFI also sources out their coco sap from other municipalities. MAO is not involved in quality 
inspection of coco sap sugar produced but sometimes joins other government agencies in their visit to 
LIFI farms coco sugar processing plant. It continues its promotion of OA in the whole municipality of 
Bansalan to sustain coconut production grown without pesticides, coco sap of which are brought to LIFI 
for processing. MAO provides OA practitioners/farmers with materials, concoctions, vermi casts etc. for 
organic fertilizer production.
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4. Conclusions 
It was established from the data gathered that for the six commodities covered, 98.8 % of potential B￾SAFE beneficiaries have applied at least one improved management practice or technology; 36.5% applied 
improved packaging, 30.2% use improved equipment, 36.4% use improved transportation, and 10.3% use 
improved cold storage. The value of annual sales of farms and firms amounted to USD 4, 178, 159,067, 
which was generated from the sales of 2,564,854 MT of products. It was also found that there are at least 
261 farms/firms/laboratories with GAP, GMP, HACCP, or ISO certification and 16 host government or 
community-derived risk management plans either formally proposed, adopted, implemented, or 
institutionalized (Table 2). The indicators for which baseline values were set at zero are given in Table 2A.
Disaggregating the results by improved management practices and technologies, the study found that 
there are important practices and technologies which are not being applied by a significant proportion of 
potential beneficiaries, hence could be good entry points for B-SAFE:
• Among rice and corn farmers in Bukidnon, only 45% and 38% respectively, are using sustainable 
practices and technologies. Also, there are no rice or corn farmers who have engaged in consolidated 
farming;
• Among hog raisers in Batangas, there is low application (only 3%) of improved practices on 
postharvest handling and storage, especially those with privately owned and operated 
slaughterhouses (low application of sanitation, use of UV lamp for flies, storage freezer, etc.). Carcass 
chillers and blast freezers are not being used. In addition, only 14% are involved in value added 
processing;
• Among broiler growers in Batangas, there is low application (only 46%) of climate adaptation
practices such as natural ventilation, blower, and cooling pads. Only 12% of producers are applying 
good postharvest handling and storage such as sanitation of crates and animal handling facilities and 
only 23% are into value-added processing;
• Among milkfish growers in Pangasinan, the study found that while 64% of grow out operators are 
adopting the recommended stocking densities the accompanying necessary method of feeding is not 
being applied. Moreover, while 77% of milkfish growers are aware of the need to acclimatize the 
fry/fingerling stock, only half of them are practicing it; and
• Among coco sugar producers in Davao and Misamis Oriental, only 3% are practicing improved 
marketing and distribution. This includes better product packaging, labeling and promotion.
On the application of improved packaging, equipment and transportation, the study highlights the 
following:
• Application of improved packaging is very low among producers of rice in Bukidnon (13%), corn in 
Bukidnon (24%), broiler chicken in Batangas (2%) and coco sugar in Davao and Misamis Oriental 
(38%); 
• Only 3% of broiler chicken growers in Batangas, 2% of hog raisers and 25% of hog traders in Batangas 
use improved equipment; and
• Only 8% of traders use dressing machines for broiler chicken in Batangas;
48
The study found very limited number of farms and firms with GAP, GMP, HACCP or ISO certification, 
regardless of commodities. This is not surprising especially for products sold in primary form as the market 
has not yet significantly incentivized compliance to the standards. Compliance to standards is higher 
among processors as products become more differentiated (such as in the case of coco sugar) and for 
large commercial farms such as in the case of most hogs, broiler chicken and milkfish growers. The study 
highlights the following:
• There is only 1 rice farm in Bukidnon with GAP certification. In addition, there is no corn farm in 
Bukidnon which is GAP certified;
• The survey found that most rice and corn farmers apply only certain components of GAP and there 
is really no conscious effort to comply with all the requirements. In most cases, the GAP compliant 
practices being applied by farmers were actually part of their traditional practices which happen to 
be the same practices prescribed under GAP; 
• In hogs in Batangas, the estimated baseline number of farms/firms/laboratories with GAP, GMP, 
HACCP, or ISO certification was 26;
• In broiler chicken in Batangas, 10% of respondents claimed to be GAHP-certified. The proportion of 
respondent-raisers who are aware of GAHP is 32%, and those practicing GAHP but not all its 
components is 30%;
• In milkfish, there were 6 producers with certification for Good Aquaculture Practices (GAqP) and 
three processors with HACCP certification; and 
• There are 62 producers and 31 traders of coco sugar that have standard certifications. 
The baseline situation analysis of the six commodity value chains highlights the following:
• Postharvest losses are high: 7.2%/year for rice from harvest to final sale; 8%/year for corn from 
harvest, shelling, drying and storage and another 2% during milling, storage to final sale; production 
and postproduction losses in hogs are due mainly to ASF and can reach as high as 70%; production 
and postproduction losses in broiler chicken are due mainly to avian diseases such as cough/cold 
and threat of avian flu; and 8.7% in coco sugar particularly due to rejected sap resulting from delayed 
delivery;
• The technical capacity of potential B-SAFE host government partners in addressing the various food 
safety, quality and productivity risks is generally adequate, but support may be needed to augment 
financial capacity, especially in providing trainings, facilities and equipment support to potential 
beneficiaries;
• Potential collaboration should revolve around promoting and capacitating potential beneficiaries to 
comply to the relevant SPS standards; reducing production and post-production losses and ensuring 
the application of more sustainable practices.
5. Recommendations 
Rice and Corn in Bukidnon
1. Facilitate training farmers on GAP and assist them in complying and certifying to the standards. This 
may also necessitate provision of assistance in the conduct of farm area assessment, building farm 
49
storage facilities for fertilizer and chemical inputs and improved farm equipment for threshing and 
drying (to avoid pavement drying), among others, to reduce contamination and postharvest losses.
2. Establish models of consolidated farming to facilitate compliance to standards, greater effectiveness 
in combatting risks of pest infestation (e.g., RBB in rice and FAW in corn), adoption of more 
sustainable practices and realize the benefits of economies of scale. As exploratory steps, B-SAFE may 
examine the potential of building on existing collaborations and models such as the lead firm model 
of collaboration being practiced by the Acosta Rice Mill in Maramag, Bukidnon for rice and the farm 
clustering model being pursued by the ISN for corn in Bukidnon.
3. Support the effort of local government agencies and LGUs in pest monitoring and surveillance against 
RBB in rice and FAW in corn. While there is local technical capacity on this, financial as well asfacilities 
and equipment support are needed.
Hogs and Broiler Chicken in Batangas
1. In hogs, work with LGUs and DA in the repopulation program to rebuild the industry devastated by 
ASF. Collaboration may be in the following: a) work with ITCPH in providing genetic materials for AI 
and semen through its program on AI Sa Barangay where AI training and equipment are provided; b) 
link with LGUs and DA, such as the Tanauan City LGUs in requiring beneficiaries of the repopulation 
program to apply for GHAP certification, or if not possible, to ensure food safety practices in their 
farms. 
2. In hogs, promote model LRMEs with the private sector to showcase good practices. LRMEs play an 
important role in ensuring food safety of meat and meat products, and their number is greater than 
the NMIS accredited facilities. 
3. In hogs, facilitate access to cold storage and transport facilities to cooperatives such as SIDC, 
organizations such as UNIBAT and farmers and traders/retailers. This may be in the form of cold 
storage rooms, large freezers, and refrigerated vans and similar facilities that will allow for the 
transport of pork to Metro Manila and other areas. This is also in preparation for the plan of the DA 
to move slaughterhouses out of the national capital to minimize transport of live animals. 
4. In broiler chicken, facilitate access to appropriate facilities and equipment for primary processing of 
chicken for small hold and independent growers. This could include provision of poultry dressing 
machines and related equipment; vacuum drying equipment; cold storage facilities such as blast 
freezers, chillers, and freezers; refrigerated vehicles; and others. 
5. In broiler chicken, promote model LRMEs with the private sector to cater to producers and traders 
who have limited access to NMIS accredited poultry dressing plants. 
Milkfish in Pangasinan
1. The study noted low access to extension services and training on food safety among the 
traders/processors. A program on provision of these services may be formulated and implemented 
in coordination with BFAR Region 1 and the LGU. Similarly, training program on productivity 
improvement for producers may be packaged and implemented with particular attention to water 
management, effluent discharge, and other food safety concerns. 
2. Provision of assistance to traders and processors in getting BFAD, HACCP and GMP certification as all 
these entail time, effort, and resources. Likewise, assistance in packaging and labeling of 
manufactured products should be provided particularly to small processors in coordination with the 
Department of Trade and Industry.
50
3. Encourage the provision of public and private investment for local hatchery establishment to ensure 
fry supply free of contaminants. BFAR Region 1 has proposed to DA/World Bank 
4. Support organizing community level milkfish processing projects focusing on deboning and 
marinating, packaging, and labeling of the products, and link the projects to major market centers. 
5. Lobby for the expansion of community fish landing terminal in Bani to service fishpond and cage 
culture operator. Freezers/coolers should be provided. These may also serve as hub of brokers and 
traders involved in milkfish marketing. 
6. Coordinate with the Cold Chain Association of the Philippines for the establishment of blast freezing 
facilities in the province.
Coco Sugar in Davao and Misamis Oriental
1. Help in the development of a grading system to encourage farmers to achieve better quality products 
and conduct of capacity building to achieve product quality development and pursue the concept 
that “Food Safety and Quality is the Product Standard”.
2. Spearhead the formulation of an International Product Standard and Trading System for Coco sap 
Sugar in agreement with other member countries of the International Coconut Community (ICC) to 
protect the product position in the global market. 
3. For coco sap tappers, facilitate access to equipment such as pH meters and facilitiest such as common 
service facility for the boiling of coco sap.
Cross-Cutting Recommendations
1. Initiate and support the development of market models that will incentivize farmer’s compliance to 
food safety and quality standards. Especially for products sold in primary form, there is still generally 
no premium price for products produced following existing product standards. 
2. Support consumer and producer awareness campaigns of government entities (e.g., FNRI, DA, FDA, 
etc.) and CSOs on the importance of food safety, quality and reduced postharvest losses and wastage 
in the food system.
51
Annexes 
Annex 1. Bibliography 
Catelo, M.A.O, Narrod, C.A., and Tiongco, M.M. (2008). Structural Changes in the Philippine Pig Industry 
and Their Environmental Implications. IFPRI Discussion Paper. Retrieved March 15, 2016 from 
https://books.google.com.ph/books?id=RhIu95FwSuUC&pg=PA13&lpg=PA13&dq=types+of+hog
+operations+catelo+philippines&source=bl&ots=JdmZQCWBOD&sig=gSpDNZ3m-q￾B9BRxVm5abg-4C9o&hl=en&sa=X&ved=0ahUKEwjIwI2J_MHLAhWhnqYKHVU4A￾cQ6AEIIjAB#v=onepage&q=types%20of%20hog%20operations%20catelo%20philippines&f=false
City Government of Batangas. (n.d.). About: General Information. Retrieved from Batangas City: 
https://www.batangascity.gov.ph/web/about-the-city/general-information/introduction
DA Communications Group. (2020, August 31). Home: News. Retrieved from Department of Agriculture: 
https://www.da.gov.ph/batangas-province-receives-p272-5m-worth-of-interventions-to-boost￾agri-sector/
DA Communications Group. (2020, August 30). Home: News. Retrieved from Department of Agriculture: 
https://www.da.gov.ph/phls-1st-govt-owned-triple-aaa-slaughterhouse-soon-to-operate-in￾tanauan-city/
DA Strategic Communications. (2020). Philippine Agriculture Rises to the Challenges of the Times.
Department of Agriculture.
Dela Cruz, R. and G. Calica. (2016). Postharvest Losses in Paddy and Maize in Major Producing Provinces 
in the Philippines. Philippine Center for Postharvets Development and Mechanization. 2016.
Elarmo, J. (2020, November 1). Home: Press Release. Retrieved from Province of Batangas: 
http://www.batangas.gov.ph/portal/pinsala-ni-quinta-sa-livestock-poultry-sa-batangas￾province-umabot-ng-mahigit-%e2%82%b11m/
Macaraig, M. J. (2020, March 3). Home: Press Release. Retrieved from Provincial Government of 
Batangas: http://www.batangas.gov.ph/portal/kampanya-laban-sa-asf-mas-pinaigting-pa-sa￾batangas-province/
National Meat Inspection Service. (2021). Home: Accredited List. Retrieved from National Meat 
Inspection Service: https://nmis.gov.ph/menu-accr-list
National Meat Inspection Services. (n.d.). Retrieved February 26, 2021, from 
https://nmis.gov.ph/images/pdf/accredited_list/Poultry_Dressing_Plant.pdf
Pabuayon, I.M. et. al., 2017. Analysis of S&T-related Institutional Capacity and Readiness to Effectively 
Implement the Philippine Food Safety Act. Terminal Report. UPLB-PCAARRD.
Philippine Statistics Authority. (2021). Backyard Livestock & Poultry Survey (BLPS), Commercial Livestock 
& Poultry Survey (CLPS). Quezon: PSA.
Philippine Statistics Authority. (2021). Swine Situation Report: October to December 2020. Quezon: PSA.
52
Philippine Statistics Authority. (n.d.). Retrieved February 25, 2021, from 
https://openstat.psa.gov.ph/PXWeb/pxweb/en/DB/DB__2E__LP/?tablelist=true&rxid=bdf9d8da
-96f1-4100-ae09-18cb3eaeb313
Philippine Statistics Authority. (n.d.). Retrieved February 26, 2021, from 
https://openstat.psa.gov.ph/PXWeb/pxweb/en/DB/DB__2M__FG/0032M4AFP10.px/chart/char
tViewLine/?rxid=42d56361-16c4-4301-9e96-c388fe7cafc7
Philippine Statistics Authority. (n.d.). Retrieved February 26, 2021, from 
https://openstat.psa.gov.ph/PXWeb/pxweb/en/DB/DB__2M__FG/0032M4AFP11.px/table/table
ViewLayout1/?rxid=42d56361-16c4-4301-9e96-c388fe7cafc7
Simeon, L. M. (2020, September 25). Home: News Clippings. Retrieved from Department of Agriculture: 
https://www.da.gov.ph/wp-content/uploads/2020/12/CLIPPINGS-FOR-SEPTEMBER-25-2020.pdf
 
53
Annex 2. B-SAFE Baseline Indicator Table: Proportions and Means 
Notes: 
1. Proportions/percentage values of estimated number of adopters of improvement management 
practices under column A are calculated relative to total population of value chain actors covering all 
6 commodities (i.e., numerator: value for disaggregate; denominator: population of 6 VCs).
2. Means/average values under column A for volume and value are calculated relative to total estimated 
number of producers and firms adopting improve management practices covering all 6 commodities 
(i.e., numerator: value for disaggregate; denominator: total number of producers and firms adopting 
improve management practices in all 6 VCs).
3. Proportions/percentage values of estimated number of adopters of improved management practices 
under column B are calculated relative to population of value chain actors of respective commodities 
(i.e., numerator: value for disaggregate; denominator: population of respective VCs)
No
.
INDICATOR TITLE
Proportions and Means
Calculated Relative to Either Total 
Population or Adopters of 6 VCs
Calculated Relative to Population 
of Respective VCs
A B
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
SI￾4
Number of individuals in the agriculture system who have 
applied improved management practices or technologies 
with USDA assistance 
Disaggregation by commodity type: 99.51% 99.61% 98.65% 99.51% 99.61% 98.65%
✓ Rice 9.42% 9.42% 9.42% 100.00% 100.00% 100.04%
✓ Corn 43.20% 43.19% 43.32% 99.73% 99.70% 100.01%
✓ Swine 31.56% 31.64% 30.77% 99.72% 100.00% 97.22%
✓ Broiler Chicken 8.40% 8.44% 8.05% 98.51% 98.96% 94.39%
✓ Milkfish 3.54% 3.52% 3.70% 95.80% 95.33% 100.00%
✓ Coco sugar 3.39% 3.39% 3.39% 100.00% 100.00% 100.00%
Disaggregation by Value chain actor type: 99.51% 99.61% 98.65%
✓ Smallholder producers 68.67% 76.30% 0.00%
✓ Non-smallholder producers 20.98% 23.31% 0.00%
✓ People in government 0.00% 0.00% 0.00%
✓ People in private sector firms 9.86% 0.00% 98.65%
✓ People in civil society 0.00% 0.00% 0.00%
✓ Others 0.00% 0.00% 0.00%
Disaggregation by sex: 99.51% 99.61% 98.65%
✓ Male 58.27% 59.22% 49.74%
✓ Female 41.24% 40.38% 48.91%
Disaggregation by age: 99.51% 99.61% 98.65%
✓ 15-29 3.37% 2.92% 7.39%
✓ 30+ 96.14% 96.69% 91.26%
54
No
.
INDICATOR TITLE
Proportions and Means
Calculated Relative to Either Total 
Population or Adopters of 6 VCs
Calculated Relative to Population 
of Respective VCs
A B
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
Disaggregation by Management practice or technology 
type
✓ Crop genetics 39.75% 44.16% 0.00%
✓ Cultural practices 89.30% 99.22% 0.00%
✓ Livestock management 38.71% 40.08% 26.37%
✓ Wild-caught fisheries management 1.19% 1.32% 0.00%
✓ Aquaculture management 3.13% 3.47% 0.00%
✓ Natural resource or ecosystem management 61.03% 67.81% 0.00%
✓ Pest and disease management 83.98% 93.31% 0.00%
✓ Soil-related fertility and conservation 30.15% 33.51% 0.00%
✓ Irrigation 6.42% 7.13% 0.00%
✓ Agriculture water management-non-irrigation 
based 53.91% 59.90% 0.00%
✓ Climate mitigation 75.30% 83.66% 0.00%
✓ Climate adaptation/climate risk management 67.46% 74.96% 0.00%
✓ Marketing and distribution 2.35% 2.49% 1.08%
✓ Post-harvest handling and storage 57.70% 56.42% 69.21%
✓ Value-added processing 8.05% 3.37% 50.15%
✓ Other 0.00% 0.00% 0.00%
CI￾1
Number of individuals using improved packaging, 
equipment, transportation, or cold storage as a result of B￾SAFE investment
Disaggregation by technology type: 
✓ Packaging 16.46% 14.78% 31.52%
✓ Equipment 36.94% 39.06% 17.82%
✓ Transportation 21.25% 18.20% 48.70%
✓ Cold storage 1.43% 1.18% 3.70%
Disaggregation by sex: 48.49% 47.40% 58.29%
✓ Male 26.95% 26.50% 31.05%
✓ Female 21.53% 20.90% 27.24%
SI￾18
Value of annual sales of farms and firms receiving USDA 
assistance
Disaggregation by commodity type: 39,300.89 21,736.12 197,387.79
✓ Rice 1,474.51 645.22 8,938.29 15,656.69 6,850.82 94,941.19
✓ Corn 3,344.46 1,735.63 17,824.33 7,719.84 4,006.23 41,145.22
✓ Swine 17,794.31 8,417.36 102,188.98 56,231.30 26,599.54 322,917.18
✓ Broiler Chicken 9,470.46 5,815.69 42,364.16 111,047.5
7
68,197.15 496,474.31
✓ Milkfish 6,314.56 4,620.92 21,557.71 89,126.71 34,217.38 583,310.66
✓ Coco sugar 902.60 501.30 4,514.33 26,621.17 14,785.47 133,142.50
55
No
.
INDICATOR TITLE
Proportions and Means
Calculated Relative to Either Total 
Population or Adopters of 6 VCs
Calculated Relative to Population 
of Respective VCs
A B
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
Disaggregation by type of producer/firm 39,300.89 21,736.12 197,387.79
✓ Producer-smallholder 9,940.13 9,940.13
✓ Producer-non-smallholder 60,102.63 60,102.63
✓ Firm-microenterprise 192,602.9
7
192,602.97
✓ Firm-small and medium enterprise 238,264.6
5
238,264.65
✓ Firm-large enterprise or corporation.
Disaggregation by sex of producer or proprietor 39,300.89 21,736.12 197,387.79
✓ Male 26,950 16,313 122,691
✓ Female 12,351 5,423 74,697
✓ Mixed 0 0 0
Disaggregation by age: 39,300.89 21,736.12 197,387.79
✓ 15-29 461 250 2,362
✓ 30+ 38,840 21,486 195,026
✓ Mixed 0 0 0
SI￾19
Volume of commodities sold by farms and firms receiving 
USDA assistance
Disaggregation by commodity type: 16.15 8.81 82.25
✓ Rice 1.47 0.97 6.04 15.66 10.27 64.18
✓ Corn 6.40 3.74 30.27 14.76 8.64 69.87
✓ Swine 4.81 1.49 34.66 15.19 4.71 109.53
✓ Broiler Chicken 1.89 1.37 6.62 22.19 16.04 77.53
✓ Milkfish 1.44 1.14 4.17 39.06 30.85 112.92
✓ Coco sugar 0.14 0.10 0.49 4.06 2.92 14.36
Disaggregation by type of producer/firm 16.15 8.81 82.25
✓ Producer-smallholder 6.05 6.05
✓ Producer-non-smallholder 17.83 17.83
✓ Firm-microenterprise 42.40 42.40
✓ Firm-small and medium enterprise 292.30 292.30
✓ Firm-large enterprise or corporation.
Disaggregation by sex of producer or proprietor 16.15 8.81 82.25
✓ Male 10.80 6.11 53.04
✓ Female 5.35 2.70 29.21
✓ Mixed 0.00 0.00 0.00
Disaggregation by age: 16.15 8.81 82.25
✓ 15-29 0.30 0.12 1.99
✓ 30+ 15.85 8.69 80.26
✓ Mixed 0.00 0.00 0.00
56
No
.
INDICATOR TITLE
Proportions and Means
Calculated Relative to Either Total 
Population or Adopters of 6 VCs
Calculated Relative to Population 
of Respective VCs
A B
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
Number of producer/firm in the agriculture system who 
have applied improved management practices or 
technologies (not an official indicator; needed for 
averaging of volume and value data)
Disaggregation by type of producer/firm 99.51% 99.61% 98.65%
✓ Producer-smallholder 68% 76% 0%
✓ Producer-non-smallholder 21% 24% 0%
✓ Firm-microenterprise 8% 0% 82%
✓ Firm-small and medium enterprise 2% 0% 16%
✓ Firm-large enterprise or corporation. 0% 0% 0%
SI￾11
Number of host government or community-derived risk 
management plans formally proposed, adopted, 
implemented or institutionalized with USDA assistance
Disaggregation by type:
✓ Government 14
✓ Community 2
Disaggregation by Phase of development:
✓ Proposed - has started working on or designing 
a risk management strategy in conjunction with 
the community or host government 
2
✓ Adopted - has been officially accepted by the 
stakeholders 1
✓ Implemented - elements of the plan are being 
actively implemented 8
✓ Institutionalized - host government or 
community internalizes the risk management 
plan and take over administration, financing, 
and implementation
5
CI￾2
Number of farms/firms/ laboratories with GAP, GMP, 
HACCP, or ISO certification as a result of USDA 
assistance
Disaggregation by type:
✓ Farm 109 109
✓ Firm 40 40
✓ Laboratory
Type of certification:
✓ GAP 23 23 0
✓ GHAP 1277 1277 0
✓ GAqP 59 59 0
✓ GMP 0 0 0
✓ HACCP 1016 547 469
✓ ISO 0 0 0
 Others (if there other types of certification)
57
No
.
INDICATOR TITLE
Proportions and Means
Calculated Relative to Either Total 
Population or Adopters of 6 VCs
Calculated Relative to Population 
of Respective VCs
A B
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
TOTAL PRODUCE
R
TRADER, 
PROCESSO
R
✓ ORGANIC AGRICULTURE 62 62 0
✓ ECC 78 0 78
✓ NMIS 847 0 847
✓ FDA 101 0 101
58
Annex 3. Selection of Sample Clusters Using Systematic Sampling 
1. Steps using two-stage cluster design with listing operation and systematic sampling of producer 
respondents:
Create a First Stage Cluster Frame (in the study cluster refers to barangay with significant 
production of the subject commodity).
Cluster 
Number
Name of Cluster 
(Barangay)
Location of Cluster 
(GPS coordinate) Municipality Province
1
2
3…
N
1.1. Calculate the number of sample clusters using the following formula:
𝑚 =
𝑇𝑆𝑃𝑃
15
Where: m = Number of sample clusters
TSPP = Total sample size for producers per province
15 = Sample size per cluster
1.1.Calculate the sampling interval using the following formula:
 𝑘 =
𝑀
𝑚
Where: k = Sampling interval
M = Total number of clusters in cluster frame
m = Number of sample clusters 
1.2.To determine the specific clusters to survey, follow the steps below:
1.2.1. Generate the random start:
 
RS = RN X k
 Where: 
RS = Random start
RN = Random number (generate using excel)
 k = Sampling interval
Note: Generate random number using excel function: =rand(). Do not round off the 
number (at least get up to 4 decimal points)
59
1.2.2. Cluster Selection:
First cluster = RN X k = RS
Second cluster = RS + k
Third cluster = RS + 2k
Forth cluster = RS + 3k
…… continue up to the last sample cluster
Example:
Assuming random number = 0.3146 and k = 3.63 therefore RS = 1.14
First cluster to select is cluster number 2
Second cluster to select is 1.14 + 3.63 = 4.77 = cluster number 5
Third cluster is 1.14 + 2(3.63) = 8.69 is cluster number 9
….continue up to the last cluster
Cluster Number Name of Cluster (Barangay) Cluster Sample
1 A
2 B First cluster
3 C
4 D
5 E Second cluster
6 F
7 G
8 H
9 I Third cluster
10 J
…N
1.3.To determine the respondents to sample per cluster, follow the steps below:
1.3.1. Create the beneficiary (i.e. producers) frame. This can be done by asking the names 
and location of producers of the subject commodity in the selected cluster. The 
barangay captain or other barangay officials can probably provide a list or 
information on this.
Name of Producer Sample Cluster Number Municipality
1
2
3…
N
60
1.3.2. Use systematic sampling as follows:
1.3.2.1. Calculate the sampling interval:
𝑘 =
𝑀
𝑚
Where k = sampling interval
M = Total number of producers of the subject commodity 
in the cluster/barangay
m = Total number producers to sample
Note: Round-off k to nearest integer 
4.5.2.1. Generate the random start:
RS = RN X k
Note: RN should be an integer (use excel function: = 
randbetween(1,k)
1.3.2.2. Selecting the survey respondent
Follow procedure 4.4.2, but this time use survey 
respondent instead of cluster.
Example of randomly selecting respondents in a selected cluster (say cluster B) and 
assuming that the cluster has 100 producers of the subject commodity from which 
15 will be randomly selected as survey respondents:
k = 100/15 = 6.67 = 7 (when rounded off)
Calculate random number using excel function: =randbetween(1,7). Suppose the 
random number generated is 4, then:
RS = RN X k = 4 X 7 = 28 (therefore, respondent number 28 will be 
the first sample
RS +k = 28+7 = 35 (respondent number 35 is the second sample)
RS +2k = 28+14 = 42 (respondent number 42 is the third sample)
….continue to last sample
5.0. Systematic Sampling of Traders/Processors
61
5.1. Create the traders/processors sampling frame. This can be created by asking 
producers of the names and locations/contact information of producers and 
processors they know in the province. Note that we are not clustering the 
traders/processors. We just try to identify as exhaustively as possible the names 
of traders and processors at the province level from which samples can be 
drawn.
List of traders/processors (of subject commodity) in the province
5.2. Follow procedures for systematic sampling in 4.5.2. this time at the provincial 
level
ID Number Names of traders/processors Locations Contact Information
1
2
3…
N
62
Annex 4. List of Organizations for Key Informant Interviews 
1. Philippine Coconut Authority
2. Provincial Agriculture Office, Bukidnon
3. Bureau of Fisheries and Aquatic Resources Region 1
4. Office of the Provincial Agriculturist, Davao del Sur
5. Department of Agriculture Field Office 4-A
6. Office of City Veterinarian-Tanauan City, Batangas
7. Municipal Agriculture Office-Bansalan, Davao del Sur
8. Department of Agriculture Field Office 10
9. Office of the Provincial Agriculturist, Misamis Oriental
10. City Agriculture Office-Valencia City, Bukidnon
11. Municipal Agriculture Office-Bani, Pangasinan
12. Batangas Office of the Provincial Veterinarian
13. Municipal Agriculture Office-Medina, Misamis Oriental
14. Provincial Agriculture Office, Pangasinan
15. Philippine Maize Federation, Inc
16. Cold Chain Association of the Philippines
17. United Broilers and Raisers Association
18. International Training Center on Pig Husbandry
63
Annex 5. Survey Questionnaires 
Annex 5.1 Chicken
Production period: October 2019 – September 2020
Interviewer/Enumerator: _________________________ Date of Survey: _______________
Reviewed by: _________________________________
A. RESPONDENT’S LOCATION
1. Province
2. City/Municipality
3. Barangay
4. GPS Coordinate Latitude:
Longitude:
B. PROFILE OF RESPONDENT
1. Name of Respondent
(Last Name, First Name, M.I.)
2. Contact Number and Email
3. Sex [1] Male [2] Female
4. Age as of last birthday
5. Ethnicity
6. Number of years in school/Level
7. No. of years engaged in chicken 
production
8. Household Size
9. Household monthly income (PhP)
10. Non-farm monthly income (PhP)
Source:
11. Membership to Organization [1] Yes [0] No (Proceed to No. 13)
12. Type of organization
[1] Farmer’s Organization
[2] Cooperative
[3] Others, specify: ________________________
13. Farm/Firm Lead’s Name
(Last Name, First Name, M.I.)
14. Farm/Firm Lead’s Sex [1] Male [2] Female
15. Farm/Firm Lead’s VC Actor Type
[1] Smallholder Producers (at least 1 head of bird)
[2] Non-Smallholder Producers (1K broilers; 100 layers & 100 broilers)
[3] People in Private Sector Firm
[4] People in Civil Society
[5] Others, please specify: _________________________________
16. Type of Producer/Firm
[1] Producer-Smallholder (Php 180K and below of sales)
[2] Producer-Non-Smallholder (Php 180K and above of sales)
[3] Firm-Microenterprise (Php 3M and below asset size)
[4] Firm-Small and Medium Enterprise (Php 3M to Php100M asset size)
[5] Firm-Large Enterprise or Corporation (Php 100M and above asset)
17. Arrangement [1] Integrator [2] Contract Grower [3] Not applicable
18. Adopter Unit [1] Individual [2] Organization/Firm [3] Not Applicable
19. Total No. of Poultry Houses 
20. Number of Birds per house
21. Number of cycles from October 2019 –
September 2020
22. Type of breed [1] Native[2] Non-native or Exotic
Capacity building and support services received:
64
23. Have you attended trainings related to 
productivity improvement?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings.
____________________________________________________
24. Have you attended trainings related to 
food safety?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings.
_____________________________________________________
25. Do you have access to extension 
services?
[1] Yes [0] No
26. Do you have access to credit? [1] Yes [0] No (Proceed to No. 28)
27. What are your sources of credit? [1] Formal [2] Informal [3] Both
28. Do you have access to agricultural 
insurance?
[1] Yes [0] No
If yes, please specify the source:
[1] Government programs, please specify: ____________________
[2] Other source: _________________________________________
65
C. TECHNOLOGY ADOPTION
1. Are you aware of the Good Animal Husbandry Practices (GAHP)? [1] Yes [0] No
2. If yes, are you practicing GAHP? [1] Yes [0] No
3. Is your farm certified under GAHP? [1] Yes [0] No
4. After explaining the benefits, are you willing to adopt GAHP? [1] Yes [0] No
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks)
Reason for non￾adoption
If NOT adopting 
what are the 
current farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State your reason
5. Good Animal Husbandry Practices (GAHP) 
5.1. Farm Components
5.1.1. Type of animal 
housing 
(describe and 
rate)
5.1.2. Location 
(describe and 
rate)
5.2. Feed, Veterinary Inputs, and Water
5.2.1. Water quality 
monitoring
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.2.2. Waste 
management 
(w/ ECC)
*Put a remark if 
with ECC or none
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.2.3. Food safety 
assurance, 
please specify:
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
a. Feed quality 
control
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
b. Food defense 
systems (threats 
of sabotage, 
hazards)
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
66
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks)
Reason for non￾adoption
If NOT adopting 
what are the 
current farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State your reason
c. Safe use of 
antibiotics
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
d. Others, specify: [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3 Farm Management
5.2.4. Production 
operation 
manual
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.2.5. Hygiene and 
sanitation 
program (SPS 
program)
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.2.6. Biosecurity 
measures
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
a. use of vehicle 
dip
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
b. shower 
(describe)
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
c. downtime
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
d. use of PPE
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
e. others, specify: [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.2.7. Climate 
Mitigation 
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
67
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks)
Reason for non￾adoption
If NOT adopting 
what are the 
current farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State your reason
a. Use of tunnel 
ventilation
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
b. Other climate 
adaptation 
(specify)
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3. Animal 
genetics/breed 
selection
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
a. Breed/strain of day-old chicks used
b. Source of day-old chicks [1] Registered hatchery [2] Own farm/hatchery
[3] Others, pls. specify_____________________________________________
c. Issues on the quality of day-old chicks
d. SPS issues in bringing day-old chicks to the 
farm
e. How do you address SPS issues?
5.4. Chicken Health Management
5.4.1. Feeding 
standard/ 
technologies
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
a. Use of prebiotics
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
b. Use of 
probiotics
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.2. Disease 
management 
program
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
a. Avian Influenza 
Management
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
68
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks)
Reason for non￾adoption
If NOT adopting 
what are the 
current farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State your reason
b. Vaccination
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
c. Presence of 
Veterinarian
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.3. Animal welfare
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.5. Transportation and Storage
5.5.1. Use of BAI 
accredited 
transport 
vehicles
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.5.2. Appropriate 
use of animal 
crates
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.6. Record-keeping
5.6.1. Production 
Record
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.6.2. Others, please 
specify:
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
6. Postharvest Practices
6.1. Dressing Plant
6.1.1. NMIS 
accreditation
[1] Yes [0] No If yes, what class? [1] Locally Registered Meat Establishment [2] AA [3] AAA
6.1.2. Description of 
dressing plant 
(status of 
ownership, 
operator, etc.)
[1] LGU owned and operated [2] Leased from LGU [3] Privately-owned and operated
6.1.3. Biosecurity 
measures
[1] Yes [0] 
No 
[1] Yes [0] 
No
[1] Yes [0] 
No
69
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks)
Reason for non￾adoption
If NOT adopting 
what are the 
current farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State your reason
a. use of vehicle 
dip
[1] Yes [0] 
No 
[1] Yes [0] 
No
[1] Yes [0] 
No
b. shower
[1] Yes [0] 
No 
[1] Yes [0] 
No [1] Yes [0] 
No
c. use of PPE
[1] Yes [0] 
No 
[1] Yes [0] 
No [1] Yes [0] 
No
d. others (specify) [1] Yes [0] 
No 
[1] Yes [0] 
No
[1] Yes [0] 
No
6.1.4. Sanitation of 
crates
[1] Yes [0] 
No 
[1] Yes [0] 
No [1] Yes [0] 
No
6.1.5. Animal holding 
facilities 
(specify
innovation)
[1] Yes [0] 
No
[1] Yes [0] 
No [1] Yes [0] 
No
6.1.6. Operation 
manual
[1] Yes [0] 
No 
[1] Yes [0] 
No [1] Yes [0] 
No
6.1.7. Hygiene and 
sanitation 
program (SPS 
program), 
SSOP, GMP
[1] Yes [0] 
No
[1] Yes [0] 
No [1] Yes [0] 
No
6.1.8. Quality 
management 
system, HACCP, 
ISO, etc.
[1] Yes [0] 
No
[1] Yes [0] 
No [1] Yes [0] 
No
6.1.9. Water quality 
monitoring
[1] Yes [0] 
No 
[1] Yes [0] 
No [1] Yes [0] 
No
70
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks)
Reason for non￾adoption
If NOT adopting 
what are the 
current farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State your reason
6.1.10. Pest control
[1] Yes [0] 
No 
[1] Yes [0] 
No
[1] Yes [0] 
No
6.1.11. Line dressing 
operation
[1] Yes [0] 
No
[1] Yes [0] 
No [1] Yes [0] 
No
a. Capacity, 
(birds/hour)
b. No. of labor
c. Meat control 
officer/inspector
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
6.1.12. Cold storage 
facilities
[1] Yes [0] 
No 
[1] Yes [0] 
No
[1] Yes [0] 
No
a. Blast freezer
[1] Yes [0] 
No 
[1] Yes [0] 
No
[1] Yes [0] 
No
b. Storage freezer
[1] Yes [0] 
No 
[1] Yes [0] 
No
[1] Yes [0] 
No
6.1.13. Improved 
packaging
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
6.1.14. Improved 
equipment, 
please specify:
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
6.1.15. Carcass 
cutting 
facilities
[1] Yes [0] 
No 
[1] Yes [0] 
No
[1] Yes [0] 
No
Production output [1] Whole carcass [2] Cut-ups 
Room temperature _________°C
6.1.16. Packaging 
system
[1] Yes [0] 
No 
[1] Yes [0] 
No 
[1] Yes [0] 
No 
Type of packaging [1] Vacuum packed [2] Modified atmosphere [3] Skintight [4] No packaging
71
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks)
Reason for non￾adoption
If NOT adopting 
what are the 
current farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State your reason
Packaging system (if applicable) [1] Automated [2] Manual
6.1.17. Improved 
products 
transportation 
facilities, NMIS 
accredited van
[1] Yes [0] 
No 
[1] Yes [0] 
No 
[1] Yes [0] 
No 
NMIS accredited? [1] Yes [0] No
Refrigerated? [1] Yes [0] No
Status of meat [1] Frozen [2] Chilled [3] Warm
7. Marketing System
[1] Yes [0] 
No 
[1] Yes [0] 
No 
[1] Yes [0] 
No 
8. Meat Shop Operation
[1] Yes [0] 
No 
[1] Yes [0] 
No 
[1] Yes [0] 
No 
9. Wet market
[1] Yes [0] 
No 
[1] Yes [0] 
No 
[1] Yes [0] 
No 
 
72
D. FARM PRODUCTION VOLUME AND VALUE (Average)
1. Total No. of Poultry Houses 
2. Number of Birds per house
3. Number of cycles from October 2019 – September 
2020 (per house)
4. Volume of production/cycle (kg)
5. Volume sold (%)
6. Volume consumed (%)
7. Volume wasted (%)
8. No. of birds/cycle
9. Average weight/bird (kg)
10. Farmgate price (P/kg)
11. Value of Sales (if paid in PHP)
12. Input Cost (in PHP) (Cost per bird)
a. Feeds
b. Materials/Biologics
c. Utilities
d. Labor Cost
13. Income/bird (PHP)
14. Feed conversion ratio
E. CHICKEN FARM PERFORMANCE
1. On Scale of 1-10 (10 being the highest) 
rate the performance in terms of 
Productivity
1 2 3 4 5 6 7 8 9 10
2. On Scale of 1-10 (10 being the highest) 
rate the performance in terms of Food 
Safety
1 2 3 4 5 6 7 8 9 10
3. Existing public-private partnership [1] Yes [0] No 
4. Certification to standards (eg. GAHP, 
Animal Welfare, others)
5. Investment in productivity improving 
technologies (PhP)
73
6. Investment in food safety technologies 
(PhP)
F. MARKETING OF PRODUCTS 
1. What are the major products being sold?
[1] Live chicken
[2] Poultry Meat
[3] Others, please identify: __________________________________
2. Major market for the products (identify 
traders/markets where produced are sold)
3. Distance of Farm to Market
4. Farm to Market Road Conditions
[1] Poor – Totally unpaved (earthen, gravel)
[2] Fair – Partially paved (with earthen, gravel and concrete parts)
[3] Good – Totally paved (concrete, asphalt)
G. PROBLEMS ENCOUNTERED
Risk Factors Have you encountered 
these problems?
What are the mitigating measures adopted to address the 
problems?
1. Feed Adulteration [1] Yes [0] No
2. Feed Misbranding [1] Yes [0] No
3. Avian Flu [1] Yes [0] No
4. Other Diseases (Specify) [1] Yes [0] No
5. Earthquake [1] Yes [0] No
6. Landslide [1] Yes [0] No
7. Typhoon and/or Flood [1] Yes [0] No
8. Labor Dispute [1] Yes [0] No
9. Others, please specify:
H. ASSISTANCE NEEDED
Assistance needed: Agencies involved: (Government, private, NGO, etc.)
1. Technical assistance
2. Equipment and machineries
74
3. Financial assistance
4. Market assistance
5. Others, please specify: ________________________________________________________________
75
 
Annex 5.2. Coco Sugar
Production period: October 2019 – September 2020
Interviewer/Enumerator: __________________________ Date of Survey: ____________________
Reviewed by: _________________________________
A. RESPONDENT’S LOCATION
1. Province
2. City/Municipality
3. Barangay
4. GPS Coordinate
Latitude:
Longitude:
B. PROFILE OF RESPONDENT
1. Name of Respondent
(Last Name, First Name, M.I.)
2. Contact Number and Email
3. Sex [1] Male [2] Female
4. Age as of last birthday
5. Ethnicity
6. Number of years in school/Level
7. Number of years engaged in sap/syrup 
production 
8. Household size
9. Household monthly income (PHP)
10. Non-farm monthly income (PHP)
Source
11. Membership to organization [1] Yes [0] No (Proceed to No. 13)
12. Type of organization
[1] Farmer’s Organization
[2] Cooperative [3] Others, specify: ________________________
13. Farm/Firm Lead’s Name
(Last Name, First Name, M.I.)
14. Farm/Firm Lead’s Sex [1] Male [2] Female
76
15. Farm/Firm Lead’s VC Actor Type
[1] Smallholder Producers (Php 180K and below of sales)
[2] Non-Smallholder Producers (Php 180K and above of sales)
[3] People in Private Sector Firm
[4] People in Civil Society
[5] Others, please specify: _______________________________
16. Type of Producer/Firm
[1] Producer (Sap)-Smallholder (Php 180K and below of sales)
[2] Producer (Sap)-Non-Smallholder (Php 180K and above of sales)
[3] Producer (Syrup)-Smallholder (Php 180K and below of sales)
[4] Producer (Syrup)-Non-Smallholder (Php 180K and above of sales)
[5] Firm-Microenterprise (Php 3M and below asset size)
[6] Firm-Small and Medium Enterprise (Php 3M to Php100M asset size)
[7] Firm-Large Enterprise or Corporation (Php 100M and above asset size)
17. Adopter Unit [1] Individual [2] Organization/Firm [3] Not Applicable
18. Actual production capacity from 
September 2019 – October 2020 (%)
Capacity building and support services received:
19. Have you attended trainings related to 
productivity improvement?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings.
_____________________________________________________
20. Have you attended trainings related to 
food safety?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings.
_____________________________________________________
21. Are you adopting voluntary 
sustainability standards?
[1] GAP
[2] Organic Certification,
If yes, what stage of certification? [1] Completed [2] Ongoing
[3] Philippine National Standards
[4] FDA Certification (license to operate)
77
If yes, what stage of certification? [1] Completed [2] Ongoing
[5] Others, please specify: _____________________
22. What are the difficulties in getting 
permits/certification?
23. Do you have access to extension 
services?
[1] Yes [0] No
24. Do you have access to credit? [1] Yes [0] No (Proceed to No. 26)
25. What are your sources of credit? [1] Formal [2] Informal [3] Both
26. Do you have access to agricultural 
insurance?
[1] Yes [0] No
If yes, please specify the source:
[1] Government programs, please specify: ____________________
[2] Other source: _________________________________________
78
C. TECHNOLOGY ADOPTION
10. Are you aware of the Philippine National Standard for Coco Sap Sugar? [1] Yes [0] No
11. If yes, are you practicing PNS for Coco Sap Sugar? [1] Yes [0] No
12. Is your farm certified under Organic Agriculture? [1] Yes [0] No
13. After explaining the benefits, are you willing to adopt the PNS for Coco Sap Sugar? [1] Yes [0] No
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT 
adopting what 
are the current 
farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
I. Philippine National Standards for Coco Sap Sugar
a. Harvesting Techniques
i. Collection of coconut sap [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
i.a. Sanitation of tapping knife [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
i.b. Collection of liquid sap out with 
the use of a plastic vessel
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
i.c. Collection every 5 hours after 
tapping to avoid fermentation
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
i.d. Use of pH meter (not below 6) [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
i.e. What percentage of product 
rejection encountered?
i.f. What are the causes of product 
rejection?
b. Heat Evaporation
i. Boil the collected sap up to 115 
degrees Celsius using a brick￾fabricated oven
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
ii. Removal of scum to avoid the 
formation of dark residues on the 
final product
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
iii. Boiling and continuous stirring until 
syrup form 
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
79
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT 
adopting what 
are the current 
farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
iv. Transfer of syrup to low fire for initial 
granulation 
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
c. Sugar granulation 
i. Natural cooling of thick syrup for 
granulation
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
ii. Manual crushing of sugar granules for 
powder form to break the lumps
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
d. Sieving and drying the coconut sap sugar
i. Sieving of sugar to have a 
uniform particle size to produce 
quality product
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
ii. Putting the sugar granules in a 
food grade stainless tray and let 
dry for 1 hour to lessen the 
moisture content
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
iii. Use of drying facilities (e.g. oven) [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
iv. Use of protective clothing/gear 
by workers (apron, working 
gloves, head caps/hair nets)
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
v. Handwashing facilities (entry and 
exit)
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
vi. Regular cleaning of utensils [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
e. Documentation and record keeping
(e.g. records for schedule of harvest, 
pH, boiling time, etc.)
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
II. Good Manufacturing Practices and HACCP System (Hazard Analysis Critical Control Point)
(This is a Food Safety Management System as required by Codex Alimentarius Commission)
a. Environmental Hygiene 
i. Waste disposal [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
ii. Sanitation in sap delivery room [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
80
Awareness/ 
knowledge of 
the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT 
adopting what 
are the current 
farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
iii. Sanitation of sap containers [1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
b. Packaging 
i. Materials should be handled in a 
sanitary manner and stored in a 
clean, dry place. 
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
ii. Use of prescribed food grade and 
suitable for intended use
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
iii. Packaging activities should be 
done in a separate room under 
conditions that preclude the 
introduction of contamination 
into the product.
[1] Yes [0] 
No
[1] Yes [0] 
No
c. Handling, storage and transport
i. Appropriate storage facility for 
finished product
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
ii. Transport of products from 
processing plant to market
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
81
D. FARM PRODUCTION VOLUME AND VALUE (Average)
15. Products produced [1] Sap [2] Syrup [3] Sugar
16. Average daily sap collection in liters 
17. Number of trees tapped per day
18. Amount of syrup produced per day (liters)
19. Volume of sugar produced per day (kg)
Sap (liters/day) Syrup (liters/week) Sugar (kg/month)
20. Quantity Sold
21. Quantity Wasted
22. Average price received (P/unit)
23. Average number of days per month in operation
24. Average number of months in operation
25. Input Cost Sap (P/liter) Syrup (P/liter) Sugar (P/kg)
e. Materials
f. Utilities
g. Labor Cost
E. COCOSUGAR BUSINESS PERFORMANCE
1. On Scale of 1-10 (10 being the highest) 
rate the performance in terms of 
Productivity
1 2 3 4 5 6 7 8 9 10
2. On Scale of 1-10 (10 being the highest) 
rate the performance in terms of Food 
Safety
1 2 3 4 5 6 7 8 9 10
3. Existing public-private partnership [1] Yes [0] No
4. Compliance to certification (eg. GAP, 
HACCP, Organic, PNS)
5. Investment in productivity improving 
technologies (Php)
6. Investment in food safety technologies 
(Php)
F. MARKETING OF PRODUCT (COCO SAP SUGAR)
1. Do you perform grading and classification? [1] Yes [0] No
2. If yes, what are the grades/classification of 
coco sugar sold?
[1] Light color [2] Slightly brown [3] Brown
[4] Others, please specify ___________________________
82
3. Do you comply to the product packaging 
and labelling requirement of buyer? [1] Yes [0] No
4. What is the usual packaging material used? [1] Paper[2] Plastic[3] Carton
[4] Bottle[5] Sachet
5. Compliance to Philippine National 
Standards 
6. Major market for the products (identify 
traders/markets where
produced are sold)
7. Are there issues on product development, 
branding and labeling? If yes, please 
specify.
8. What percentage of product rejection 
encountered?
9. What are the causes of product rejection?
10. Distance of farm to market road (in 
kilometers)
a. Farm to market road condition
[1] Poor – Totally unpaved (earthen, gravel)
[2] Fair – Partially paved (with earthen, gravel and concrete parts)
[3] Good – Totally paved (concrete, asphalt)
G. PROBLEMS ENCOUNTERED
Risk Factors Have you encountered these 
problems?
What are the mitigating measures adopted to 
address the problems?
1. Low yield of sap from existing coconut 
varieties in the area [1] Yes [0] No
2. Limited number of dwarf coconut trees in 
the area [1] Yes [0] No
3. Limited skilled manpower in collecting sap [1] Yes [0] No
4. High risk in collecting sap due to tall trees [1] Yes [0] No
5. High labor cost [1] Yes [0] No
6. Fermentation problem due to delays in 
collection and contamination [1] Yes [0] No
7. Adulteration due to high cost of labor [1] Yes [0] No
8. Lack of sanitation in storage facilities [1] Yes [0] No
9. Price competitiveness [1] Yes [0] No
83
Follow-up Questions
10. If coco sap is fermented, what other by￾products can be processed?
11. Are these by-products commercially 
viable?
H. ASSISTANCE NEEDED
Assistance needed: Please specify assistance needed Agencies involved: (Government, 
private, NGO, etc.)
1. Technical assistance (e.g. Capacity 
building and technology upgrading)
2. Equipment and machineries
3. Infrastructure and storage facilities
4. Financial assistance (Capital, Loans)
5. Market assistance and linkaging
6. Training on GMP-HACCP
7. Seal of Quality Assurance/Trade 
marking
8. FDA/Organic Certification 
84
Annex 5.3. Corn
Production period: October 2019 – September 2020
Interviewer/Enumerator: _________________________ Date of Survey: _______________
Reviewed by: _________________________________
A. RESPONDENT’S LOCATION
1. Province
2. City/Municipality
3. Barangay
4. GPS Coordinate Latitude:
Longitude:
B. PROFILE OF RESPONDENT
1. Name of Respondent
(Last Name, First Name, M.I.)
2. Contact number and Email
3. Sex (by birth) [1] Male [2] Female
4. Age as of last birthday
5. Ethnicity
6. Number of years in school/ Level
7. Number of years engaged in farming
8. Household size
9. Household monthly income (PHP)
10. Non-farm monthly income (PHP) 
Source
11. Membership to Organization [1] Yes [0] No (Proceed to No. 13)
12. Type of organization
[1] Farmer’s Organization
[2] Cooperative [3] Others, specify: ________________________
13. Farm/Firm Lead’s Name
(Last Name, First Name, M.I.)
14. Farm/Firm Lead’s Sex [1] Male [2] Female
85
15. Farm/Firm Lead’s VC Actor Type
[1] Smallholder Producers (Php 180K and below of sales)
[2] Non-Smallholder Producers (Php 180K and above of sales)
[3] People in Private Sector Firm
[4] People in Civil Society
[5] Others, please specify: _______________________________
16. Type of Producer/Firm
[1] Producer-Smallholder (Php 180K and below of sales)
[2] Producer-Non-Smallholder (Php 180K and above of sales)
[3] Firm-Microenterprise (Php 3M and below asset size)
[4] Firm-Small and Medium Enterprise (Php 3M to Php100M asset)
[5] Firm-Large Enterprise or Corporation (Php 100M and up asset)
17. Adopter Unit [1] Individual [2] Organization/Firm [3] Not Applicable
18. Total No. of Hectares Planted
19. Tenurial status [1] Farm Owner [2] Lease Holder [3] Tenant
20. Type of production system [1] Non-organic [2] Organic
Capacity building and support services received:
21. Have you attended trainings related to 
productivity improvement?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings: 
_______________________________________________
22. Have you attended trainings related to 
food safety?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings: 
_______________________________________________
23. Are you adopting voluntary 
sustainability standards?
[1] GAP [2] Organic [3] Others, please specify: 
 ____________________________
24. Do you have access to extension 
services?
[1] Yes [0] No
25. Do you have access to credit? [1] Yes [0] No (Proceed to No. 27)
86
26. What are your sources of credit? [1] Formal [2] Informal [3] Both
27. Do you have access to agricultural 
insurance?
[1] Yes [0] No
If yes, please specify the source:
[1] Government programs, please specify: ____________________
[2] Other source: _________________________________________
87
C. TECHNOLOGY ADOPTION
1. Are you aware of the Good Agricultural Practices (GAP)? [1] Yes [0] No
2. If yes, are you practicing GAP? [1] Yes [0] No
3. Is your farm certified under GAP? [1] Yes [0] No
4. After explaining GAP, are you willing to adopt GAP? [1] Yes [0] No
Awareness/ 
knowledge of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to adopt 
the technology/ 
practice?
State your 
reason
5. Good Agricultural Practices (GAP)
5.1. Farm Location. Assessment of farm for suitability for agricultural land use. The farmer needs to know the history of the land to determine potential hazards such as 
chemical (heavy metals) and physical (plastic, glass) hazards.
5.1.1. Conduct of farm 
location 
assessment.
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.2. Farm Environment. The production, post-harvest, and storage areas shall be kept clean and organized at all times. Field sanitation shall always be practiced. 
5.2.1. Soil and nutrient 
analysis: 
a. Use of color chart for 
fertilization
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
b. Others (Please specify): [1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.2.2. Farm sanitation
(farm waste mgt and 
sanitation, cleaning of 
sprayers, distance of 
composting and HH wastes 
from water supply)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.2.3. Agri water 
management to check to 
check for possible 
contamination
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.3. Farm Structure and Facility Maintenance. Farm structures and facilities should be appropriately designed for the intended 
purpose and constructed separately from one another to minimize contamination. 
5.3.1. Risk assessment of 
storage/warehouse area 
(contamination from 
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
88
Awareness/ 
knowledge of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to adopt 
the technology/ 
practice?
State your 
reason
chemicals and vehicle 
exhaust; kept dried; proper 
lighting – non-breakable 
lights/with protection)
5.3.2. Signages for all 
facilities (e.g. storage areas 
for chemicals, harvests, 
tools, etc.)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.3.3. Storage/warehouse 
safety practices 
e.g..available facilities for 
handwashing, CR, cleaning 
schedule)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.3.4. Warehouse/storage 
maintenance
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.3.5.
Warehouse/storage hygiene 
and sanitation;
General cleanliness/waste 
mgt; water quality
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.3.6. Storage of 
pesticides and fertilizers 
(designated storage, away 
from house, preferably non￾porous shelves, separate 
liquid/non-liquid, properly 
ventilated, secure)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.3.7. Pest control of 
facility
(birds, rodents – use of traps 
not poison; flying insects, 
etc.)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.3.8. Equipment cleaning 
and maintenance (scheduling 
and recording)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
89
Awareness/ 
knowledge of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to adopt 
the technology/ 
practice?
State your 
reason
5.3.9. Sanitation of sacks 
and containers (appropriate 
and clean – free from 
chemical and microbial 
contaminants
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.3.10. Transport facility 
cleaning and 
maintenance (records)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4. Farming Practices. 
5.4.1. Crop Variety/seed 
selection (source of seeds, 
type of seeds (hybrid, inbred, 
farmer)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.2. Use of pesticides 
and other agrochemicals 
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
a. Use of appropriate 
registered chemicals
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
b. Use of recommended 
rates
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
c. Use of recommended 
frequency of application
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
d. Disposal of containers of 
and expired pesticides 
and other agrochemicals
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.3. Integrated nutrient 
management
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
a. Use of manure [1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
b. Use of compost [1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
c. Use of straw [1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
d. Others (Please 
specify: ____)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.4. Natural Resource 
or Ecosystem Management 
(e.g. SALT, organic farming, 
protection of water 
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
90
Awareness/ 
knowledge of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to adopt 
the technology/ 
practice?
State your 
reason
system, watershed 
management)
5.4.5. Integrated Pest 
Management (e.g. Cultural 
mgt, variety, water mgt., 
attractants, repellants, 
pest monitoring, chemical)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.6. Weed management
(use of herbicide, water 
management)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.7. Water 
management (Protection 
of water quality, filtration 
system)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.8. Soil-Related 
Fertility and Conservation 
(composting, fallow period, 
use of crop rotation, use of 
different/ alternating 
varieties)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.9. Climate Mitigation 
(burning of straw, 
alternate wetting and 
drying, use of chemical 
fertilizer & pesticide, use of 
organic fertilizer, weed 
management)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.10. Climate Adaptation 
(varieties, time of planting, 
transplanting age, others)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.11. Harvesting 
practices (correct maturity, 
use of manual and 
mechanical harvesting)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.12.Shelling [1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
91
Awareness/ 
knowledge of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to adopt 
the technology/ 
practice?
State your 
reason
5.4.13. Selling in cobs to 
processing plant/center
[1] Yes [0] No [1] Yes [0] No
5.4.14. Hauling (farm to 
dryer, proper worker 
attire, clean vehicle)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.15.Drying practices 
(solar, mechanical drying, 
proper moisture content 
(13%-14%)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.16.Hauling (dryer to 
storage, proper worker 
attire, clean vehicle, 
etiquette – smoking, 
spitting)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.17.Piling system 
(Distance from wall, use of 
pallets)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.4.18. Labelling 
(minimum GAP standard; 
variety, date of harvest)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.5. Worker’s health and safety
5.5.1. Worker’s health 
and safety (e.g. proper 
training, use of PPE, below 
18 y/o, protocols when staff 
are sick)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.5.2. Personnel training 
and records
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.6. Farm Management/farm records
5.6.1. Proper 
documentation and record 
keeping. Farm records (all 
practices are recorded, 
financial records)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.6.2. Warehouse/storage 
records (inventory, etc.)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
92
Awareness/ 
knowledge of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to adopt 
the technology/ 
practice?
State your 
reason
5.6.3. Record keeping of 
use of pesticides
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.6.4. Record keeping of 
fertilizer usage
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.6.5. Traceability (where 
harvested, when harvested –
lot numbers, etc.)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.6.6. Product recall 
procedures
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.6.7. Improved 
Packaging
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
5.6.8. Stock maintenance 
and preservation (PNS for 
warehousing – inventory and 
sampling)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] No
 
93
D. FARM PRODUCTION VOLUME AND VALUE
1. Number of production periods from September 2019 to October 2020: ___________
First Cropping: Second Cropping:
Duration Period:
Area planted (ha)
2. Quantity Produced (metric 
tons)
3. Quantity Sold (metric tons)
4. Quantity Consumed (metric 
tons)
5. Quantity wasted (metric 
tons)
6. Price per kg
7. Value of Sales (if paid in 
PHP)
No. of 
MD/MAD/MMD
Cost/Unit 
(P)
Total Cost 
(P)
No. of 
MD/MAD/MMD
Cost/Unit 
(P)
Total 
Cost (P)
1. Land Preparation
2.1. Plowing
2.2. Harrowing
2.3 Furrowing
2. Transplanting/ Planting
3. Fertilization
4. Pesticide Application
5. Water Management/ 
Irrigation
6. Weeding
7. Harvesting
8. Drying
9. Shelling
10. Hauling
11. Storage
12. Others:
MD – Mandays (1 Manday = 8 hrs of work)
MAD – Man-Animal Day (with draft animal e.g. carabao)
MMD – Man-Machine Day (with rental or use of farm machineries e.g. tractor)
94
Amount (Unit) Cost/Unit 
(P)
Total Cost 
(P)
Amount (Unit) Cost/Unit 
(P)
Total 
Cost (P)
1. Seeds
a. Genetic material [1] GMO
[2] Conventional Hybrid 
[3] OPV
[4] Others, specify_______________ 
[1] GMO
[2] Conventional Hybrid 
[3] OPV
[4] Others, specify_______________ 
b. Variety, please specify
c. Source of genetic 
material. Please 
identify supplier in the 
locality.
2. Fertilizers 
3. Chemicals:
a. Pesticides
b. Herbicides
4. Packaging materials: 
please specify:
_______________________
5. Others: (Pls. specify)
_____________________
6. Where do you source your 
inputs? Please, identify 
inputs supplier in the 
locality.
E. CONSOLIDATED FARMING
1. Do you practice consolidated farming? 
(Enumerator to explain consolidated 
farming)
[1] Yes [0] No (If No, go to 3)
2. If Yes, 
a. What type of consolidation?
[1] consolidation at production
[2] consolidation at the marketing level
[3] complete consolidation, from production to marketing
b. Total area under consolidated 
farming(ha)
c. No. of farmers involved in 
consolidated farming
d. Total production (metric tons)
95
e. Who is managing the consolidated 
farm?
3. If consolidated farming will be promoted 
in your area, are you willing to adopt it? [1] Yes (If Yes, go to 4) [0] No, state reason: ______________
4. If yes, are you willing to adopt any of the 
ff:
[1] consolidation at production
[2] consolidation at the marketing level
[3] complete consolidation, from production to marketing
5. Farm area willing to be allocated for 
consolidated farming (ha)
F. MARKETING OF PRODUCTS 
Individual Farm Consolidated Farm
1. What are the major products being sold? (e.g. 
corn grains, corn in cobs)
2. Major market for the products (identify 
traders/markets where produced are sold)
3. Distance of farm to market road
(in kilometers)
a. Farm to market road condition
[1] Poor – Totally unpaved
[2] Fair – Partially paved
[3] Good – Totally paved
[1] Poor – Totally unpaved
[2] Fair – Partially paved
[3] Good – Totally paved
G. CORN FARM PERFORMANCE
1. On Scale of 1-10 (10 being the highest) rate 
the performance in terms of Productivity 1 2 3 4 5 6 7 8 9 10
2. On Scale of 1-10 (10 being the highest) rate 
the performance in terms of Food Safety 1 2 3 4 5 6 7 8 9 10
3. Existing public-private partnership [1] Yes [0] No
4. Certification to standards (eg. GAP, Organic 
Farm, etc.)
5. Investment in productivity improving 
technologies (PhP)
6. Investment in food safety technologies 
(PhP)
H. PROBLEMS ENCOUNTERED
Risk Factors Have you encountered these 
problems?
What are the mitigating measures adopted to address 
the problems?
96
A. Production
1. Chemical contamination (pesticide residue, 
heavy metals) [1] Yes [0] No
2. Drought [1] Yes [0] No
3. Pest infestation (eg. fall armyworm)
a.Extent of infestation [1] Yes [0] No
b.Bureau of Plant Industry approach (likely 
to be the use of buffer farm areas to 
prevent spread of pest)
[1] Yes [0] No
c. Biocontrol solution to fall armyworm [1] Yes [0] No
4. Earthquake [1] Yes [0] No
5. Landslide [1] Yes [0] No
6. Typhoon and/or Flood [1] Yes [0] No
B. Post-harvest
7. Physical contamination (glass, metals, sand, 
stones) [1] Yes [0] No
8. Microbial contamination [1] Yes [0] No
9. Food Adulteration [1] Yes [0] No
10. Milling [1] Yes [0] No
C. Marketing
11. Packaging and Marketing [1] Yes [0] No
12. Food Misbranding [1] Yes [0] No
13. Others, please specify: 
_____________________________
[1] Yes [0] No
I. ASSISTANCE NEEDED
What are the assistance needed? Who are the agencies involved: (Government, private, NGO, etc.)
9. Technical assistance
10. Equipment and machineries
11. Financial assistance
12. Market assistance
97
13. Others, please specify: _________________________________________________________________
98
Annex 5.4. Hogs
Production period: October 2019 – September 2020
Interviewer/Enumerator: __________________________ Date of Survey: _______________
Reviewed by: _________________________________
A. RESPONDENT’S LOCATION
1. Province
2. City/Municipality
3. Barangay
4. GPS Coordinate
Latitude:
Longitude:
B. PROFILE OF RESPONDENT
1. Name of Respondent
(Last Name, First Name, M.I.)
2. Contact Number and Email
3. Sex [1] Male [2] Female
4. Age as of last birthday
5. Ethnicity
6. Number of years in school/Level
7. Number of years in hog farming
8. Household Size
9. Household monthly income (PhP)
10. Non-farm monthly income (PHP)
Source:
11. Membership to Organization [1] Yes [0] No (Proceed to No. 13)
12. Type of organization
[1] Farmer’s Organization
[2] Cooperative
[3] Others, specify: ________________________
13. Farm/Firm Lead’s Name
(Last Name, First Name, M.I.)
14. Farm/Firm Lead’s Sex [1] Male [2] Female
99
15. Farm/Firm Lead’s VC Actor Type
[1] Backyard (Smallholder) Producers
[2] Commercial (Medium to Large-scale) Producers
[3] People in Private Sector Firm
[4] People in Civil Society
[5] Others, please specify ___________________________________
16. Type of Producer/Firm
[1] Producer-Smallholder (Backyard) (1-20 heads of adult; 1-40 heads of young 
animals; 1-9 heads of adult & 1-21 heads of young animals)
[2] Producer-Commercial
[3] Firm-Microenterprise (up to Php3M asset size)
[4] Firm-Small and Medium Enterprise (Php3M to Php100M asset)
[5] Firm-Large Enterprise or Corporation (Php100M and above asset)
17. Arrangement [1] Integrator [2] Contract Grower [3] Not applicable
18. Adopter Unit [1] Individual [2] Organization/Firm [3] Not Applicable
19. Total No. of Houses 
20. Sow level
21. Number of head per house
22. Number of cycles from October 2019 –
September 2020 During period (With ASF): Before period (No ASF):
23. Type of breed [1] Native[2] Non-native or Exotic
24. Type of operation
[1] Farrow to finish [2] Grower to finish[3] Breeder
[4] Others (e.g. piglets)
Capacity building and support services 
received:
25. Have you attended trainings related to 
productivity improvement?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings.
_______________________________________________________
100
26. Have you attended trainings related to 
food safety?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings.
_________________________________________________________
27. Do you have access to extension 
services?
[1] Yes [0] No
28. Do you have access to credit? [1] Yes [0] No (Proceed to No. 30)
29. What are your sources of credit? [1] Formal [2] Informal [3] Both
30. Do you have access to agricultural 
insurance?
[1] Yes [0] No
If yes, please specify the source:
[1] Government programs, please specify: ____________________
[2] Other source: _________________________________________
101
C. TECHNOLOGY ADOPTION
1. Are you aware of the Good Animal Husbandry Practices (GAHP)? [1] Yes [0] No
2. If yes, are you practicing GAHP? [1] Yes [0] No
3. Is your farm certified under GAHP? [1] Yes [0] No
4. After explaining the benefits, are you willing to adopt GAHP? [1] Yes [0] No
Awareness/ 
knowledge of 
the technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
the rating)
Reason for non￾adoption
If NOT adopting what 
are the current 
farmer’s practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
5. Good Animal Husbandry Practices (GAHP)
5.1. Farm Establishment, Location and Facilities
5.1.1. Type of animal 
housing 
(describe and 
rate)
5.1.2. Location 
(describe and 
rate)
5.2. Feeds and Nutrition
5.2.1. Feeding 
standard/ 
technologies
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
c. Use of prebiotics [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
d. Use of probiotics [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.2.2. Food safety 
assurance 
system
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
e. Feed quality 
control [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
Source of feeds [1] Commercial feed millers [2] Cooperatives/association
[3] Own feed mill; mix own feeds (please proceed to section of raw materials)
Swill feeding [1] Yes [0] No
If yes, source of swill feed:
Sources of raw materials (if 
applicable)
102
Awareness/ 
knowledge of 
the technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
the rating)
Reason for non￾adoption
If NOT adopting what 
are the current 
farmer’s practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
a. soybean/soybean meal
b. fish meal
c. corn
d. copra meal
e. wheat/pollard
f. vitamins and minerals 
g. pre-mixes
h. amino acids
i. other additives
j. other ingredients not 
mentioned above:
_______________________________
[1] Local traders [2] Direct import (Country of origin: ____________________)
[1] Local traders [2] Direct import (Country of origin: ____________________)
[1] Local traders [2] Direct import (Country of origin: ____________________)
[1] Local traders [2] Direct import (Country of origin: ____________________)
[1] Local traders [2] Direct import (Country of origin: ____________________)
[1] Local traders [2] Direct import (Country of origin: ____________________)
[1] Local traders [2] Direct import (Country of origin: ____________________)
[1] Local traders [2] Direct import (Country of origin: ____________________)
[1] Local traders [2] Direct import (Country of origin: ____________________)
[1] Local traders [2] Direct import (Country of origin: ____________________)
Do the farm has its own Animal 
Nutritionist?
[1] Yes [2] Yes, but on consultant basis [0]None
f. Food defense 
systems (threats 
of sabotage, 
hazards)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
g. Safe use of 
antibiotics [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
d. Others, specify:
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.3. Improved production techniques 
103
Awareness/ 
knowledge of 
the technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
the rating)
Reason for non￾adoption
If NOT adopting what 
are the current 
farmer’s practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
5.3.1. Animal 
genetics/ breed 
selection
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
a. breed
b. Source of genetic material (e.g. semen, barako or 
gilt)
[1] Registered breeders [2] Own farm [3] LGU
[4] Others, pls. 
specify_____________________________________________
c. Source of piglet [1] Registered breeders [2] Own farm [3] LGU
[4] Others, pls. 
specify_____________________________________________
d. Issues on the quality of piglets
e. SPS issues in bringing piglets to the farm
f. How do you address SPS issues?
5.4. Water for Pig
5.4.1. Water quality 
monitoring
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.4.2. Waste 
management (w/ 
ECC)
*Put a remark if 
with ECC or none
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.5. Farm Management
5.5.1. Production 
operation 
manual [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.5.2. Hygiene and 
sanitation 
program (SPS 
program)
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.5.3. Biosecurity 
measures
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
f. use of vehicle dip [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
104
Awareness/ 
knowledge of 
the technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
the rating)
Reason for non￾adoption
If NOT adopting what 
are the current 
farmer’s practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
g. foot bath (farm 
entrance and all 
buildings) [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
h. shower 
(describe) [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
i. downtime [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
j. use of PPE [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
f. Others, specify: [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.5.4. Climate 
Mitigation [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
c. Use of tunnel 
ventilation [1] Yes [0] No [1] Yes [0] No
[1] Yes [0] 
No
d. Other climate 
adaptation [1] Yes [0] No [1] Yes [0] No
[1] Yes [0] 
No
5.6. Recording
5.6.1. Production 
record [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.7. Animal Health
5.7.1. Disease 
management 
program
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
d. eg. ASF
[1] Implementing strict measures to ensure BAIs’ ASF-free [2] Regular check-up of facilities for infection rate
[3] Multi-level bio-security protocols [4] Others: __________________________________________________
 [ ] farm level _________________________________
 [ ] barangay _________________________________
 [ ] municipality _________________________________
 [ ] province _________________________________
 [ ] region _________________________________
e. Vaccination [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
105
Awareness/ 
knowledge of 
the technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
the rating)
Reason for non￾adoption
If NOT adopting what 
are the current 
farmer’s practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
e. Presence of 
Veterinarian
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.8. Animal Welfare
5.8.1. Proper handling 
and restraining of 
animals
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.8.2. Use of tools to 
minimize stress 
and injury to 
animals
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.9. Animal Transport
5.9.1. Use of BAI 
accredited 
transport 
vehicles
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.9.2. Sanitation of 
vehicles [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
5.9.3. Description of animal transport vehicle and practices:
a. Ventilation [1] Sufficient [2] Not sufficient
b. Rated capacity _________ Heads
c. Average actual load _________ Heads
d. Average travel time _________ Hours Leaving the farm at ______ am/pm. Arrive market/slaughterhouse at ______ 
am/pm
5.9.4. ASF
[1] Implementing strict measures to ensure BAIs’ ASF-free [2] Regular check-up of facilities for infection rate
[3] Multi-level bio-security protocols [4] Others: __________________________________________________
 [ ] farm level _________________________________
 [ ] barangay _________________________________
 [ ] municipality _________________________________
 [ ] province _________________________________
 [ ] region _________________________________
5.9.5. Others, specify: 
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
6. Postharvest Practices (For Integrator only)
6.1. Slaughterhouse
106
Awareness/ 
knowledge of 
the technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
the rating)
Reason for non￾adoption
If NOT adopting what 
are the current 
farmer’s practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
6.1.1. NMIS 
accreditation [1] Yes [0] No If yes, what class? [1] Locally Registered Meat Establishment [2] AA [3] AAA
6.1.2. Description of 
slaughterhouse 
(status of 
ownership, 
operator, etc.)
[1] LGU owned and operated [2] Leased from LGU [3] Privately-owned and operated
6.1.3. Biosecurity 
measures
[1] Yes [0] No [1] Yes [0] No
[1] Yes [0] 
No
e. use of vehicle dip [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
f. shower [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
g. use of PPE [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
h. others, specify: [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
6.1.4. Sanitation of 
facilities [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
6.1.5. Animal holding 
facilities [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
6.1.6. Operation 
manual [1] Yes [0] No [1] Yes [0] No [1] Yes [0]
No
6.1.7. Description of 
slaughtering 
operation
Capacity Heads/Day
Line operation? [1] Yes [0] No
Automation [1] Full [2] Partial [3] None
6.1.8. Hygiene and 
sanitation 
program (SPS 
program), SSOP, 
GMP
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
6.1.9. Quality 
management 
system, HACCP, 
ISO, etc.
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
107
Awareness/ 
knowledge of 
the technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
the rating)
Reason for non￾adoption
If NOT adopting what 
are the current 
farmer’s practice
Willing to 
adopt the 
technology/ 
practice?
State 
your 
reason
6.1.10. Pest control [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
6.1.11. Cold storage 
facilities [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
a. Carcass chiller [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
6.2. Meat cutting 
facilities
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
Uses PNS pork cutting standard? [1] Yes [0] No If No, specify standard used __________________________________
Room temperature ______°C
6.2.1. Meat 
packaging 
system
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
Type of packaging [1] Vacuum packed [2] Modified atmosphere [3] Skintight [4] No packaging
Packaging system (if applicable) [1] Automated [2] Manual
6.2.2. Cold storage 
facilities [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
a. Carcass chiller [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
b. Blast freezer [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
c. Storage 
freezer [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
6.2.3. Meat/carcass 
transport 
vehicles and 
conditions
[1] Yes [0] No [1] Yes [0] No
[1] Yes [0] 
No
NMIS accredited? [1] Yes [0] No
Refrigerated [1] Yes [0] No
Status of meat [1] Frozen [2] Chilled [3] Warm
7. Marketing System
7.1. Meat Shop 
Operation
[1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
7.2. Wet market [1] Yes [0] No [1] Yes [0] No [1] Yes [0] 
No
108
D. FARM PRODUCTION VOLUME AND VALUE (Average for all cycles)
FOR FATTENER
1. Total No. of Hog Houses
2. Number of head per house
3. Sow-level
4. Number of cycles from October 2019 – September 
2020 (per house)
5. No. of hogs/cycle (heads)
6. Average live weight of marketable hogs (kg/head)
7. Farmgate price of hogs (P/kg) (live weight)
8. Value of Sales (if paid in PHP)
9. Value of sales (if paid in USD)
10. Input Cost (in PHP) (Cost per head)
a. Feeds
i. Feed conversion ratio
b. Materials/biologics
c. Utilities
d. Labor Cost
11. Income/hog (PHP) As reported by farmer: As computed:
FOR BREEDER
1. No. of gilt produced
2. No. of boar produced
3. No. of services for Artificial Insemination (AI)
4. Value of gilt sold (P/head)
5. Value of boar sold (P/head)
6. Value of services for AI (P/service)
7. Input Cost (in PHP) (Cost per head)
a. Feeds
b. Materials/biologics
c. Utilities
d. Labor Cost
109
E. HOG FARM PERFORMANCE
1. On Scale of 1-10 (10 being the highest) 
rate the performance in terms of 
Productivity
1 2 3 4 5 6 7 8 9 10
2. On Scale of 1-10 (10 being the highest) 
rate the performance in terms of Food 
Safety
1 2 3 4 5 6 7 8 9 10
3. Existing public-private partnership [1] Yes [0] No
4. Specify certification to standards (eg. 
GAHP, HACCP, Animal Welfare, others)
5. Investment in productivity improving 
technologies (PhP)
6. Investment in food safety technologies 
(PhP)
F. MARKETING OF PRODUCTS 
1. What are the major products being sold?
[1] Live hogs
[2] Pork carcass
[3] Pork meat cuts
[4] Others, please identify:
_______________________________________________
2. Major market for the products (identify 
traders/markets where produced are sold)
3. Distance of Farm to Market
4. Farm to Market Road Conditions
[1] Poor – Totally unpaved (earthen, gravel)
[2] Fair – Partially paved (with earthen, gravel and concrete parts)
[3] Good – Totally paved (concrete,asphalt)
G. PROBLEMS ENCOUNTERED
Risk Factors Have you encountered 
these problems?
What are the mitigating measures adopted to address the 
problems?
1. Feed Adulteration [1] Yes [0] No
2. Feed Misbranding/Mislabeling [1] Yes [0] No
110
3. African Swine Fever [1] Yes [0] No
4. Other Diseases (Specify) [1] Yes [0] No
5. Earthquake [1] Yes [0] No
6. Landslide [1] Yes [0] No
7. Typhoon and/or Flood [1] Yes [0] No
8. Labor Dispute [1] Yes [0] No
Others, please specify: _________________________________________________________________
H. ASSISTANCE NEEDED
Assistance needed: Agencies involved: (Government, private, NGO, etc.)
1. Technical assistance
2. Equipment and machineries
3. Financial assistance
4. Market assistance
5. Others, please specify: ________________________________________________________________
111
Annex 5.5. Milkfish
Production period: October 2019 – September 2020
Interviewer/Enumerator: __________________________ Date of Survey: _______________
Reviewed by: __________________________________
A. RESPONDENT’S LOCATION
1. Province
2. City/Municipality
3. Barangay
4. GPS Coordinate
Latitude:
Longitude:
B. PROFILE OF RESPONDENT
1. Name of Respondent
(Last Name, First Name, M.I.)
2. Contact Number and Email
3. Sex [1] Male [2] Female
4. Age as of last birthday
5. Ethnicity
6. Number of years in school/Level
7. Number of years engaged in milkfish 
farming
8. Household size
9. Household monthly income (PhP)
10. Non-farm monthly income (PhP)
Source:
11. Membership to organization [1] Yes [0] No (Proceed to No. 13)
12. Type of organization
[1] Farmer’s Organization
[2] Cooperative [3] Others, specify: ________________________
13. Farm/Firm Lead’s Name
(Last Name, First Name, M.I.)
14. Farm/Firm Lead’s Sex [1] Male [2] Female
112
15. Farm/Firm Lead’s VC Actor Type
[1] Smallholder Producers (Php 180K and below of sales)
[2] Non-Smallholder Producers (Php 180K and above of sales)
[3] People in Private Sector Firm
[4] People in Civil Society
[5] Others, please specify: _______________________________
16. Type of Producer/Firm
[1] Producer-Smallholder (Php 180K and below of sales)
[2] Producer-Non-Smallholder (Php 180K and above of sales)
[3] Firm-Microenterprise (Php 3M and below asset size)
[4] Firm-Small and Medium Enterprise (Php 3M to Php100M asset)
[5] Firm-Large Enterprise or Corporation (Php 100M and up asset)
17. Adopter Unit [1] Individual [2] Organization/Firm [3] Not Applicable
18. Type of operation 
[1] Fingerling production operation only
[2] Grow-Out Brackish pond operation
[3] Grow-Out Sea cage culture
(material of cage structure used: _________________________)
19. Total Area
Fingerling 
Production 
Only
Grow-out 
Brackish pond
Grow-out 
Sea cage
Grow-Out 
Offshore
Nursery Area ___ sq.m ___ sq.m ____sq.m ____sq.m
Transition Area 
(if applicable) ___ sq.m ___ sq.m ___ sq.m
Total Area ___ sq.m ___ sq.m ___ sq.m ___ sq.m
20. Total Production Capacity
Fingerling Production 
Only
Grow-Out Brackish 
pond 
Grow-Out 
Sea Cage
Nursery Area
Transition 
Pond
Rearing
21. Actual production capacity from 
September 2019 – October 2020 (%)
Capacity building and support services received:
113
22. Have you attended trainings related to 
productivity improvement?
[1] Yes [0] No
If Yes, please identify three (3) trainings and training service providers
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings.
_____________________________________________________
23. Have you attended trainings related to 
food safety?
[1] Yes [0] No
If Yes, please identify three (3) trainings and training service providers
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings.
_____________________________________________________
24. Food safety standards and practices do 
you know? 
[1] Good Aquacultural Practices (GAqPs) [2] HACCP
[3] Others, please specify: ____________
25. Do you have access to extension 
services?
[1] Yes [0] No
26. Do you have access to credit? [1] Yes [0] No (Proceed to No. 28)
27. What are your sources of credit? [1] Formal [2] Informal [3] Both
28. Do you have access to agricultural 
insurance?
[1] Yes [0] No
If yes, please specify the source:
[1] Government programs, please specify: ____________________
[2] Other source: _________________________________________
114
C. TECHNOLOGY ADOPTION
1. What do you know about Good Aquaculture Practices (GAqP)? [1] Yes [0] No
2. Are you practicing GAqP? [1] Yes [0] No
3. If yes, is your farm certified under GAqP? [1] Yes [0] No
4. If you know the benefits of GAqP, are you willing to adopt it? [1] Yes [0] No; Explain your answer.
Awareness 
/knowledge 
of the 
technology/ 
practices
Adopting 
the 
technology/ 
practice?
Level of 
adoption
Rating Scale:
1-5
(With remarks 
on rating)
Reason for 
non-adoption
If NOT adopting 
what are the 
current 
farmer’s 
practice
Willing to 
adopt the 
technology/ 
practice?
State your 
reason why or 
why not 
willing to 
adopt 
technology/
practice
I. Good Aquaculture Practices 
a. Fry/Fingerling conditioning and transport
i. Sources of fries? (Fry is less than 2cm 
in size)
i.a.Type of source [1] Local [2] Imported
i.b. Origin [1] Wild [2] Hatchery-bred
i.c. Frequency of purchase/year
ii. Sources of fingerlings? (4cm in size)
ii.a. Type of source [1] Local [2] Imported
 ii.b. Origin [1] Own Farm [2] Others, specify _________________________
ii.c. Frequency of purchase/year
iii. Appropriate 
Packaging/Transport/materials
[1] Yes [0] 
No
[1] Yes [0] 
No
[1] Yes [0] 
No
iv. Acclimatization process 
(temperature/salinity)
[1] Yes
[0] No
[1] Yes
[0] No
 [1] Yes [0] 
No
b. Nursery management and operations (stocking and caring for fry)
b.1. Pond Nursery
i. Stocking density [1] Extensive (1500-3000/ha) [2] Semi-extensive (3001-10000/ha) [3] Intensive (10001-20000/ha)
[4] Others, specify
ii. Feed Type [1] Lablab/Plankton method [2] Use of formulated diets [3] Others, specify 
_______________________________
iii. Feeding regime/frequency
iv. Nursing Period
115
v. Average Survival Rate (%)
b.2. Cage Nursery
i. Cage net size/No. of Units
ii. Stocking Density [1] Intensive (10-20/m3
) [2] Others, specify _______________________________
iii.Feeding regime/frequency
iv.Feed Type [1] Use of formulated diets [2] Others, specify _______________________________
v.Nursing Period
vi.Average Survival Rate (%)
c. Grow out Operations
c.1.Pond Grow out
i. Pond preparation (cleaning/drying) [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ii. Tilling/Soil conditioning [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iii. Liming (Type and quantity/hectare) [1] Yes [0] No
Type and quantity ___________________________________________
iv. Pest/Predator Control/Eradication 
(e.g. tobacco dust, teaseed)
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v. Flushing [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
vi. Fertilization [1] Organic (chicken manure) [2] Inorganic (specify chemicals used 
_____________________________________)
vi.a. Quantity/hectare
vii. Natural food (lablab) production [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
viii. Water Level [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ix. Water Quality (physicochemical 
parameters)
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
x. Other Inputs (probiotics, rice bran, 
etc)
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xi. Stocking Density [1] Extensive (1500-3000/ha) [2] Semi-extensive (3001-10000/ha) [3] Intensive (10001-20000/ha)
[4] Others, specify
xii. Feeding regime/frequency
xii.a. Feed Type [1] Lablab/Plankton method [2] Use of formulated diets [3] Others, specify _______________________________
xii.b. Feeding Method [1] Hand Feeding [2] Feeding Tray [3] Demand Feeder [4] Automatic Feeder
xiii. Water management (this pertains to 
water exchange procedure)
[1] Yes
[0] No
[1] Yes [0] 
No
 [1] Yes [0] No
116
xiii.a. Tidal [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xiii.b. Use of Pumps [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xiv. Presence of Drainage canals [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xiv.a. Central canal [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xiv.b. Peripheral canals [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xv. Aeration [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xvi. Effluent Discharge
Monitoring/Analysis/Recording
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xv.a. Physicochemical parameters [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xv.a.1. Ammonia buildup [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xv.a.2. Dissolved Oxygen [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xv.a.3 Temperature [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xvii. Presence of predators
Specify_______________
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
xviii. Disease symptoms
Specify: ____________________
xviii.1. At what stage did the 
disease mentioned occur?
[1] Fry to fingerling
[2] Fingerling stage
[3] Grow out stage
[4] Others (specify)
xix. What caused the disease observed? [1] Genetic materials (e.g. SPS issue)
[2] Production and management related
[3] Water quality/management
[4] Feeds (type/quality)
[5] Others, specify ___________________________
xx. Mortalities (%)
xx.1. Fry Stage
xx..2. Fingerling Stage
117
xx.3. Grow out Stage
xxi. Abnormalities (%) 
xxi.1. Stunted growth
xxi.2. Deformities
xxi.3. Others (please specify)
xxii. Survival rate (%)
xxiii. Average weight/size at harvest
c.2. Cage/Pen Culture
i. Cage net size/no. of units
ii. Stocking Density [1] Intensive (10-20/m3
) [2] Others, specify _______________________________
iii. Feeding regime/frequency
iii.a. Feed Type [1] Use of formulated diets [2] Others, specify _______________________________
iii.b. Feeding Method [1] Hand Feeding [2] Feeding Tray [3] Demand Feeder [4] Automatic Feeder
iv. Net management [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iv.a. Change net frequency [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iv.b. Cleaning procedure [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iv.c. Disinfection procedure [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iv.d. Drying procedure [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v. Monitoring [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.a. Physicochemical parameters
v.a.1. Ammonia buildup [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.a.2. Dissolved Oxygen [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.a.3. Temperature [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.b. Check Mooring (frequency) [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.c. Check cage structure (frequency) [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.d. Sorting/Size Increase [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
118
v.e. Presence of predators [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.f. Disease symptoms [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.g. Mortalities (%)
v.g.1. Fry Stage
v.g.2. Fingerling Stage
v.g.3. Grow out Stage
v.h. Abnormalities (%)
v.h.1. Stunted growth
v.h.2. Deformities
v.h.3. Others (please specify)
v.i. Survival rate (%)
v.j. Average weight/size at harvest
v.k. Monitoring of substrates [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.k.1. Eutrophication [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.k.2. Analysis of bottom substrate [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v.l. Application of bioremediation 
procedures
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
d. Grow out management
d.1. Pond Culture
i. Extensive or straight
-run method [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ii. Modular or progression method [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iii. Deep water
-plankton method [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iv. Stock manipulation or multi
-size 
group metho
d
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v. Semi intensive pond culture [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
vi. Polyculture (specify other 
commodity: crab, shrimp, etc.)
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
119
vii. Intensive pond culture [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
viii. Fish farm record keeping [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
d.2. Cage Culture
i. Modular (with stock transfers) [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ii. Straight run [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iii. Stocking Density [1] Extensive (1500-3000/ha) [2] Semi-extensive (3001-10000/ha) [3] Intensive (10001-20000/ha)
iv. Fish farm record keeping [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
II.Good Handling Practices
a. Harvesting of marketable milkfish
a.1. Pond Culture
i. By freshening (“pasulang”) [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ii. By total drainage [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iii. By gill net [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iv. By seining [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v. By stationary fish corral [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
 a.2. Cage Culture
i. Total or partial harvest per cage 
net
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
b. Post-harvest handling of marketable 
milkfish
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
i. Washing with pond water 
(seawater for cage culture stocks)
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ii. Pre-chilling/icing
-On-site (for pond harvest)
-Live fish boat (for cage harvest)
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ii.a. Availability of ice plants within 
the area
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
120
iii. Minimizing contact in dirty 
surfaces
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iii.a. sorting and grading [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iv. Preventing physical damage [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v. Packing in wooden/styro boxes or 
metal container“baňera”
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
vi. Labelling [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Manufacture Date [2] Expiry Date (“Best Before)
vii. Use of rigid wooden container if 
produce is to be shipped through 
commercial cargo truck/vessel
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
viii. Use of refrigerated transport van [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
c. Processing (if applicable)
i. Cleaning/Degutting [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ii. Deboning and marinating [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Fresh [2] Fresh Chilled [3] Smoked [4] Frozen
iii. Smoking (brine/marinated) [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Drum Type [2] Traditional Smokehouse [3] State-of-the-art Smokehouse
iv. Other Processes
Frozen: Whole/Prime cuts 
(belly/back)
Fresh Chilled
Canned
 Sardine style (regular/spicy)
 Salmon style (regular/spicy)
 Spanish style
Bottled
Dried
Brined
Marinated
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
d. Packaging and labelling (if applicable) [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
121
[1] Can [2] Bottle [3] Sachet (Multi-Polyethylene)
e. Improvement of processing (if applicable)
i. Semi and/or full automation system 
for:
-Cleaning/degutting
-Cutting/Slicing/Trimming
-Washing
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ii. Use of automatic timers for critical 
processes (brining, margination, etc.)
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iii. Use of conveyors [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iv. Strict Quality Check (microbiological 
tests for contamination)
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
v. Proper storage facilities (cold 
storage facilities) (if applicable)
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
vi. Others, please specify: 
_______________________________
III.Other Food safety aspects related to marketing and transporting of milkfish (if applicable)
i. Use of cold storage facility [1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
ii. Use of refrigerated van for 
transporting milkfish
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iii. Upgrading of processing areas/plants 
(facilities, machinery and appliances, 
cleaning and sanitation protocols of 
utilities (including personnel) to 
ensure delivery of safe and suitable 
processed milkfish product
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
iv. Upgrading and employment of 
modern processing methods adhering 
to general food safety principles
[1] Yes
[0] No
[1] Yes
[0] No
[1] Yes [0] 
No
122
D. PRODUCTION VOLUME AND VALUE (Average)
1. Total Area (ha)
2. Number of compartments
3. Number of cycles (October 2019-September 2020)
4. Production
Quantity Price (PHP)
a. Small (250g or below)
b. Medium (300g to 500g)
c. Large (501g and above)
d. Others
5. Quantity Sold (%)
a. Small (250g or below)
b. Medium (300g to 500g)
c. Large (501g and above)
d. Others
6. Quantity Consumed (%)
7. Quantity Wasted/Loss (%)
8. Input Cost (in PHP) (Cost per cycle)
e. Feeds
f. Materials
g. Utilities
h. Labor Cost
i. Other inputs
E. FISH FARM PERFORMANCE
On Scale of 1-10 (10 being the highest) rate 
the farm performance in terms of Productivity 1 2 3 4 5 6 7 8 9 10
On Scale of 1-10 (10 being the highest) rate 
the farm performance in terms of Food Safety 1 2 3 4 5 6 7 8 9 10
Existing public-private partnership [1] Yes [0] No
Certification to standards (eg. GAqP/GMP, 
HACCP)
123
Investment in productivity improving 
technologies (PhP)
Investment in food safety technologies
(PhP)
F. MARKETING OF PRODUCT
1. Major market for the products 
(identify traders/markets where 
produced are sold)
2. Distance of Farm to Market (km)
3. Farm to Market Road Conditions
[1] Poor – Totally unpaved (earth, gravel)
[2] Fair – Partially paved (some parts are earth/gravel, some parts are concrete)
[3] Good – Totally paved (concrete, asphalt)
G. PROBLEMS ENCOUNTERED
Risk Factors Have you encountered 
these problems?
What are the mitigating measures adopted to address 
the problems?
1. Poor brackish water quality/water 
quality in sea-cages/water quality in 
off-shore production system
[1] Yes [0] No
2. Low survival rate of fry/fingerlings [1] Yes [0] No
a. Probable cause of mortality
b. Do you have a disease surveillance 
and/or laboratory services for 
diagnosis?
[1] Yes, specify ______________________________
[0] No
c. Stocking density
d. What practices in poly-culture in 
ponds with integration of crustaceans 
and other finfishes are applied?
i. Advantages
ii. Disadvantages
3. Diseases [1] Yes [0] No
a. At what stage did the disease 
mentioned occur?
[1] Fry to fingerling [2] Fingerling stage
[3] Grow out stage [4] Others, specify _____________________
124
b. What caused the disease observed?
[1] Genetic materials (e.g. SPS issue)
[2] Production and management related
[3] Water quality/management
[4] Feeds (type/quality)
[5] Others, specify ________________________________________
4. Natural calamities (typhoon, flood, 
drought) [1] Yes [0] No
5. Predators (snakes, birds, other fishes) [1] Yes [0] No
6. High cost of inputs (e.g., fertilizer, 
supplemental feeds, fry/fingerling) [1] Yes [0] No
7. Adulteration in fry/fingerlings [1] Yes [0] No
8. Seasonal fluctuation in market price [1] Yes [0] No
9. High labor cost [1] Yes [0] No
10. Fish kill [1] Yes [0] No
11. Others, please identify:
H. ASSISTANCE NEEDED
Assistance needed: Agencies involved: (Government, private, NGO, etc.)
1. Technical assistance
2. Equipment and machineries
3. Financial assistance
4. Market assistance
5. Others, please specify: _________________________________________________________________
____________________________________________________________________________________
___________________________________________________________________________________
125
Annex 5.6. Rice
Production period: October 2019 – September 2020
Interviewer/Enumerator: _________________________ Date of Survey: _______________
Reviewed by: _________________________________
A. RESPONDENT’S LOCATION
1. Province
2. City/Municipality
3. Barangay
4. GPS Coordinate Latitude:
Longitude:
B. PROFILE OF RESPONDENT
1. Name of Respondent (Last, First, M.I.)
2. Contact number and Email
3. Sex [1] Male [2] Female
4. Age as of last birthday
5. Ethnicity
6. Number of years in school/Level
7. Number of years engaged in farming
8. Household size
9. Household monthly income (PhP)
10. Non-farm monthly income (PHP) Source
11. Membership to Organization [1] Yes [0] No (Proceed to No. 13)
12. Type of organization
[1] Farmer’s Organization
[2] Cooperative [3] Others, specify: ________________________
13. Farm/Firm Lead’s Name (Last, First, M.I.)
14. Farm/Firm Lead’s Sex [1] Male [2] Female
15. Farm/Firm Lead’s VC Actor Type
[1] Smallholder Producers (Php 180K and below of sales)
[2] Non-Smallholder Producers (Php 180K and above of sales)
[3] People in Private Sector Firm
[4] People in Civil Society
[5] Others, please specify: _______________________________
16. Type of Producer/Firm
[1] Producer-Smallholder (Php 180K and below of sales)
[2] Producer-Non-Smallholder (Php 180K and above of sales)
[3] Firm-Microenterprise (Php 3M and below asset size)
[4] Firm-Small and Medium Enterprise (Php 3M to Php100M asset)
[5] Firm-Large Enterprise or Corporation (Php 100M and up asset)
126
17. Adopter Unit [1] Individual [2] Organization/Firm [3] Not Applicable
18. Total No. of Hectares Planted
19. Tenurial status [1] Farm Owner [2] Lease Holder [3] Tenant
20. Type of farm [1] Irrigated [2] Rainfed
21. Type of production system [1] Non-organic/Conventional [2] Organic
Capacity building and support services received:
22. Have you attended trainings related to 
productivity improvement?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings.
_____________________________________________________
23. Have you attended trainings related to food 
safety?
[1] Yes [0] No
If Yes, please identify three (3) trainings
1. _____________________________________________________
2. _____________________________________________________
3. _____________________________________________________
If No, state reasons for not being able to attend/participate in related trainings: 
________________________________________________
24. Are you adopting voluntary sustainability 
standards?
[1] GAP [2] Organic [3] Others, please specify: 
 ____________________________
25. Do you have access to extension services? [1] Yes [0] No
26. Do you have access to credit? [1] Yes [0] No (Proceed to No. 28)
27. What are your sources of credit? [1] Formal [2] Informal [3] Both
28. Do you have access to agricultural 
insurance?
[1] Yes [0] No
If yes, please specify the source:
[1] Government programs, please specify: ____________________
[2] Other source: _________________________________________
127
C. TECHNOLOGY ADOPTION
1. Are you aware of the Good Agricultural Practices (GAP)? [1] Yes [0] No
2. If yes, are you practicing GAP? [1] Yes [0] No
3. Is your farm certified under GAP? [1] Yes [0] No
4. After explaining GAP, are you willing to adopt GAP? [1] Yes [0] No
Awareness/ 
knowledge 
of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to 
adopt the 
technology/ 
practice?
State your reason 
why or why not 
willing to adopt 
technology/practice
5. Good Agricultural Practices (GAP)
5.1. Farm Location. Assessment of farm for suitability for agricultural land use. The farmer needs to know the history of the land to determine potential hazards such as 
chemical (heavy metals) and physical (plastic, glass) hazards.
5.1.1. Conduct of farm 
location assessment.
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.2. Farm Environment. The production, post-harvest, and storage areas shall be kept clean and organized at all times. Field sanitation shall always be practiced. 
5.2.1. Soil and nutrient 
analysis: 
c. Use of color chart for 
fertilization
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
d. Others (Please specify): [1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.2.2. Farm sanitation
(farm waste mgt and sanitation, 
cleaning of sprayers, distance of 
composting and HH wastes 
from water supply)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.2.3. Agri water 
management to check for
possible contamination
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3. Farm Structure and Facility Maintenance. Farm structures and facilities should be appropriately designed for the intended purpose and constructed separately from 
one another to minimize contamination. 
5.3.1. Risk assessment of 
storage/warehouse area
(contamination from 
chemicals and vehicle 
exhaust; kept dried; proper 
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
128
Awareness/ 
knowledge 
of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to 
adopt the 
technology/ 
practice?
State your reason 
why or why not 
willing to adopt 
technology/practice
lighting – non-breakable 
lights/with protection)
5.3.2. Signages for all 
facilities (e.g. storage areas for 
chemicals, harvests, tools, etc.)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3.3. Storage/warehouse 
safety practices
(e.g. available facilities for 
handwashing, CR, cleaning 
schedule)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3.4. Warehouse/storage 
maintenance
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3.5. Warehouse/storage 
hygiene and sanitation;
General cleanliness/waste mgt; 
water quality
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3.6. Storage of pesticides 
and fertilizers (designated 
storage, away from house, 
preferably non-porous shelves, 
separate liquid/non-liquid, 
properly ventilated, secure)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3.7. Pest control of facility
(birds, rodents – use of traps 
not poison; flying insects, etc.)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3.8. Equipment cleaning 
and maintenance (scheduling 
and recording)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.3.9. Sanitation of sacks 
and containers
(appropriate and clean –
free from chemical and 
microbial contaminants
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
129
Awareness/ 
knowledge 
of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to 
adopt the 
technology/ 
practice?
State your reason 
why or why not 
willing to adopt 
technology/practice
5.3.10. Transport 
facility cleaning and 
maintenance (records)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4. Farming Practices. 
5.4.1. Land preparation
(leveling)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.2. Crop 
Variety/seed selection 
(source of seeds, type of 
seeds (hybrid, inbred, 
farmer)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.3. Seedling 
preparation
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.4. Transplanting [1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.5. Use of pesticides and other 
agrochemicals 
e. Use of appropriate 
registered chemicals
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
f. Use of recommended 
rates
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
g. Use of recommended 
frequency of 
application
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
h. Disposal of containers 
of and expired 
pesticides and other 
agrochemicals
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.6. Integrated nutrient 
management
e. Use of manure [1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
f. Use of compost [1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
130
Awareness/ 
knowledge 
of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to 
adopt the 
technology/ 
practice?
State your reason 
why or why not 
willing to adopt 
technology/practice
g. Use of straw [1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
h. Others (Please 
specify): 
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.7. Natural Resource or 
Ecosystem Management 
(e.g. SALT, organic farming, 
protection of water system, 
watershed management)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.8. Integrated Pest 
Management (e.g. Cultural 
mgt, variety, water mgt., 
attractants, repellants, pest 
monitoring, chemical, rice￾duck system)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.9. Weed management
(use of herbicide, water 
management)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.10. Water management 
(Protection of water quality, 
filtration system)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.11. Soil-Related Fertility 
and Conservation 
(composting, fallow period, 
use of crop rotation, use of 
different/ alternating 
varieties)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.12. Climate Mitigation 
(burning of straw, alternate 
wetting and drying, use of 
chemical fertilizer & 
pesticide, use of organic 
fertilizer, weed management)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.13. Climate Adaptation 
(varieties, time of planting, 
transplanting age, others)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
131
Awareness/ 
knowledge 
of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to 
adopt the 
technology/ 
practice?
State your reason 
why or why not 
willing to adopt 
technology/practice
5.4.14. Harvesting practices 
(correct maturity, use of 
manual and mechanical 
harvesting)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.15. Ratooning [1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.16. Hauling (farm to 
dryer, proper worker attire, 
clean vehicle)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.17. Drying practices 
(solar, mechanical drying, 
proper moisture content 
(14%)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.18. Hauling (dryer to 
storage, proper worker attire, 
clean vehicle, etiquette –
smoking, spitting)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.19. Piling system 
(Distance from wall, use of 
pallets)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.4.20. Labelling (minimum 
GAP standard; variety, date of 
harvest)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.5. Worker’s health and safety
5.5.1. Worker’s health and 
safety (e.g. proper training, use 
of PPE, below 18 y/o, protocols 
when staff are sick)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.5.2. Personnel training 
and records
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.6. Farm Management/farm records
5.6.1. Proper 
documentation and record 
keeping. Farm records (all 
practices are recorded, 
financial records)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
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Awareness/ 
knowledge 
of the 
technology/ 
practices
Adopting the 
technology/ 
practice?
Level of adoption
Rating Scale:
1-5
(With remarks on 
rating)
Reason for non￾adoption
If NOT adopting, 
what are the 
current farmer’s 
practices
Willing to 
adopt the 
technology/ 
practice?
State your reason 
why or why not 
willing to adopt 
technology/practice
5.6.2. Warehouse/storage 
records (inventory, etc.)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.6.3. Record keeping of use 
of pesticides
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.6.4. Record keeping of 
fertilizer usage
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.6.5. Traceability (where 
harvested, when harvested –
lot numbers, etc.)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.6.6. Product recall 
procedures
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.6.7. Improved Packaging [1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
5.6.8. Stock maintenance 
and preservation (PNS for 
warehousing – inventory and 
sampling)
[1] Yes
[0] No
[1] Yes [0] 
No
[1] Yes [0] 
No
 
133
D. FARM PRODUCTION VOLUME AND VALUE
1. Number of production periods from September 2019 to October 2020: ___________
First Cropping: Second Cropping:
Duration Period:
Area planted (ha)
Type (irrigated, rainfed)
2. Quantity Produced (metric tons)
3. Quantity Sold (metric tons)
4. Quantity Consumed (metric tons)
5. Quantity wasted (metric tons)
6. Price per kg
7. Value of Sales (if paid in PHP)
No. of 
MD/MAD/M
MD
Cost/Uni
t (P)
Total Cost 
(P)
No. of 
MD/MAD/MMD
Cost/Uni
t (P)
Total Cost (P)
13. Seedbed preparation
14. Land Preparation
2.1. Plowing
2.2. Harrowing
2.3 Furrowing
15. Transplanting/ Planting
16. Fertilization
17. Pesticide Application
18. Water Management/ Irrigation
19. Weeding
20. Harvesting
21. Threshing
22. Hauling
23. Storage
24. Drying
25. Milling
26. Others:
27. Pakyaw labor Arrangement: 
MD – Manday (1 Manday = 8 hrs of work)
MAD – Man-Animal Day (with draft animal e.g. carabao)
MMD – Man-Machine Day (with rental or use of farm machineries e.g. tractor)
134
Material Inputs Amount 
(Unit)
Cost/Uni
t (P)
Total Cost 
(P)
Amount (Unit) Cost/Uni
t (P)
Total Cost (P)
7. Seeds
d. Genetic material [1] Hybrid
[2] Inbred
[3] Farmer Saved Seeds/ Own Harvest 
[4] Black
[5] Others, specify_______________ 
[1] Hybrid
[2] Inbred
[3] Farmer Saved Seeds/ Own Harvest 
[4] Black
[5] Others, specify_______________ 
e. Variety, please specify
f. Source of genetic material
8. Fertilizers 
9. Chemicals:
a. Pesticides
b. Herbicides
10. Packaging materials: please 
specify: __________________
11. Others: (Pls. specify)
_____________________
12. Where do you source your inputs? Please, identify 
inputs supplier in the locality.
E. CONSOLIDATED FARMING
1. Do you practice consolidated 
farming? (Enumerator to explain 
consolidated farming)
[1] Yes [0] No (If No, go to 3)
2. If Yes, 
f. What type of consolidation?
[1] consolidation at production
[2] consolidation at the marketing level
[3] complete consolidation, from production to marketing
g. Total area under consolidated 
farming(ha)
h. No. of farmers involved in 
consolidated farming
i. Total production (metric tons)
j. Who is managing the consolidated 
farm?
3. If consolidated farming will be promoted 
in your area, are you willing to adopt it? [1] Yes (If Yes, go to 4) [0] No, state reason: ______________
4. If yes, are you willing to adopt any of the 
ff:
[1] consolidation at production
[2] consolidation at the marketing level
135
[3] complete consolidation, from production to marketing
5. Farm area willing to be allocated for 
consolidated farming (ha)
F. MARKETING OF PRODUCTS 
Individual Farm Consolidated Farm
1. What are the major products being sold? (e.g. 
palay)
2. Major market for the products (identify 
traders/markets where produced are sold)
3. Distance of farm to market road (in kilometers)
a. Farm to market road condition
[1] Poor – Totally unpaved
[2] Fair – Partially paved
[3] Good – Totally paved
[1] Poor – Totally unpaved
[2] Fair – Partially paved
[3] Good – Totally paved
G. RICE FARM PERFORMANCE
1. On Scale of 1-10 (10 being the highest) rate the 
performance in terms of Productivity 1 2 3 4 5 6 7 8 9 10
2. On Scale of 1-10 (10 being the highest) rate the 
performance in terms of Food Safety 1 2 3 4 5 6 7 8 9 10
3. Existing public-private partnership [1] Yes [0] No
4. Certification to standards (e.g. GAP, Organic Agriculture Certification, etc.)
5. Investment in productivity improving technologies (PhP)
6. Investment in food safety technologies (PhP)
H. PROBLEMS ENCOUNTERED
Risk Factors Have you encountered 
these problems?
What are the mitigating measures adopted to 
address the problems?
B. Production
1. Chemical contamination (pesticide residue, heavy 
metals) [1] Yes [0] No
2. Drought [1] Yes [0] No
3. Pest infestation (eg. fall armyworm) [1] Yes [0] No
a. Extent of infestation
136
b. Bureau of Plant Industry approach (likely to be the use of buffer 
farm areas to prevent spread of pest)
c. Biocontrol solution to fall armyworm
d. If no control is being done, would you be willing to adopt a 
technology intended to control FAW?
[1] Yes [0] No
4. Earthquake [1] Yes [0] No
5. Landslide [1] Yes [0] No
6. Typhoon and/or Flood [1] Yes [0] No
B. Post-harvest
7. Physical contamination (glass, metals, sand, stones) [1] Yes [0] No
8. Microbial contamination [1] Yes [0] No
9. Food Adulteration [1] Yes [0] No
10. Milling [1] Yes [0] No
C. Marketing [1] Yes [0] No
11. Packaging and Marketing [1] Yes [0] No
12. Food Misbranding [1] Yes [0] No
13. Others, please specify: [1] Yes [0] No
I. ASSISTANCE NEEDED
What are the assistance needed? Who are the agencies involved: (Government, private, NGO, etc.)
1. Technical assistance
2. Equipment and machineries
3. Financial assistance
4. Market assistance
5. Others, please specify: _________________________________________________________________
158
Annex 6. Guide questions for key informant interviews 
 
Annex 6.1. Key Informant Interview Guide Questions for Government
Baseline Study for the Building Safe Agricultural Food Enterprises (B-SAFE) Project in the Philippines
Name of Respondent: _________________________
Position: ___________________________________
Organization: ________________________________
City/Municipality: _____________________________
1. What is your understanding of food safety, especially for rice, corn, chicken, hogs, milkfish and coco 
sugar? 
2. What are the regulatory policies on food safety (e.g. inspection of food establishments like restaurants 
and canteens; regular inspection of slaughter houses, dressing plants, supermarkets, wet markets, etc.)?
3. What is the regulatory framework being implemented related to food safety?
4. What is the level of implementation of these policies, especially for rice, corn, chicken, hogs, milkfish and 
coco sugar?
5. What is your agency’s role in the implementation of these policies?
6. Who are the key personnel/staff involve in implementing the food safety policies? Describe the 
qualifications needed to effectively implement the policies and guidelines? 
What are the issues related to human resources in terms of implementing the food safety policies and 
guidelines (e.g. capacity of the assigned personnel, lack of appropriate personnel, etc.)?
7. What facilities are available in your locality (including the facilities in your agency) for the implementation 
of food safety policies and guidelines?
Facility Lead Unit/Agency Location
8. What are the various programs implemented/funded to advocate for stakeholder awareness, 
enforcement, adoption of these policies at various stages in the supply chain for rice, corn, chicken, hogs, 
milkfish and coco sugar?
9. Is monitoring for compliance to food safety standards for these commodities being monitored? Who is 
monitoring the compliance?
10. Is there certification being done? Is there regular monitoring if standards are being followed?
159
11. What do you think are the risks in the implementation of the policies? 
How do you manage them? 
Do you have a risk management plan to address these risks? [ ] Yes [ ] No
Plan Type: [ ] Government [ ] Community
RMP Phase of Development: [ ] Proposed
[ ] Adopted
[ ] Implemented
[ ] Institutionalized
What are the risk factors:
[ ] Food Adulteration [ ] Food Misbranding
[ ] Non-certification [ ] Non-compliance to standards 
[ ] Drought [ ] Earthquake
[ ] Landslide [ ] Typhoon and/or Flood
[ ] Others, please specify ____________________________________
Who conducts the RMP? 
RMP Official Title: _______________________________________________________
12. What are the risks of not implementing the policies?
13. What are the issues associated with the implementation of the policies and programs?
14. Trainings attended on food safety
15. Management practices or technologies applied for food safety policy implementation
16. Partnerships/Collaborations (e.g. DOH, DA, LGUs, Other Government Agencies, Private Sector)
a. Identify other organized groups/organizations (e.g. cooperatives, NGOs, POs) in the area working in 
projects/initiatives on food safety? 
Agencies Role/Activities
b. Identify your existing/current partners?
160
Current/Existing Partner Agencies Role and Support Provided
c. Identify your previous partners?
Previous Partner Agencies Role and Support 
Provided
Is the organization still supporting in food 
safety implementation? If not, reason(s) for 
support termination
d. Among the identified agencies, which can be tapped for trainings and other technical activities?
17. Public investments in food safety
18. Public investments for productivity
19. Rate the agency performance (1-10) in terms of functions related to food safety
20. Problems/issues in implementing the policies/guidelines.
21. Recommendations.
161
Annex 6.2. Key Informant Interview Guide Questions for Private Sector
Organization: ________________________________
City/Municipality: _____________________________
1. What is your understanding of food safety protocols and standards?
2. What are the food safety protocols being adopted by your firm? (Describe)
a. [ ] Good Agricultural Practices (GAP)
b. [ ] Good Manufacturing Practices (GMP)
c. [ ] Hazard Analysis Critical Control Point (HACCP)
d. [ ] Sanitary and Phytosanitary Standards (SPS)
e. [ ] Compliance to FDA requirements
f. [ ] Other protocols: ______________________
3. What are the requirements needed to comply to these standards? (e.g. certification)
4. What are the investments in productivity-enhancing technologies and food safety standards? 
(Identify investments, objectives in investment and estimated cost)
5. Did you receive support from government, private firms, NGOs, etc. in compliance to these standards?
Indicate the support provided:
a. Government (e.g. LGUs, DOH, DA, research institutions, FDA, etc.)
b. Private Sector
c. Civil Society/NGOs
d. Other agencies: ______________________
6. What are the support needed from the government, private firms, NGOs, etc. to comply with the 
standards?
a. Government (e.g. LGUs, DOH, DA, research institutions, FDA, etc.)
b. Private Sector
c. Civil Society/NGOs
d. Other agencies: ______________________
7. What are the public-private partnerships in implementing/monitoring food safety standards?
8. Is the partnership or support from these various agencies effective in supporting the adoption and 
compliance to prescribed food safety standards. Please describe.
9. What are the issues and problems in seeking support/partnering with other agencies? 
10. What are the necessary conditions for VC actors like the private sector to adopt higher product quality 
standards?
11. Are you being monitored in terms of compliance to standards?
a. Describe the procedure in monitoring the compliance
b. Who are the key players in monitoring?
c. Issues in monitoring and evaluation
12.
13. What facilities are available in your locality (including the facilities in your agency) for the implementation 
of food safety policies and guidelines?
162
Facility Lead Unit/Agency Location
14. What are the various programs implemented/funded to advocate for stakeholder awareness, enforcement, 
adoption of these policies at various stages in the supply chain for rice, corn, chicken, hogs, milkfish and 
coco sugar?
15. What are the problems/risks encountered in complying to food safety standards? 
Risk Factors (Describe) Mitigating measures adopted?
14. Changes in 
policies/regulations (e.g. 
long process, limited staff 
from monitoring/regulatory 
body)
 
15. Lack of equipment/facilities
16. Lack of technical skills (e.g. 
identification of 
adulteration, misbranding, 
etc.)
17. Lack of partners 
implementing standard
18. Natural calamities (e.g. 
earthquake, landslide, 
typhoon/flood)
19. Others: 
_________________
16. Does your organization have a Risk Management Plan? [ ] Yes [ ] No
Plan Type: [ ] Government [ ] Community
RMP Phase of Development: [ ] Proposed
[ ] Adopted
[ ] Implemented
Who conducts the RMP?
RMP Official Title: ________________________________________________________________
17. What are the plans in sustaining/expanding the adoption of food safety standards?
18. What can you recommend to improve the food safety standards/protocols being adopted?
158
Annex 7. Terms of Reference for Baseline Study 
PHILIPPINES: BUILDING SAFE AGRICULTURAL FOOD ENTERPRISES (B-SAFE)
REQUEST FOR SUBMISSION OF PROPOSALS
The Building Safe Agricultural Food Enterprises (B-SAFE) Project is a four (4) year program 
implemented by Winrock International and funded by the Food for Progress Program of the 
United States Department of Agriculture (USDA).
Winrock International seeks proposals from qualified firms/consultants with experience 
conducting baseline studies on agricultural and economic growth activities. Qualified 
firms/consultants are those that have been involved in similar projects in the past, particularly 
within the last five (5) years.
Interested parties may send their proposals as outlined here within.
REQUEST FOR PROPOSAL – WI-B-SAFE
United States Department of Agriculture Food for Progress 
Building Safe Agricultural Food Enterprises (B-SAFE)
BASELINE STUDY
The purpose of this Request for Proposal (RFP) is to solicit proposals from Consultant organizations / 
firms interested in conducting a Baseline Study for the Building Safe Agricultural Food Enterprises (B￾SAFE). The terms of reference outlined herein may be subject to change by Winrock International 
Institute for Agricultural Development (Winrock) or the U.S. Department of Agriculture (USDA). Any 
changes to the terms of reference will be communicated to interested applicants and, if deemed 
necessary by Winrock, the deadline for submission will be extended. 
AGRICULTURAL CONTEXT IN THE PHILIPPINES
159
Agriculture trade is an essential component of the Philippines economy, providing a lifeline to over 
12 million farmers and fishermen, representing 40% of the country’s labor force, and contributing 
to over $5.68 billion in export revenues. Integration into the Association of Southeast Asian Nations 
(ASEAN) —along with the United States (US) and Government of the Philippines (GOP) commitment 
to strengthen bilateral trade— opens Filipino farmers, businesses, and consumers to expanded 
market opportunities. 
The development and adoption of evidence-based international food safety systems are 
fundamental building blocks for this to happen, and the Philippines has the strong potentials to 
realize this. The GOP has committed to improve domestic food safety systems and adhere to 
international trade protocols which are expected to advance consumer health and strengthen 
bilateral trade relationships. At the food system level, this is evidenced by the Philippines Food 
Safety Law of 2013 and subsequent Implementing Rules and Regulations (2015) which are 
consistent with Codex Alimentarius Commission Guidelines (CODEX), the International Plant 
Protection Convention (IPPC), and the World Animal Health Organization (OIE). The GOP 
commitment to adhering to World Trade Organization (WTO) protocols on Sanitary and 
Phytosanitary (SPS) systems, particularly in relation to evidence-based risk analysis on imports, and 
efforts to eliminate food safety-related non-tariff barriers have been recognized by its trading 
partners. 
This political will is however threatened by the limited capacity of regulatory agencies involved in 
implementing food safety systems. Sustained government action on food safety needs to be 
complemented by private sector investment in upgrading food safety systems. The cost of 
complying with improved domestic and export market food safety standards is a constraint for 
farmers and small businesses when the market incentives for upgrading production and processing 
practices are unclear and relevant business support services (i.e., laboratories and cold chain) are 
inefficient, insufficient, or inaccessible. Lack of cold chain infrastructure, an essential element to 
food safety compliance, drives up transaction costs and contributes to food losses of up to 50% 
from the point of production to distribution to consumers. On the other hand, a burgeoning Filipino 
middle class is demanding safe food and is willing to pay a premium for it. 
In cognizance of these overarching opportunities and challenges, B-SAFE will support the GOP to 
build its capacity to implement and enforce food safety standards and gain adherence of the private 
sector. 
BUILDING SAFE AGRICULTURAL FOOD ENTERPRISES (B-SAFE) PROJECT DESCRIPTION
B-SAFE Food for Progress Strategic Objectives
Winrock will monetize soybean meal and use the proceeds from the sale to implement B-SAFE project 
in the Philippines over a period of four years (October 1, 2019 to September 30, 2023). 
B-SAFE will be focused on contributing to the following two USDA Food for Progress Strategic 
Objectives:
• Increase agricultural productivity by improving the Sanitary and Phytosanitary Standards (SPS) in 
production and management of supply chains. 
• Expand trade of agricultural products by improving the GOP’s regulatory agencies to manage 
risk-based systems, promote awareness of biotechnology, enhance regulatory standards and 
processes, enhance domestic and export market linkages, and build the capacity of the private 
sector to leverage investment. 
160
B-SAFE’s theory of change is: if the GOP and the private sector use risk-based management approaches 
to guide their use of relevant SPS-related technical assistance that build capacity; and if the GOP and 
private sector become stronger at capturing information and decision making to meet SPS and 
regulatory requirements for export and import markets, in market situations that change quickly; and if 
the GOP and private sector adopt and invest in SPS systems and have adequate facilities and equipment 
to use; then agricultural products will have increased trade that meet SPS standards for the US, ASEAN, 
international, and domestic markets. 
The approach is built on two distinct, but mutually reinforcing pillars: (1) GOP regulatory agencies’ 
capacity in risk-based SPS systems; and (2) SPS-compliant supply chain linkages. 
The B-SAFE project is based in Manila to foster a stronger relationship and facilitate effective 
coordination with GOP partner agencies. Its capacity development interventions are expected to be 
implemented in some focused areas of Luzon, Mindanao and Cebu.
(For identification of B-SAFE’s expected contributions to FFPr’s intermediate results and performance 
indicators, refer to the B-SAFE Performance Management Plan.)
Beneficiary Description
B-SAFE will carry out activities in the Philippines’ National Capital Region and in regions that produce a 
major volume of product in each of the target commodity value chains within the horticulture, 
livestock, and fisheries sectors (to be determined before the contract is awarded), targeting the 
following actors: 
1. Pillar I direct beneficiaries: B-SAFE will target GOP regulatory agencies, particularly Manila￾based and targeted frontline regional staff of the Department of Agriculture (DA), Food and 
Drug Administration (FDA), and Local Government Units (LGUs). These agencies will be 
prioritized because of their institutional mandate to govern food safety systems, the capacity 
gaps they face in implementing those systems, and their political will. Within each agency 
and their subdivisions, B-SAFE will liaise with and empower “champions” who can drive 
change. B-SAFE will ensure that women staff are equitably included in training and technical 
assistance activities. The approximate number of direct beneficiaries under Pillar I is 11,500
persons. 
2. Pillar II direct beneficiaries: B-SAFE will target private sector trade associations and 
agribusinesses with the incentives and resources to invest in SPS compliant supply chains 
(both lead firms and SMEs – with a focus on identifying at least 40% women-owned or those 
employing high numbers of women), training service providers that have the proven capacity 
and willingness to respond to dynamic market requirements, and business service providers 
(i.e. refrigerated trucking and packaging companies) that have the ability to invest their 
resources in testing and scaling smallholder-oriented cold chain services. Trade associations 
and firms will be selected based on ability to self-invest, commitment to food safety, and 
aspiration to expand and upgrade. The approximate number of direct beneficiaries under 
Pillar II is 26,000 persons. 
3. Indirect beneficiaries will include GOP regulatory agency departments and officials not 
directly supported by the project but who will benefit from improved policies and 
procedures; SMEs and producers not directly supported by the project or project-assisted 
institutions but who will benefit from stronger supply chains and cold chains; domestic 
retailers who will receive higher quality products; trade associations and alliances not directly 
161
supported by the project but that will benefit from a streamlined policy and regulatory 
system; and consumers who will have access to safer foods.
In total, B-SAFE plans to work directly with the following populations of beneficiaries:
• About 9 Food Safety and Regulatory Agencies of the DA and FDA including the Bureau of Animal 
Industry, Bureau of Plant Industry, National Meat Inspection Service, Bureau of Fisheries and 
Aquatic Resources, Fertilizer and Pesticide Authority, Bureau of Agriculture and Fisheries 
Standards, Biotech Program Office, Policy Research Service, and the Food and Drug 
Administration.
• About 10 Local Government Units involved in the enforcement of regulations.
• About 10 trade associations including Cold Chain Association of the Philippines, Biotechnology 
Coalition of the Philippines, CropLife Philippines, Philippine Association of Meat Processors, 
Philippines Food Processors and Exporters Organization, and others.
• About 20 Training and Business Service Providers including Freshport, American National 
Standards Institute, and others
• About 1,000 agribusinesses working through the value/cold chains of targeted crops/products
Beneficiary type Organizations Approximate Numbers of Beneficiaries
Food Safety and Regulatory Agencies 9 10,500
Local Government Unit 10 1,000
Trade Associations 10 800
Agribusinesses (producers/producer 
organizations, transporters, processors, 
buyers, aggregators/traders, retailers, etc.)
1,000 25,000
Training/Business Service Providers 20 200
B-SAFE Activities
B-SAFE will carry out five activities over a four-year period. For a more comprehensive description of the 
project components and activities, please see B-SAFE Year 1 Work Plan. Brief descriptions of each project 
activity are as follows:
Activity 1: Conduct Sanitary & Phytosanitary Gap Assessment and Benchmark Capacity Needs
Winrock has begun conducting a participatory needs assessment that will identify capacity-building 
priorities and technical assistance (TA) strategies for the Government of the Philippines. This needs 
assessment started with desk research of past capacity assessments as well as other relevant secondary 
sources related to SPS capacity, which will be followed by validation of findings with the Food Safety 
Regulatory Agencies of the Philippines and their participation in a self-assessment activity. Winrock is 
assessing the capacity of the Philippines Food and Drug Administration (FDA) and the Department of 
Agriculture (DA), as well as other stakeholders in sanitary and phytosanitary (SPS) systems, including 
exporters, importers, and the Bureau of Customs. Winrock is assessing the alignment of Filipino SPS 
regulations with international standards, including Codex, IPPC, and OIE.
Activity 2: Enhance Government of Philippines Capacity in Risk-Based Systems 
162
Winrock will develop a capacity-building programs that supports the adoption of international and risk￾based standards to support trade facilitation while being responsive to emerging food borne health risks 
and pest and disease threats with the Philippines Food and Drug Administration (FDA) and the 
Department of Agriculture (DA).
Activity 3: Support Biotechnology Decision-Making and Awareness-Building 
In order to enhance the importation and use of biotechnology, Winrock will support the development of 
a streamlined review/approval process through targeted technical assistance to departments involved in 
permitting and renewal and support inter-departmental coordination and streamlining. Winrock will also 
provide flexible, demand driven technical assistance on evolving biotechnology issues.
Activity 4: Build Technical Capacity of the Private Sector to Meet International Standards
Winrock will strengthen the capacity of the private sector to develop and manage SPS-compliant supply 
chains and adhere to the standards set by the Food Safety Law of 2013. Winrock will provide targeted 
technical assistance to firms to incentivize new, SPS-compliant supply chains to form and investments in 
supply chain upgrades. Winrock will strengthen training service providers who can provide segmented 
training services tailored to food safety requirements.
Activity 5: Build Cold Chain Systems 
Winrock will provide cold chain capacity building by developing business-decision support tools, grants 
targeting small infrastructure and new technologies, trainings, and forums to showcase the initiatives. 
Winrock’s activities will build upon past activities and complement other investments in the sector.
SCOPE OF WORK
Objectives
To support B-SAFE’s learning agenda and capture results, the Winrock Monitoring, Evaluation and 
Learning (MEL) team seeks to contract with a third-party consultant or organization to conduct a 
baseline study. The baseline study will have four principal functions:
• Establishing a baseline as points of comparison to support measurement of program impacts 
as part of future project evaluation activities;
• Validating proposed targets for performance indicators to ensure realistic target setting;
• Supporting program design through situational analysis relevant to target beneficiaries’ 
knowledge and capacities; access to quality and utilization of proposed inputs and 
infrastructure; value chain diagrams; and, organizational capacity; and
• Identifying and recommending responses to risks and constraints that may pose challenges to 
planned project implementation.
Indicator Measurements
A major focus of the analysis of the baseline study are the following twelve (12) FFPr standard indicators 
and two (2) custom indicators. Of the fourteen outlined indicators, quantitative baseline values are 
required to be established for three (3) standard indicators, with their respective disaggregates.
163
No. Indicator Title Type Remarks
SI-22 Number of individuals 
participating in USDA food 
security programs Output Baseline is zero.
SI-23 Number of individuals benefiting 
indirectly as a result of USDA 
assistance Output Baseline is zero.
SI-21 Number of individuals who have 
received short-term agricultural 
sector productivity or food 
security training as a result of 
USDA assistance Output Baseline is zero.
SI-4 Number of individuals in the 
agriculture system who have 
applied improved management 
practices or technologies with 
USDA assistance Outcome
Baseline values of indicator 
and disaggregates will be 
calculated
SI-11 Number of host government or 
community-derived risk 
management plans formally 
proposed, adopted, implemented 
or institutionalized with USDA 
assistance Output
Baseline values of indicator 
and disaggregates will be 
calculated
SI-12 Percent of USDA-assisted 
organizations with improved 
performance Outcome
Baseline values of indicator 
and disaggregates will be 
calculated
SI-9 Number of technologies, 
practices, and approaches under 
various phases of research, 
development, and uptake as a 
result of USDA assistance
Output (phases 1-3);
Outcome (phase 4) Baseline is zero.
SI-13 Number of public-private 
partnerships formed as a result of 
USDA assistance Output Baseline is zero.
SI-17 Number of policies, regulations 
and/or administrative procedures 
in each of the following stages of 
development as a result of USDA 
assistance
Output (stages 1-2);
Outcome (stages 3-5) Baseline is zero.
SI-18 Value of annual sales of farms 
and firms receiving USDA Outcome
Baseline values of indicator 
and disaggregates will be 
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No. Indicator Title Type Remarks
assistance calculated
SI-19 Volume of commodities sold by 
farms and firms receiving USDA 
assistance Outcome
Baseline values of indicator 
and disaggregates will be 
calculated
SI-14 Value of new USG commitments 
and new public and private sector 
investment leveraged by USDA to 
support food security and 
nutrition Outcome Baseline is zero.
CI-1 Number of individuals using 
improved packaging, equipment, 
transportation, or cold storage as 
a result of B-SAFE investment Outcome
Baseline values of indicator 
and disaggregates will be 
calculated
CI-2 Number of farms/firms/ 
laboratories with GAP, GMP, 
HACCP, or ISO certification as a 
result of USDA assistance Outcome
Baseline values of indicator 
and disaggregates will be 
calculated
The consultant should be able to design a statistically sound data collection methodology to ensure 
that the quantitative estimates for the indicator values of SI-11, SI-18 and SI-19 and their 
corresponding disaggregated data sets are produced. For a complete list of indicator disaggregates, 
the consultant may refer to USDA’s Food Assistance Indicators Definition manual.
Key Evaluation Questions4
:
The baseline study is expected to address the following key evaluation questions: 
B-SAFE Specific Research 
Questions Baseline Requirements
1. What models of collaboration 
among local and international 
actors, including public institutions, 
private sector partners, and civil 
society are effective in supporting 
improved compliance with 
standards and regulations?
• Map and describe the private sector various actors and existing models of 
collaboration at baseline 
• Identify and describe the well-functioning collaboration mechanisms in 
order to eliminate them as potential project outcomes.
• Identify and describe potential external factors that may affect project 
outcomes (such as other public or private sector initiatives or donor 
efforts) and identify strategies to segment attribution.
2. What are the conditions (such as 
technologies, cold trucking, GAP, 
GMP, HACCP certification and 
SPS or private sector government 
services) necessary for agriculture 
actors, particularly SMEs and 
producers, to adopt higher product 
quality standards for food safety 
and SPS standards?
• Describe the existing conditions at baseline; identify and describe which 
conditions are enabling at the time of the baseline in order to eliminate 
them as potential project outcomes; identify and describe potential 
external factors that may affect project outcomes (such as other public or 
private sector initiatives or donor efforts) and identify strategies to 
segment attribution.
• Establish baseline process/procedural costs and duration efficiencies for 
select commodities and markets (domestic and import/export) for 
comparison at Final Evaluation.
• Identify the commercial supply chain and cold chain pathways at baseline 
for select commodities for select supermarket chains for comparison at 
Final Evaluation.
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B-SAFE Specific Research 
Questions Baseline Requirements
• Establish baseline organizational and individual capacity for comparison 
at Final Evaluation; establish baseline process/procedural costs and 
duration efficiencies for comparison at Final Evaluation.
Situational Analysis
In addition to the prescribed quantification of values for indicators mentioned above, the following 
situational analysis should be arrived at by the study: 
• Map value chains for each targeted commodity and analyze potential for collaboration among 
chain actors. 
• Analyze the risk management capacities of host government agency partners and communities in 
the targeted project sites by identifying mechanisms in place, including the development and 
institutionalization of risk management plans. Scope of analysis should cover the types of risks 
that have shown to be recurrent and/or potential (e.g., typhoons, flooding, etc.) and the stage at 
which host government partners and/or target communities put in place their respective risk 
management plans. (The consultant is recommended to take reference from the USDA Food 
Assistance Indicators and Definitions manual, February 2019 version, particularly on Indicator SI￾11, for guidance on this analysis.) 
• Establish level of post-harvest loss and sanitary and phytosanitary conditions along value chains 
of each targeted commodity. Establish the potential partners’ capacities and gaps in terms of 
meeting compliance to GAP, GMP, HACCP, or ISO certification standards. 
• For each commodity to be supported by the project, establish the current state of adoption/use 
of improved management practices or technologies by agricultural producers and other value 
chain actors in the field of production, climate risk management, marketing and distribution, post￾harvest handling and storage, and value-added processing. 
• Establish the current organizational performance of targeted beneficiary organizations (e.g., input 
and equipment providers, financial institutions, infrastructure owners, producers’ organizations, 
water users’ associations, women’s groups, trade and business associations, and community￾based organizations) based on any generally accepted organizational capacity measure (e.g., 
Organizational Performance Index). Analyze the potential project partners’ capacity gaps that may 
be addressed with support from the project. Collect necessary contact information, including GPS 
location, for possible follow up. 
Key Audience
• B-SAFE Project staff and partners
• Government stakeholders: Manila-based and targeted frontline regional staff of the following 
agencies with jurisdiction over targeted project sites: 
o Department of Agriculture 
o Food and Drug Administration 
o Local Government Units 
• Private Sector stakeholders: 
o Private sector trade associations with the incentives and resources to invest in SPS 
compliant supply chains
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o Agribusinesses with the incentives and resources to invest in SPS compliant supply chains 
o Training service providers that have the proven capacity and willingness to respond to 
dynamic market requirements
o Business service providers that have the ability to invest their resources in testing and 
scaling smallholder-oriented cold chain services 
• USDA officials located in Washington D.C. (must be consulted as key informants
Methodology
This baseline design will be non-experimental and largely dependent upon a sample survey of 
beneficiary types to establish baseline measurements and provide input to implementation priorities. 
The baseline will be conducted using the following methodologies:
• Document Review: The consultant/organization shall review available project documentation to be 
provided by Winrock, including the B-SAFE MEL Plan. Additionally, the consultant will review 
secondary data, including but not limited to the 2019 FSN Philippines SPS assessment and 2019 
Food Safety and SPS Planning Workshop Report, relevant for providing contextual background on 
the operating environment and agriculture sector in the Philippines. This will be both a quantitative 
and qualitative secondary data source review. To ensure compliance and responsiveness to USDA 
requirements, the consultant will also review USDA guidance on indicators, monitoring and 
evaluation, and the relevant solicitation. Additionally, the consultant may access additional 
materials from credible and validated sources, including government statistics and industry data 
sets. 
• Key-informant Interviews (KII): KIIs will be the principle form of data collection for high-status 
leaders or under conditions in which a group dynamic may inhibit candid discussion. The interview 
protocol will include both questions common across respondent types (facilitating analysis of 
variation in perspectives), as well as customized questions specific to a type or individual who has 
a unique role or view. Likely respondent types include the USDA-led Steering Committee, SPS and 
food safety experts, regional and international trade experts, potential direct and indirect 
beneficiaries in national and local government regulatory agencies and the commercial supply 
chains and cold chains. 
• Focus Group Discussions (FGD): FGDs will consist of groups of four to 10 persons, likely to be 
separated when appropriate by location, value chain function, and type of B-SAFE involvement. 
Dividing FGD into these groupings will support disaggregated analysis to identify possible 
differences in responses according to these key characteristics. Likely types of respondents include 
consumers, laboratory testing facility staff, DA and FDA personnel, private-sector buyers (domestic, 
import, and export), farmers/fisherfolk, and SME owners in transport, processing, and other post￾production functions. 
• Beneficiary- and Client-Based Surveys (BBS): During the baseline evaluation, the consultant will 
survey planned program beneficiaries to gather baseline information on participants to be used to 
measure progress later in the project. The BBS should be able to provide a single point in time 
estimate, which can be compared to the future performance evaluations and annual targets. In 
consultation with B-SAFE, each consultant must define its sample size, selection plan and proposed 
design. B-SAFE anticipates that the sampling plan will follow USDA recommendations for a 
household survey approach with two-stage sampling. Only planned direct beneficiaries will be 
included in the pool with the first stage sampling clusters, followed by second stage sampling of 
direct beneficiaries within the sampled cluster. In order to support data verification, surveys should
be conducted in-person, and whenever possible at the respondent’s farm, infrastructure facility, or 
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place of business. Consultant will collect quantitative data for indicators and disaggregates as above 
specified in section E on Indicator Measurements. Survey sample size should be decided on in 
consultation with B-SAFE management. The consultant must also include a plan for data entry and 
cleaning, weighted sample calculations and analysis, if needed. 
Whenever possible, data should be verified with written documentation. However, when not feasible 
either due to poor recordkeeping, dependency on recall or other threats to validity, the Consultant 
should identify and explain responses to any limitations on data. 
As above stipulated, baseline data for some specified indicators should be disaggregated according to 
USDA mandatory categories identified in the B-SAFE Performance Monitoring Plan (e.g., sex, location, 
commodity). Consultants and Winrock may recommend additional disaggregates useful for project 
management. Consultants can use reliable secondary data sets with corresponding citation and 
rationale for substitution of primary data collection, with the prior approval of Winrock International, 
and are not to be used to set baseline values for project indicators. Secondary data should be for a 
period not beyond 3 years prior to the baselining year. However, secondary data will not qualify for 
indicators requiring baseline values and disaggregates. Consultants are encouraged to suggest creative 
approaches beyond those mentioned in the RFP and explain how precisely they will enable the project 
to answer its questions.
The Consultant should include ethical considerations for research with human subjects in its proposed 
approach. This includes following Do No Harm principles, addressing issues of confidentiality, including 
data management, training of enumerators, and disclosures to respondents. Enumerators should 
inform all respondents that their participation will be used to inform programming but does not 
necessarily commit the project to work with them.
At the Kick-Off Meeting, the B-SAFE management, Winrock headquarters and the consultant will discuss 
the study design and level off on the baseline requirements. The Consultant shall collaborate with 
Winrock B-SAFE team to develop appropriate data collection tools, including the formulation of 
questionnaires, and methodology for conducting the baseline study. The Consultant will then be 
expected to take the primary lead in providing local expertise in the design phase; data collection, 
analysis and interpretation; and support in formulating conclusions and recommendations. 
Tasks and Deliverables
The selected Consultant will implement the following tasks along the proposed timeline and 
approximate LOE as summarized in the below table:
Tasks LOE Estimated 
Date
Kick-off meeting with B-SAFE team to discuss the study design and 
level off on the baseline requirements. 1 day
November 
23, 2020
Desk Review of B-SAFE project documentation (Winrock will 
provide USDA MEL Policy, USDA Food for Progress Indicators and 
Definitions Handbook, Project-Level Results Framework, Project 
MEL Plan and PMP, and relevant project-level 
studies/assessments) and other industry, trade and commodity 
background resources and data records to inform best approach to 
establishing baselines and informing aspects of project design. 3 days
November 
24 – 26, 
2020
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Tasks LOE Estimated 
Date
Draft Baseline Design Plan for the data collection and analysis, 
including: 
1. Listing of B-SAFE’s baseline data requirements, in consultation 
with B-SAFE project staff;
2. Methodology for data collection and analysis, including 
sampling plan with sample size calculations for a 
representative random sample of producers; surveys of other 
types of stakeholders may not be random but should specify 
the sampling method;
3. Recruitment and training requirements for data
collectors/enumerators;
4. Field work schedule and timeline for key milestones;
5. Identification of key assumptions and limitations on data; and
6. Baseline data collection tools (e.g., questionnaires, interview 
guides, secondary data analysis, checklists, interview 
confidentiality agreements, etc.).
7. Data management and analysis plan.
8. Quality assurance plan 
6 days
November 
27 –
December 7, 
2020
Winrock, USDA, B-SAFE feedback on Baseline Design Plan 
(including data collection tools and surveys) received n/a
December 8 
– 11, 2020
Final Baseline Design Plan submitted
3 days
December 
16, 2020
Enumerator training covering B-SAFE project background, 
confidentiality and Do No Harm considerations, data collection 
tools, and interviewing skills.
5 days 
(Saturdays & 
Sundays 
included)
December 
17 - 20
Field work activities scheduled, conducted and completed.
20 days
December 
28, 2020 –
January 29, 
2021
Data consolidation. Organize all data collected into a database, 
exportable into Microsoft Excel spreadsheets. Ensure anonymity 
of data, Do No Harm concerns, and confidentiality. 7 days
February 5, 
2021
Draft Baseline Report of baseline measures/values of relevant 
indicators and disaggregates, with recommendations for project 
implementation based on needs assessment. 
The report should include the following sections:
• Cover Page (with photo, if possible)
• List of Acronyms
• Table of Contents, which identifies page numbers for the 10 days
February 19, 
2021
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Tasks LOE Estimated 
Date
major content areas of the report.
• Executive Summary (3 to 5 pages): should be a clear and 
concise stand- alone document that gives readers the essential 
content of the baseline report.
• Body of Report (not to exceed 30 pages):
o Introduction (2 page): Briefly describe the B-SAFE project 
and state the objectives of the baseline assessment.
o Methodology (4 pages): Describe the data collection 
methods used including schedule of activities, description
of any statistical analysis undertaken, and constraints and 
limitations of the baseline process and rigor.
o Findings and analysis (14- 18 pages) pertaining to 
qualitative data addressing the baseline learning questions 
and baseline measures/values for selected indicators and 
disaggregates, as prescribed
o Recommendations (6-10 pages): Provide actionable 
recommendations on project design, implementation, 
approaches to mitigate potential risks to implementation 
(including COVID-19), validation of indicator targets, and 
monitoring and data collection methodologies based on 
lessons learned in the process of collecting the baseline 
data
• Annexes: Attach this Terms of Reference; additional 
methodology documentation, including data collection tools 
and field visit schedule; list of stakeholders interviewed with 
number and type of interactions; table of indicator values; 
other special documentation as needed.
• Photographs: 20-25 high quality photographs (minimum 300 
dpi resolution) of data collection activities, i.e., interviews; 
focus group discussions, current agriculture and trade 
practices, etc. Photographs should be provided upon 
submission of the written baseline report on a CD-ROM disc, 
thumb drive or equivalent external storage device.
Winrock, USDA, B-SAFE feedback on draft Baseline Report 
received n/a
February 26, 
2021
Final Baseline Report submitted to Winrock B-SAFE by COB
4 days
March 5, 
2021
Available for follow-up guidance per donor requests for clarification 
on baseline report. 6 days
Baseline Completion – Total Estimated LOE 65 days
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Evaluation Management
Winrock B-SAFE management (COP and MEL Director) and Winrock B-SAFE home office staff (Program 
Officer, Program Associate, and Agriculture Unit Director) will be responsible for the following tasks to 
support the baseline assessment:
• Providing background documentation on the B-SAFE project.
• Recommending and providing introductions to key stakeholders for interviews and other forms 
of data collection
• Reviewing Design Plan, data collection tools, and draft and final Baseline reports.
• Approving Design Plan, data collection tools, and draft and final Baseline reports.
Deliverables under this assignment will include the following:
• Baseline Design Plan (as outlined in above table).
• B-SAFE quantitative and qualitative datasets (descriptive and phenomenal data sets that can be 
observed but cannot be quantified) and listing of respondents with independent variables (e 
.g., sex, beneficiary type, location, etc.); quantitative data sets for specified indicators should 
include prescribed disaggregates. 
• Draft of the Baseline Report.
• CD-ROM or other external storage of photographs (each photo clearly titled including GPS
coordinates).
• PowerPoint presentation of the Draft Baseline Report to the Winrock B-SAFE office, with 
electronic version and hard copies of presentation.
• Final Baseline Report with Annexes submitted as electronic Word and PDF files (as outlined in 
the above table).
• Evaluators shall provide a copy of the final baseline report that is free of personally identifiable 
information (PII) and proprietary information which is ready for publication and should be 
accessible to persons with disabilities, known in the US as making the reports Section 508 
compliant. USDA will provide a report template for the evaluator to use that helps makes the 
report document 508 compliant.
As specified in regulations (see 7 CFR Part 1499.13 and 7 CFR Part 1599.13), baseline study will be 
independent and conducted by a third party. Independence of the evaluation function from program 
design and management is a core principle of the donor (USDA). Independence helps to ensure both 
credible and objective evaluation. The project is committed to selecting a proposal that will be 
conducted by people who are involved in the design and implementation of the project and we will 
ensure that the process is free from political influence and organizational pressure.
Timeframe 
For the purposes of the proposal, the consultant should present a proposed timeline for completion 
of the aforementioned activities. The consultant should be available to begin work on November 23rd. 
The entire assignment, including report revisions, presentations and consultations, is expected to 
require a Level of Effort not to exceed 65 days, and completion by March 30, 2021.
SUBMISSION REQUIREMENTS
Proposal Components
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Local and international firms and organizations that are registered to work in the Philippines and 
interested in implementing this assignment are requested to submit a proposal. Each proposal should 
be typed in 12-point font. The proposal submission should include each of the following sections in the 
specific order listed below in order to be considered for this consultancy:
• Technical proposal (not exceeding 15 pages) The technical proposal should reflect how the 
applicant would undertake all the tasks in the Scope of Work. The applicant will provide a 
detailed plan of specific activities and timetable for carrying out the assignment and data 
collection and analysis activities. Also, it will include a proposal for the statistical 
approach/method to be used to estimate the optimum sample size and selection of survey
participants.
• Organization (maximum of 2 pages) The applicant shall provide summary of organizational 
capacity to conduct monitoring and evaluation in general and baseline studies specifically. This 
section should also state the organizational legal status in Philippines, type of ownership and 
management, overview of projects/services, and geographic scope.
• Team Composition (maximum of 2 pages) The applicant shall list and briefly describe the 
name(s), qualifications and responsibilities of the staff proposed to work on the assignment. 
(CVs of proposed personnel should be included in an annex and not counted toward page limit). 
The proposed team must include an Evaluation Team Leader who is an Agricultural Economist, 
Rural Development Specialist, or has related qualifications with expertise in evaluating 
development projects in the Philippines. Experience with value chain analysis is preferred. 
Other recommended team members could include: analyst familiar with quantitative and 
qualitative data analysis; data entry team; and survey enumerators.
Proposed staff should meet the following requirements at a minimum:
o Team members with experience in horticultural, livestock and fisheries sectors
o Team members with experiencing conducting evaluation of USDA and/or USAID projects
o Team members with experience developing designing surveys and developing sampling
plans.
o Team leader with experience working with multicultural teams
o Philippine language skills
• Experience (maximum of 4 pages) Illustrative listing of contracts, grants, or cooperative 
agreements involving similar or related assignment within the last three years. Reference 
information must include the location, a brief description of work performed, value of the 
project, and contact with current telephone numbers and email addresses. Winrock reserves 
the right to contact these projects as an organizational reference in the selection process.
• Assumptions and Risks (maximum of half page) Describe assumptions which are necessary for 
the survey to be implemented. Describe any risk/threats which could potentially threaten 
implementation of the activities and what is or will be done to mitigate these risks.
• Work Plan (maximum of 2 pages) Propose the main activities of the assignment, their content 
and duration, phasing and interrelations, milestones (including interim approvals by the Client), 
and delivery dates of the reports. The proposed work plan should be consistent with the 
technical approach and methodology, showing understanding of the SOW and ability to 
translate them into a feasible working plan. A list of the final documents, including reports, 
drawings, and tables to be delivered as final output, should be included here. The work plan 
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should be consistent with the Work schedule. This contract is tied to deliverable based
payments.
• Financial Budget (length as required to clarify proposed costs) The applicant shall propose a 
realistic cost estimate for this assignment, including a line-item budget and budget narrative
that justifies expenses. The budget shall include only those costs that can be directly attributed 
to the activities proposed (with explanation of line items). The line item budget should include 
expenses for enumerator training. In the budget narrative, applicant must show existence of 
financial and administrative systems to adequately account for funds provided under this 
assignment.
Example of financial budget is given below:
Line Item Cost
I. Professional Remuneration
II. Travel and Per Diem
III. Supplies and Equipment
IV. General Administrative Costs
Total Cost including applicable VAT and tax, and others cost as per
country law
N.B. Please add detailed cost breakdown documents for summery of cost. Above line items are 
mentioned as example for understanding. Please add separate sheet or more Column & Row for 
detail information, if necessary. For detailed budget please use attached excel sheet.
Assumptions & Constraints
Key assumptions for the baseline bids include that the bidder already has qualified evaluators, data 
analysts, and enumerators ready to start work without having to go through a lengthy recruitment 
process; that bidders will provide their own data collection and analysis hardware and software; and that 
the evaluation team will be ready to start work within 5 days after signing the subcontract. Likely 
constraints include limited logistical or administrative support the project can provide to the evaluation 
team, such as transportation and scheduling meetings, due to a smaller project team size at start up and 
travel related and group size restrictions due to COVID-19. 
Terms and Conditions
Each Bidder must conform to the following requirements:
1. Must agree to the general provisions outlined in Attachment A. Any variations must be requested 
in the bid submission and agreed to before a purchase order is issued.
2. No minimum order requirements may be made by a bidder.
3. Winrock International will not consider advance payment.
4. A Bidder may withdraw or change a bid before the deadline to receive bids if written notice of the 
withdrawal or change is received by Winrock for submission of bids. Any changes may be made 
173
only by substitution of another bid.
5. Bids received after the time specified in the request for bid will not be considered and shall be 
returned to the respondent.
6. Final Payment by Winrock will not be made until acceptance of the baseline report by the USDA.
7. Winrock reserves its rights to reject any services and to cancel all or any part of this contract if 
bidder fails to deliver all or any part of the services described in the request for bid. If bidder 
ceases to conduct its operations in the ordinary course of business or are unable to meet its 
obligations, Winrock may cancel this order without liability except for deliveries previously made 
or for goods covered. The bidder must be able to demonstrate substantial experience in working 
on similar projects and, in particular, to demonstrate past experience in working with 
organizations similar to Winrock.
8. The bidder must have excellent communication skills and methods and be able to communicate 
very clearly at every step of development, both providing information to the Winrock team aswell 
as requesting, understanding and closely following guidance from the Winrock team.
PROPOSAL SELECTION
Technical Evaluation
Submitted Proposals must clearly demonstrate alignment with the SOW outlined above with an adequate 
level of detail. The following are criteria that all proposals will be judged on:
Proposal Evaluation Committee (PEC) or Procurement Committee (PC) set out by WI, will review the 
technical as well as financial proposals as per Eligibility/Qualification and Technical criteria mentioned 
below. Technical proposal will carry 70% weightage; and financial proposal will carry 30% weightage 
(Technical Pass Mark is 65%). The proposal will be ranked according to combined technical and financial 
score using the weightage. 
Technical evaluation criteria & allocated points are as follows:
No. Evaluation criteria Points
1 (1.1+1.2) Specific experience of the firm related to this assignment 25
1.1 (a+b+c) Experience of the Firm and its Consultant/s 15
1.1.a Minimum of 5 years of demonstrated experience in designing and 
conducting baseline and similar studies in development sector 
particularly horticulture agriculture and business development 
fields. 5
1.1.b Experience in working with US government grants, specifically 
USDA and/or USAID 5
1.1.c Knowledge of agriculture sectors, including SPS and GAP, GMP, 
HACCP, or ISO certification standards 5
1.2 (a+b) Experience in similar assignments 10
1.2.a Experience handling multiple datasets from a large survey, and 
producing high quality analytical reports is what’s required. 5
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No. Evaluation criteria Points
1.2.b Experience in conducting similar assignments for other donors in
the Philippines 5
2(2.1+2.2+2.3) Implementation and Quality Assurance Plan 35
2.1 Understanding the assignment, comments and suggestions of 
Consultant/s on the Terms of Reference. 8
2.2 (a+b+c+d) Roll out plan 19
2.2.a Team Composition and task assignment 5
2.2.b Roll out plan and calendar 4
2.2.c All proposed activities reflected in the work plan with timeline 5
2.2.d All proposed activities reflecting the assignment properly 5
2.3 (a+b) Quality Assurance Plan 8
2.3.a Monitoring tools 4
2.3.b Monitoring plan 4
3 (3.1+3.2) Professional qualification and competence for the assignments 10
3.1 Consultant/s educational qualification 5
3.2 List of similar assignment conducted, with names of references for 
each 5
4 (4.1) Methodology and Reporting Structure 30
4.1 Details and quality of methodology proposed for the assignment 30
Total Points 100
As a part of evaluation process, the firm may be interviewed/asked for presentation on submitted 
proposal by Proposal Evaluation Committee. Only firms/consultants that obtain more than 65% in the 
technical proposal will have their financial proposal reviewed.
Financial Evaluation Criteria
A financial proposal shall include Summary of Costs, Breakdown of Staff Remuneration, Travel and DSAs 
(Daily Subsistence Allowance), miscellaneous, overhead costs (if any). Total cost of the financial proposal 
(after correctness and confirmation of arithmetical error, if any) will be considered for financial 
evaluation. Evaluation will be done based on proposed budget amount linked with deliverables. A critical 
analysis will be done to cross check the proposed amount is appropriate and justified to complete the 
assignment.
Financial evaluation criteria & allocated points are as follows:
No. Particulars Points
1 Presentation of Summary budget 20
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No. Particulars Points
2 A detail budget with all unit and unit rate (also with details of each unit rate) 40
3 Budget note and justification of each cost 40
TOTAL 100
Consultant Selection Process
The potential consultants will be evaluated according to the criteria mentioned above. Winrock B-SAFE
and headquarters will be following an internal evaluation and selection process.
• Notification of RFP opportunity disseminated on October 22, 2020.
• Deadline for Expression of Interest and request for supporting documents on October 29, 2020.
• Deadline for submission of questions to Winrock on RFP is October 29, 2020.
• Responses on questions disseminated to applicants by November 5, 2020.
• Deadline for submission of proposal is November 12, 2020 by 5:00 pm (Philippine Standard Time).
• Submission should not include any zipped files.
• Winrock International may request additional documentation after the bid deadline.
• Winrock B-SAFE and headquarter staff will review submitted proposals after the closing date
• Winrock B-SAFE and headquarter staff will conduct in-person or remote interviews with 
candidates under consideration.
• Winrock B-SAFE and headquarter staff reserve the right to consult applicant’s provided references 
of prior clients, included in experience section of proposal.
• Winrock B-SAFE will work with the selected consultant to develop a contract with final Scope of 
Work, budget and timeline; and
• Awardees will be required to submit deliverables as outlined above.
• Winrock reserves the right to negotiate with the bidders with or without discussion.
SUBMISSION OF PROPOSAL
Instructions to Bidders
• Validity of bid: 60 days starting from the submission date.
• For each item quoted, a detailed description and picture should be included if applicable
• Cost quoted must include unit price and total price in Philippine Peso and USD and inclusive oftax
• Technical and financial proposal must be submitted as separate attachments
• Payment terms and complete banking information
• Winrock reserves right to make changes or cancel this solicitation as required byUSDA
• Agreement will be offered as fixed price basis (but detail budget is required for analysis)
Bid Documents to Include
• Legal Business Name
• Authorized contact including address, phone number and email
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• Proof of business registration and nationality
• Provide legal establishment / registration, GST, NTN certificates or any other additional 
supporting documents (if any)
• Proposed Firm must provide information, organizational profile, CVs of key staff/team 
members and documentary evidences to establish that they have met eligibility criteria for 
thisservice.
• Applicant/s must clearly indicate in their profiles for the past evaluation work they have 
conducted, with names of references for each.
• A list of previous similar contracts completed successfully with the names and contact 
information of clients.
• A sample of similar assignment done previously.
Submission Procedures
Submissions must be in English and typed single-spaced. All pages must be numbered and include the RFP 
reference number and name of organization on each and every page. The proposals must be emailed to 
Winrock B-SAFE Project to the attention of:
MEL Manager: Nielo Tingzon
Email address: Nielo.Tingzon@Winrock.org
Please include the name of the person in your organization who is submitting the application as well as 
the current telephone and email contacts.
Deadline for submission of proposal is at COB November 12, 2020. 
Winrock B-SAFE reserves the right to fund any or none of the applications submitted.
Certification of Independent Price Determination
(a) The offeror certifiesthat—
(1) The prices in this offer have been arrived at independently, without, for the purpose of restricting 
competition, any consultation, communication, or agreement with any other offeror, including but not
limited to subsidiaries or other entities in which offeror has any ownership or other interests, or any 
competitor relating to (i) those prices, (ii) the intention to submit an offer, or (iii) the methods or factors 
used to calculate the prices offered;
(2) The prices in this offer have not been and will not be knowingly disclosed by the offeror, directly or 
indirectly, to any other offeror, including but not limited to subsidiaries or other entities in which offeror 
has any ownership or other interests, or any competitor before bid opening (in the case of a sealed bid 
solicitation) or contract award (in the case of a negotiated or competitive solicitation) unless otherwise 
required by law;and
(3) No attempt has been made or will be made by the offeror to induce any other concern or individualto 
submit or not to submit an offer for the purpose of restricting competition or influencing the competitive 
environment.
(b) Each signature on the offer is considered to be a certification by the signatory that the signatory—
(1) Is the person in the offerors organization responsible for determining the prices being offered in this bid 
177
or proposal, and that the signatory has not participated and will not participate in any action contrary to 
subparagraphs (a)(1) through (a)(3) above; or
(2) (i) Has been authorized, in writing, to act as agent for the principals of the offeror in certifying that those 
principals have not participated, and will not participate in any action contrary to subparagraphs (a)(1) 
through (a)(3) above; (ii) As an authorized agent, does certify that the principals of the offeror have not 
participated, and will not participate, in any action contrary to subparagraphs (a)(1) through (a)(3) above; 
and (iii) As an agent, has not personally participated, and will not participate, in any action contrary to 
subparagraphs (a)(1) through (a)(3) above.
(c) Offeror understands and agrees that –
(1) violation of this certification will result in immediate disqualification from this solicitation without 
recourse and may result in disqualification from future solicitations; and
(2) Discovery of any violation after award to the offeror will result in the termination of the award fordefault.
Attachment A: General Provisions
1. Independent Organization. Vendor shall be an independent organization and shall not claim to be an agent, 
officer, or employee of Winrock International and shall not have authority to make any commitments on behalf 
of Winrock International, except to the extent that such authority shall be expressly conferred by Winrock 
International in writing.
2. Insurance. Vendor shall maintain comprehensive general liability and automobile liability insurance coverage 
to cover itself for all activities undertaken under this Purchase Order.
3. Publicity. No advertising or publicity having or containing any reference to Winrock International, or in which 
the name of Winrock International is mentioned, shall be used by Vendor without the written approval of 
Winrock International. Vendor shall not use Winrock International's logo or title block on any correspondence 
or written matter without the written approval of Winrock International.
4. Communication with the Funding Agency. All contact, communication and dealings with the Funding Agency 
and its agent and representatives by Vendor and any of its personnel, consultants, or Vendors, on matters 
subject to this Purchase Order shall be through or approved by Winrock International.
5. Terms of Payment. Subject to any superseding terms on the face hereof, Vendor shall invoice Winrock 
International at address and contact listed on Purchase Order and be paid upon completion/acceptance of the 
required supplies/services. Vendor shall be paid no later than thirty (30) days unless otherwise negotiated in 
terms and conditions of the Purchase Order after Winrock’s receipt of an acceptable invoice or Winrock’s 
receipt of the completed products/services, together with any required documents. Drafts will not be honored.
6. Compliance with Law. Vendor's performance of work hereunder and all products to be delivered hereunder 
shall be in accordance with any and all applicable executive orders, Federal, State, municipal, and local laws 
and ordinances, and rules, orders, requirements and regulations. Such Federal laws shall include, but not be 
limited to, the Fair Labor Standards Act of 1938 as amended. Unless otherwise agreed, governing law shall be 
that of the State of Arkansas.
7. Assignment Prohibited. Vendor may not assign or Subcontract any part of the activities described in the 
Purchase Order without the prior written consent of Winrock International. Where such prior written consent 
is given, it shall not relieve the Vendor of any of its responsibilities under this PurchaseOrder.
8. Indemnification. Vendor hereby agrees to indemnify, hold harmless, and defend each and every Winrock 
Indemnified Party from and against any and all Claims arising out of, relating to, or in connection with (i) any 
injuries (including death) to persons and for damage or loss to property caused by, arising out of, or relating to 
Vendor performing the Contract Work or otherwise providing of any goods and/or services covered by this 
Agreement in whatever manner and by whomever the same may be caused; (ii) any wrongful act, omission, 
178
misconduct, or violation of Laws by Vendor or by any agent, servant, or employee of Vendor or any Vendor and 
any party retained by any Vendor; (iii) any negligent, wanton, willful, or intentional act or omission of or by 
Vendor, any Vendor, anyone directly or indirectly employed or retained by any of them, or anyone for whose 
acts any one of them may be liable under any Law; (iv) any breach of Warranty; and (v) any breach or violation 
by Vendor of, or default by Vendor with respect to, any other terms and conditions of this Agreement or 
Vendor's duties, obligations, and responsibilities under this Agreement. The indemnity provided in this Section 
is intended for the benefit of Winrock and each Winrock Indemnified Party. Vendor's indemnification 
obligations will in no way be limited by the limitation on amount or type of damages or by any compensation 
or benefits payable by or for Vendor or any Vendors, under any worker's compensation act, employer liability 
act, disability act, or other employee benefit act. The indemnification provided in this Section will survive the 
expiration or termination of this Agreement.
9. Title and Risk of Loss. Title to and risk of loss of, each product and/or service to be delivered/provided 
hereunder shall, unless otherwise provided herein, pass from Vendor to Winrock upon acceptance of such 
product/service by Winrock.
10. Stop Work Order. Winrock International’s contracting authority may at any time before acceptance of the 
order by the Vendor, by written order to the Vendor require the Vendor to stop all, or any part, of the work 
called for by this purchase order for a period of 90 days after the order is delivered to the Vendor, and for any 
further period to which the parties may agree. The order shall be specifically identified as a stop-work order 
issued under this clause. Upon receipt of the order, the Vendor shall immediately comply with its terms and 
take all reasonable steps to minimize the incurrence of costs allocable to the work covered by the order during 
the period of work stoppage. Within a period of 90 days after a stop work order is delivered to the Vendor, or 
within any extension of that period to which the parties shall have agreed, the Winrock International 
contracting authority shall follow the guidelines as described in FAR 52.242-15.
11. Debarment and Suspension. In accepting this Agreement, the Vendor certifies that neither it nor its principals 
are presently debarred, suspended, proposed for debarment, declared ineligible or voluntarily excluded from 
participation in this transaction by any US Federal department or agency. Any change in the debarred or 
suspended status of the Vendor during the life to this Agreement must be reported immediately to Winrock. 
The Vendor agrees to incorporate the Debarment and Suspension certification into any lower-tier award that 
they may enter into as part of this Agreement.
12. Termination. Winrock International shall have the option to terminate this Purchase Order in the event of 
termination of the Prime Agreement by the Funding Agency for whatever reasons. In the event of such 
termination, Vendor shall be entitled to receive all supporting funds as described herein for those expenditures 
justifiably incurred to the time of termination of this Purchase Order, including commitments which cannot be 
reversed or mitigated, to the extent that said funds are available to Winrock International under its Prime
Agreement. Either party shall have the option to terminate this Purchase Order if either party fails to perform 
its obligations under this Purchase Order and fails to cure any such default in performance within thirty (30) 
days unless otherwise noted in Purchase Order Terms & Conditions after written notification by the other party 
thereof. In the event termination is due to fault of Vendor, Winrock International may hold it liable of 
reimbursement for expenses incurred due to said fault and of any penalties, damages or interest which are 
incurred by Winrock International as a result of said fault; provided that Winrock International delivers 
adequate documentation to Vendor evidencing the expenses, penalties, damages, or interest which have been 
incurred. Any such expenses may be deducted from any sums due to Vendor, and Vendor shall promptly pay 
any deficiencies upon demand of Winrock International. In the event of termination of this Purchase Order, 
Vendor shall, upon receipt of notification of termination, immediately take all steps required to minimize 
additional costs incurred during the termination of performance hereunder.
13. Applicable Law. This purchase order shall be enforced in accordance with the body of law applicable to 
procurement of goods and services by the Federal Government. To the extent that Federal law does not exist, 
the laws of Arkansas shall apply. By accepting this agreement Vendor agrees to waive any rights to invoke the 
jurisdiction of the local national courts where this contract is performed.
14. Drug Trafficking. Winrock reserve the right to terminate this purchase order to demand a refund or take other 
179
appropriate measures if the Vendor is found to have been convicted of a narcotics offense or to have been 
engaged in drug trafficking as defined in 22 CFR Part 140.
15. Disputes. Any disputes arising out of this Purchase Order or from a breach thereof shall be submitted to 
arbitration in Little Rock, Arkansas, and the judgment upon the award rendered by the arbitrators may be 
entered in any court having jurisdiction thereof. The arbitration shall be held under the standard form of the 
Rules of the American Arbitration Association.
16. Liens. Vendor agrees to deliver/provide the products/services which are the subject-matter of this order to 
Winrock free and clear of all liens, claims, and encumbrances.
17. Access to Accounting Records. Vendor agrees that Winrock International, the Funding Agency, or any of their 
duly authorized representatives, shall have access to any books, documents, papers and records of the Vendor 
which are directly pertinent to the services provided hereunder, for the purpose of making audits, 
examinations, excerpts and transcriptions upon prior written request and during normal business hours.
18. Confidential Information. The Vendor may become privy to confidential information either provided by to the 
Vendor by Winrock International or discovered by the Vendor without the knowledge of Winrock International. 
The Vendor agrees to treat such information as confidential and to use such information only for the purposes 
of carrying out the scope of work under this agreement. The Vendor further agrees that such information will 
not be disclosed to any third party without the prior written consent of Winrock International and return to 
Winrock International all original and copies of such information upon completion of this agreement or 
whenever requested by Winrock International, whichever occurs first. No news release, public announcement, 
denial or confirmation of any part of the subject matter of this agreement shall be made without the prior 
written consent of Winrock International. The restrictions of this article shall continue in effect upon 
completion or the parties may mutually agree upon termination of this Agreement for such period of time as 
in writing. In the absence of a written established period, no disclosure is authorized.
19. Intellectual Property. Unless otherwise provided for in the Primary Contract, if Vendor first conceives of, 
actually puts into practice, discovers, invents, or produces any intellectual property subject to patent or 
copyright exclusively in connection with Vendor’s performance pursuant to the Purchase Order (the 
“Intellectual Property”), it shall report that finding to Winrock International. Vendor shall also assist Winrock 
International in obtaining governmental protection for rights in the intellectual property. Winrock International 
shall retain ownership of all patents and copyrights for intellectual properties created as the result of this 
Vendor Agreement, either in part or in whole. In the case of copyrighted materials created as a result of this 
Vendor Agreement, Winrock International shall grant to Vendor a nonexclusive, royalty-free right to use, 
publish, reproduce or distribute those materials for educational purposes.
20. Work Product Presumptive Property. All writings, books, articles, computer programs, databases, source and 
object codes, and other material of any nature whatsoever, including trademarks, trade names,and logos, that 
is subject to copyright protection and reduced to tangible form in whole or in part by Vendor in the course of 
Vendor’s service to Winrock shall be considered a work made for hire, or otherwise Winrock property. During 
this agreement and thereafter, Vendor agrees to take all actions and execute any documents that Winrock may 
consider necessary to obtain or maintain copyrights, whether during the application for copyright or during the 
conduct of an interference, infringement, litigation, or other matter (Winrock shall pay all related expenses). 
Vendor shall identify all materials in which Vendor intends to exempt from this provision prior to the use or 
development of such materials.
21. Affirmative Action. Unless this Purchase Order is exempted by rules, regulations or orders of the Secretary of 
Labor, Vendor agrees to comply with the provisions of paragraph 91) through (7) of Part 202 of Executive Order 
11246, as amended; the affirmative action for handicapped workers clause set forth in 41 CFR 60-741.5; and 
the affirmative action for disabled veterans and veterans of the Vietnam era clause set forth in 41 CFR 60-250.4, 
which are by reference incorporated herein.
22. Force Majeure. Vendor’s failure to perform the terms and conditions of this Purchase Order, in whole or in 
part, shall not be deemed to be a breach or a default hereunder or give rights to any liability to Winrock 
International if such failure is attributable to any act of God, riot, public enemy, fire, explosion, flood, drought, 
180
war, sabotage, an action by governmental authorities or any other condition beyond the reasonable control.
23. Rights in Data. The Vendor understands and agrees that Winrock may itself and permit others, including 
government agencies of the United States and other foreign governments, to reproduce any provided 
publications and materials through but not limited to the publication, broadcast, translation, creation of other 
versions, quotations there from, and otherwise utilize this work and material based on this work. During the 
agreement and thereafter, Vendor agrees to take all actions and execute any documents that Winrock may 
consider necessary to obtain or maintain copyrights, whether during the application for copyright or during the 
conduct of an interference, infringement, litigation, or other matter (all related expenses to be borne by 
Winrock). The Vendor shall identify all materials it intends to exempt from this provision prior to the use or 
development of such materials. The Vendor shall defend, indemnify, and hold harmless Winrock against all 
claims, suits, costs, damages, and expenses that Winrock may sustain by reason of any scandalous, libelous, or 
unlawful matter contained or alleged to be contained in the work, or any infringement or violation by the work 
of any copyright or property right; and until such claim or suit has been settled or withdrawn, Winrock may 
withhold any sums due the Vendor under this agreement.
24. United States Executive Order 13224 – Anti Terrorism. The Vendor is reminded that U.S. Executive Orders and 
U.S. Law prohibit transactions with, and the provision of resources and support to, individuals and organizations 
associated with terrorism. It is the legal responsibility of the Vendor to ensure compliance with these Executive 
Orders and laws. This provision must be included in all lower-tier awards and will flow down into task orders 
issued under this IQC. A list of individuals and organizational names that are the subject of this Executive Order 
can be found at the web site of the Office of Foreign Assets Control (OFAC) within the U.S. Department of
Treasury. The address of this web site is http://treasury.gov/ofac.
25. Computer Software Licenses. Vendor agrees to specifically identify to Winrock International any and all 
computer software licenses ("including shrink-wrap") as may convey to the Winrock International. The Vendor 
agrees that any and all computer software developed in the performance of this order using Winrock 
International monies shall, unless otherwise agreed, become and remain the property of Winrock International.
26. Anti-trafficking in Persons Directive. Vendor acknowledges that WI International is opposed to human 
trafficking, prostitution, and related activities, which are inherently harmful and dehumanizing, and contribute 
to the phenomenon of trafficking in persons. None of the funds made available under this Agreement may be 
used to engage in trafficking in persons or to promote, support, or advocate the legalization or practice of 
prostitution. Nothing in the preceding sentence shall be construed to preclude assistance designed to 
ameliorate the suffering of, or health risks to, victims while they are being trafficked or after they are out of 
the situation that resulted from such victims beingtrafficked.
27. Conflict of Interest. Vendor must establish safeguards to prevent employees, consultants, or members of 
governing bodies from using their positions for purposes that are, or give the appearance of being, motivated 
by a desire for private financial gain for themselves or others such as those with whom they have family, 
business, or other ties. Each Subcontracting institution receiving funds must have written policy guidelines on 
conflict of interest and avoidance thereof. These guidelines should reflect country and local laws and must 
cover conflict of interest situations regarding financial interests, gifts, gratuities and favors, nepotism, and other 
areas such as political participation and bribery. Winrock International must be informed of any conflict of 
interest or appearance of conflict of interest by the recipient. If organizational or management systems cannot 
be structured to neutralize such conflict, Winrock International may choose to terminate the relationship with 
the Vendor.
28. No Improper Payments: Vendor agrees and represents that, in connection with its performance hereunder, it 
has not and will not make any payments or gifts or any offers or promises of payment or gifts of any kind, 
directly or indirectly, to any official of any government, government agent, government instrumentality or to 
any political candidate. This agreement will become null and void if the recipient organization makes any such 
offer, promise, payment or gift in connection with performance of this agreement.
29. Insurance & Work on Winrock’s or Winrock’s Client Premises. When Vendor performs work on Winrock’s 
premises during the performance of this order, the Vendor agrees to maintainGeneral Liability Insurance in the 
181
amount of at least $500,000 per claim/occurrence unless otherwise noted in the Purchase Order Terms & 
Conditions and such other insurance as may be required in writing by the Winrock Client. Vendor, however, 
shall maintain adequate insurance coverage against claims arising from injuries sustained by Vendor on 
Winrock’s facilities and agrees to be liable for all damages & claims arising against Winrock for which the Vendor 
is responsible.
30. U.S. Export Control Laws. Vendor shall at all times comply fully with all United States export control laws and 
regulations as they apply to any goods, software, or information, or the direct product of such information, 
provided under this Agreement. Vendor shall not at any time sell, deliver, or divert any goods other than in 
strict compliance with all applicable U.S. export control laws and regulations.
31. Liquidated Damages. If the Vendor fails to deliver the supplies or perform the services within the time specified 
in this agreement, Winrock may require that Vendor pay, in place of actual damages, liquidated damages in the 
amount of one percent (1%) unless noted in the Purchase Order Terms & Conditions of the agreement value 
for each day of delay. If Winrock terminates this agreement in whole or in part for default, as provided under 
section 11 above, Vendor is liable for liquidated damages accruing until such time that Winrock reasonably 
obtains delivery or performance from another Vendor. These liquidated damages shall be in addition to any 
excess costs for re-purchase. Vendor will not be charged with liquidated damages when delay of delivery or 
performance is beyond the control and without the fault or negligence of the Vendor.
32. Entire Purchase Order. The Purchase Order document and all attachments incorporated therein represents 
and constitutes the entire Purchase Order between parties and shall not be explained, modified, or 
contradicted by any prior or contemporaneous negotiations, representations, or agreements, either written or 
oral. Only a written instrument signed by each party may amend this Purchase Order.
33. Waiver. A waiver of a breach of any provision of this Agreement shall not constitute a waiver of any subsequent 
breach of that provision or a breach of any other provision of this Agreement. The failure of Winrock to enforce 
at any time or from time to time any provision of this Agreement shall not be construed as a waiver of any of 
Winrock's rights or the Vendor's duties.
34. Severability. If any provision or any portion of a provision of this Agreement shall be finally determined to be 
superseded, invalid, illegal, or otherwise unenforceable pursuant to any applicable legal requirements or court 
order, such determination shall not impair or otherwise affect the validity, legality, or enforceability of the 
remaining provision or portion of the provision hereunder, which shall remain in full force and effect as if the 
unenforceable provision or portion weredeleted.
35. Clauses Incorporated By Reference. Work performed under this Agreement is pursuant to a contract or grant 
from the U.S. Government, or other funding sources, and all relevant flow-down clauses from the contract or
grant shall be deemed to be incorporated in this Agreement: (a) in such manner as to make the Vendor subject 
to those clauses, as applicable; and (b) to the extent necessary to enable Winrock International to perform its 
obligations under the contract or grant and to enable the funding source to enforce its rights hereunder. This 
agreement incorporates the following FAR, and agency regulations (AIDAR) as applicable. To the fullest extent 
that these clauses flow-down or apply to the Vendor, they are incorporated herein by reference with the same 
force and effect as if they were given in full text. Where appropriate and applicable under these clauses, 
reference to the “Government” shall be interpreted to mean “Winrock International” and “Vendor” to mean
“Vendor.”
36. Laws and regulations within the General Provisions apply to all purchase orders. Special provisions that apply 
to a specific purchase order activity can be found in the Terms and Conditions section of this agreement. It is 
the responsibility of the vendor to read and accept the terms and conditions included in the purchase order.
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Attachment B: Results Framework
183
Annex 8. Conflict of Interest Statement 
184
List of Appendices 
Rice Appendices 
Rice Appendix 1. Overview of the Rice Industry
Rice is the most important crop in the Philippines, with a per capita consumption of about 111.62 kg/year. In 2020, 
the industry contributed the largest, at 18.1 percent, to the agriculture, forestry and fishery GVA. It employed 2.1 
million farmers, 110,000 and 320,000 workers for post-farm and ancillary activities, respectively. 
The country was the 8th largest rice producer of the world with 11.73 million metric tons in 2018/2019. More than 
three-fourths (77 %) of the country’s palay output were harvested from irrigated areas and the rest from rainfed 
farms. Luzon accounted for the bulk of the country’s palay output (60.7 %), of which almost one-third came from 
Central Luzon. Cagayan Valley was also a major rice producing region, accounting for 14.1 percent of the country’s 
total output. The three regions in Visayas had 17 percent of total output, bulk of which (11 percent) was from 
Western Visayas region. Mindanao accounted for about one-fifth of total, with the SOCCKSARGEN region as the top 
producer having a share of 6.3 percent, followed by Northern Mindanao which had 4 percent of the country’s total 
palay output.
The average volume of imported rice from 2017 to 2019 was 2 million metric tons. Import volume was only 0.9 
million metric tons in 2017. However, this amount increased considerably to 2 million metric tons in the following 
year and further jumped to 3 million in 2019. During the same period per capita consumption increased from 119 
kg/year in 2017 to 128 kg/year in 2019. Rice self-sufficiency consequently declined from 95 percent in 2017 to 79.8 
percent in 2019. The increasing dependence on imports is attributed to import liberalization under the 2019 Rice 
Tariffication Law. 
The government enacted the RTL in 2019 to comply with its quarter-of-a-century obligation under the WTO 
Agreement on Agriculture to convert the rice import monopoly of the National Food Authority into ordinary import 
rice tariff. In 2018, rice prices increased by 20 percent, pushing the country’s inflation by about two percentage 
points. 
The import monopoly of the NFA had pushed rice prices up and eroded the competitiveness of the country’s rice 
farmers vis-à-vis the Thai and Vietnamese farmers. The total cost of a kilogram of local rice is PhP 12.41, which is 
almost twice as high as that of Vietnam and 41 percent higher than that of Thailand. The high cost is due mainly to 
the labor cost, which on average is PhP3.66/kg as against less than PhP1/kg in Vietnam and Thailand. The costs of 
animal labor, as well as fuel and oil for farm machinery are likewise higher in the Philippines. Accordingly, the 
farmgate price of palay is high, which understandably translates to higher wholesale and retail prices of the 
commodity in the country. 
Besides production cost, rice marketing in the Philippines is likewise more costly than in Thailand and Vietnam. 
Marketing a kilogram of rice entails a cost of PhP 4.63, significantly higher than the corresponding figures of PhP 
2.73 in Thailand and PhP 3.78 in Vietnam. This cost disadvantage is traced to relatively inefficiencies in transporting, 
milling and packaging rice locally. Relative to Vietnam and Thailand, the Philippines has a natural comparative 
disadvantage in rice production since former have larger flat plains, fewer typhoons and better access to water, the 
Mekong River system. This river provides a rich source of soil nutrients thus, the higher paddy yields achieved in 
these countries. Liberalizing rice imports is therefore considered advantageous to the country so that consumers
can enjoy lower rice prices. 
To enhance the competitiveness of rice farmers, the government has implemented various competitiveness￾enhancing programs, funded with the Rice Competitiveness Enhancement Fund (RCEF) with at least 10 billion pesos 
per year for a period of six years. RCEF is funded from the in-quota customs duties of rice imports, which can 
185
accumulate to at least 60 billion pesos in the next six years following the enactment of the RTL. Besides RCEF, the 
DA is implementing its Rice Roadmap.
Rice Industry in Bukidnon
Bukidnon has a total land area of 1,049,859 hectares. Of this, 669,529 hectares are classified as timberland and the 
remaining as alienable and disposable of which, 92% is utilized for agricultural production. In terms of area 
harvested, corn and rice are the two largest crops grown in the province. Other important crops are sugarcane and 
pineapple. From the latest census of agriculture in 2012, 38,333 households of the province are engaged in corn 
production and 8,333 households in rice. There are over a thousand small or medium firms in the province engaged 
in rice and corn milling (Provincial Profile, 2019).
About 95 percent of rice producers in Bukidnon cultivate less than 5 hectares (average is 1.75 hectares) and are 
therefore classified as smallholders using the Food for Progress (FFPr) classification. Majority (56%) of the farmers 
are male, almost all (98%) of whom are more than 30 years of age and trace their ethnic origin either as “Higaonon”, 
“Kapampangan” and “Cebuano”. Three fourths of these farmers have at most ten years of formal education, and 
the rest have 11 to 14 years. Fifty- seven percent of households have at least five members. The large majority (75%) 
have monthly household income of at most PhP 11,000 and may therefore be classified as poor, while 15 percent 
have monthly household income of more than PhP11,000 to lower than PhP21,000. Almost all (96%) have non-farm 
income sources, albeit small or less than PhP10,000 monthly. Six (6) percent of the farmers are members of 
cooperatives, while 66 percent are members of farmers associations (Rice Appendix Tables 3 and 4).
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Rice Appendix 2. Rice Probit Models
Probit models are used to explore the factors affecting significantly the decision of producers to adopt a given 
improved technology or management practice. The model is formulated and estimated using the data from the 
survey conducted in this baseline study. The general form of the model is 𝑌𝑖 = 𝐴 +∝
𝒕 𝑿𝑖 +∈𝑖 where 𝑌𝑖
is a binary 
variable with values of 0 and 1, representing the adoption decision of producer i. 𝑿𝑖
is a vector of explanatory 
variables attributable to producer I, while ∝ is a vector of same dimension representing the coefficients of each of 
the explanatory variable in 𝑿. 𝐴 and ∈𝑖 are respectively the constant and error terms, respectively of the probit 
model. 
For the rice producers, the model specified in this study is the following:
𝑌𝑖𝑗 = 𝐴𝑗 + ∑ 𝛼𝑘𝑆𝐸𝐷𝐶𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑆𝐸𝐷𝐶
+ ∑ 𝛽𝑘𝐹𝐴𝑅𝑀𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐹𝐴𝑅𝑀
+
∑ 𝜇𝑘𝑀𝑘𝑖 + ∑ 𝛿𝑘𝐼𝑁𝑆𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑀 ∀ 𝑘 𝑖𝑛 𝐼𝑁𝑆
+ ∑ 𝛾𝑘𝐼𝑁𝐹𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐼𝑁𝐹
+ 𝜀𝑖𝑖
𝑌𝑖𝑗 is 1 if respondent I adopts technology/practice j,
J=1 is pest management (especially control of fall army worm); j=2 is general pest management (recommended 
pesticide application); j=3 is soil fertility management; j=4 is nutrient management; j=5 is water management; j=6 
is post-harvest management; j=7 is consolidated farming; j=8 is GAP certification; j=9 is organic farming.
𝑺𝑬𝑫𝑪𝒌𝒊 is the vector of socio-economic demographic cultural variables attributable to producer i and used to 
explain the adoption decision j of producer I, where k=1 is education; k=2 is age; k=3 is ethnicity, k=4 is gender, 
k=5 is household income, k=6 is non-farm income; and k=7 is household size.
𝑭𝑨𝑹𝑴𝒌𝒊 is the vector of farm characteristics attributable to producer i and used to explain the adoption decision j 
of producer i, where k=1 is irrigated/rainfed farm; k=2 is farm size; and k=3 is distance from market; k=4 is 
accessibility; and k=5 is fall army worm infestation.
𝑴𝒌𝒊 is the vector of market-related variables attributable to producer I and used to explain the adoption decision j 
of producer I, where k=1 is premium price for quality; k=2 is major market (e.g. trader, consolidator, processor); 
k=3 is source of market information.
𝑰𝑵𝑺𝒌𝒊 is the vector of institutional variables attributable to producer i and used to explain the adoption decision j 
of producer I, where k=1 is membership in organization; k=2 is access to extension service; k=3 is availability of 
technology in the area; k=4 is contractual arrangements; k=5 is access to credit; k=6 is access to crop insurance; 
k=7 is beneficiary of government program; and k=8 is financial inclusion.
𝑰𝑵𝑭𝒌𝒊 is the vector of infrastructural variables attributable to producer i and used to explain the adoption decision 
j of producer I, where k=1 is access to farm to market roads; k=2 is road condition; and k=3 is access to the 
internet.
𝐴𝑗
, 𝜀𝑖𝑖 are respectively the constant and error terms of the model.
𝛼𝑘, 𝛽𝑘,𝜇𝑘, 𝛿𝑘 and 𝛾𝑘 are the vectors of coefficients for each of the variable k in vectors SEDC, FARM, M, INS, and 
INF respectively.
187
Rice Appendix Table 1. Reason for non-adoption of GAP practices on area
assessment, rice farms in Bukidnon
Reason Number Reporting % 
Farm location assessment
Not enough knowledge on farm location assessment 110 58.2
Difficult to apply/assess 10 5.3
No time 11 5.8
No need to assess the farm 9 4.8
No one conducted the farm assessment 35 18.5
others 7 3.7
Soil nutrient analysis using color chart
Lack of knowledge/awareness 48 25.8
Lack of facility/accessible analysis center 87 46.8
Lack of time 15 8.1
No budget/expensive 8 4.3
Not practiced 6 3.2
Others 16 8.6
Farm sanitation
Lack of knowledge/awareness 7 33.3
Labor intensive 3 14.3
Others 4 19.0
Agri water management
Lack of knowledge/awareness 97 65.1
Lack of facility/equipment 19 12.8
Lack of time 17 11.4
Others 9 6.0
Rice Appendix Table 2. Results of Probit analysis on adoption of GAP practices among rice 
farmers
Adoption of GAP Coef. Std. Err. Z P>z
YrsInSchool -.021 .0272 .596 .440
Sex -.401** .1775 5.105 .024
HHIncome .000 .0000 1.999 .157
HHSize .022 .0326 .463 .496
FarmSize -.002 .0168 .011 .917
FarmOwn .012 .1825 .004 .949
DistFarmtoMarket -.038** .0148 6.429 .011
FAW -.113 .1782 .399 .527
IPM -.172 .1966 .763 .382
MajorMarket .207 .1780 1.346 .246
MemOrg -.255 .1959 1.696 .193
AccExt .082 .1920 .183 .668
AccCredit .033 .1902 .030 .862
AccAgriIns .061 .1955 .096 .757
FarmMarketRoad .212 .1353 2.462 .117
cons -.622 .4025 2.388 .122
**Significant at 5% level; *Significant at 10% level
188
Corn Appendices 
Corn Appendix 1. Overview of the Corn Industry
Corn is the second most important crop in the Philippines after rice. It is not only used as food for human 
consumption but also for animal feed and industrial uses. Two types of corn are grown in the country, yellow and 
white corn. Yellow corn is used mostly for animal feeds, while white corn is mostly for human consumption, and 
partly for industrial uses. The per capita consumption of corn in 2019 was 20.54 kg/year. In 2020, corn was the 6th 
biggest contributor to GVA of agriculture, fishing and forestry, and 3rd in the crops sector after rice and coconuts. In 
addition, an estimated 600,000 households depend on corn farming as a primary source of income, most of whom 
are small farmers with an average farm size of merely 1.14 hectares.
Yellow corn production, area harvested and yield during the last decade are shown in Corn Appendix Figure 1. Area 
harvested is steadily increasing during the period. Consequently, total volume of production was generally on an 
uptrend, albeit the trend is not as smooth as that of area harvested expectedly due to the interplay of agro-climatic 
and agronomic conditions, which may vary over time and which determine to a large extent the annual volume of 
output. It is interesting to note the rapid growth of yellow corn production in just a decade. The 50-percent 
expansion is attributed more to yield growth than to area expansion. Yield expansion from 2.5 MT/ha in 2010 to 6 
MT/ha in 2020 may be attributed primarily to the use of genetically modified corn technology.
In contrast to yellow corn, the country’s white corn output plateaued over the last ten years at about 2.2 million 
metric tons per year (Corn Appendix Figure 2). 
Cagayan Valley is the country’s largest yellow corn producing region, producing hardly anything of white corn, but 
comes after BARMM in terms of combined output of both types of corn. Northern Mindanao is the third largest 
yellow corn producing region, but harvests most of the country’s white corn. Other major corn producing regions in 
the Philippines are SOCCSKSARGEN and the Ilocos regions.
The country’s corn supply and utilization accounts from 2017 to 2019 are shown in Corn Appendix Table 2. The 
annual average domestic output was about 7.9 million metric tons. Together with an annual average import of 650 
thousand metric tons, the average annual gross supply of the country was about 9.2 million metric tons. 
The bulk of the annual supply (about 5.1 million metric tons) were used as animal feeds, while about 1 million metric 
ton were used as raw material by the various processing industries. The net food disposable, i.e. for consumption, 
was about 2.16 million metric tons per year. 
The production of yellow corn in the country remains profitable with a net profit to cost ratio of 0.4 in 2011 (Corn 
Appendix Table 3). This even improved the following years reaching as high as 0.77 in 2014. The net profit to cost 
ratio was slightly lower at 0.67 in 2019. 
Seeds, fertilizer and pesticide constitute the largest cash expense items in yellow corn production amounting to 
almost PhP7,000 per hectare in 2019. This represents about 44 percent of the total cash cost. However, hired labor 
is the single highest expense item amounting to almost PhP5,600 per hectare. The cost of seeds and hired labor were 
increasing over the years, albeit very slightly. Together with the cost of pesticides, these are the cost items that have 
to be managed if not significantly reduced to sustain the financial viability of producing yellow corn in the country.
Producing white corn is much less profitable than yellow corn. The net profit to cost ratio of producing white corn, 
which was 0.38 in 2011 approximates that of yellow corn, but the profitability difference between the two widened 
over the years in favor of yellow corn. In 2019, the net profit to cost ratio of producing white corn was only 0.23, 
which is a far cry from the 0.67 reported for yellow corn.
189
Corn Appendix 2. Corn Probit Models
Probit models are used to explore the factors affecting significantly the decision of producers to adopt a given 
improved technology or management practice. The model is formulated and estimated using the data from the 
survey conducted in this baseline study. The general form of the model is 𝑌𝑖 = 𝐴 +∝
𝒕 𝑿𝑖 +∈𝑖 where 𝑌𝑖
is a binary 
variable with values of 0 and 1, representing the adoption decision of producer i. 𝑿𝑖
is a vector of explanatory 
variables attributable to producer I, while ∝ is a vector of same dimension representing the coefficients of each of 
the explanatory variable in 𝑿. 𝐴 and ∈𝑖 are respectively the constant and error terms, respectively of the probit 
model. 
For the corn producers, the model specified in this study is the following:
𝑌𝑖𝑗 = 𝐴𝑗 + ∑ 𝛼𝑘𝑆𝐸𝐷𝐶𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑆𝐸𝐷𝐶
+ ∑ 𝛽𝑘𝐹𝐴𝑅𝑀𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐹𝐴𝑅𝑀
+
∑ 𝜇𝑘𝑀𝑘𝑖 + ∑ 𝛿𝑘𝐼𝑁𝑆𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑀 ∀ 𝑘 𝑖𝑛 𝐼𝑁𝑆
+ ∑ 𝛾𝑘𝐼𝑁𝐹𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐼𝑁𝐹
+ 𝜀𝑖𝑖
𝑌𝑖𝑗 is 1 if respondent I adopts technology/practice j,
J=1 is pest management (especially control of fall army worm); j=2 is general pest management (recommended 
pesticide application); j=3 is use of Bt corn; j=4 is nutrient management; j=5 is consolidated farm management; j=6 
is GAP certification; and j=7 is organic farming.
𝑺𝑬𝑫𝑪𝒌𝒊 is the vector of socio-economic demographic cultural variables attributable to producer i and used to 
explain the adoption decision j of producer I, where k=1 is education; k=2 is age; k=3 is ethnicity, k=4 is gender, 
k=5 is household income, k=6 is non-farm income; and k=7 is household size.
𝑭𝑨𝑹𝑴𝒌𝒊 is the vector of farm characteristics attributable to producer i and used to explain the adoption decision j 
of producer i, where k=1 is irrigated/rainfed farm; k=2 is farm size; and k=3 is distance from market; k=4 is 
accessibility; and k=5 is fall army worm infestation.
𝑴𝒌𝒊 is the vector of market-related variables attributable to producer I and used to explain the adoption decision j 
of producer I, where k=1 is premium price for quality; k=2 is major market (e.g. trader, consolidator, processor); 
k=3 is source of market information.
𝑰𝑵𝑺𝒌𝒊 is the vector of institutional variables attributable to producer i and used to explain the adoption decision j 
of producer I, where k=1 is membership in organization; k=2 is access to extension service; k=3 is availability of 
technology in the area; k=4 is contractual arrangements; k=5 is access to credit; k=6 is access to crop insurance; 
k=7 is beneficiary of government program; and k=8 is financial inclusion.
𝑰𝑵𝑭𝒌𝒊 is the vector of infrastructural variables attributable to producer i and used to explain the adoption decision 
j of producer I, where k=1 is access to farm to market roads; k=2 is road condition; and k=3 is access to the 
internet.
𝐴𝑗
, 𝜀𝑖𝑖 are respectively the constant and error terms of the model.
𝛼𝑘, 𝛽𝑘,𝜇𝑘, 𝛿𝑘 and 𝛾𝑘 are the vectors of coefficients for each of the variable k in vectors SEDC, FARM, M, INS, and 
INF respectively.
190
Corn Appendix Table 1. Corn Grits Classification, PNS/BAFPS 15:2004, Philippines
Grade factors (% by 
weight maximum)
 Grades
Premium Grade No. 1 Grade No. 2 Grade No. 3 Grade No. 4
Moisture Content 14 14 14 14 14
Aflatoxin 20ppb 20ppb 20ppb 20ppb 20ppb
Filth 0.1 0.1 0.1 0.1 0.1
Discolored Grits Trace 0.5 1.0 2.0 3.0
Foreign Matter Trace 0,5 0.8 1.0 2.0
Grits of other colors Trace 0.5 1.5 3.0 5.0
Grits of other sizes 1.0 4.0 7.0 10.0 13.0
Corn Appendix Table 2. Supply and utilization accounts, corn, 2017-2019
SUPPLY UTILIZATION
Net Food Disposable
Year Beginning
Production Imports
Gross
Exports Seeds
Feeds &
Processing
Per Capita Ending
Stock Supply Waste Total
Kilogram
/Year Gram/Day Stock
Level (in ‘000 metric tons)
2017 382 7,915 475 8,772 a/ 51 5,145 1,056 1,569 15.06 41.27 952
2018 952 7,772 1,017 9,740 a/ 50 5,052 1,037 2,925 27.66 75.79 676
2019 676 7,979 458 9,113 a/ 50 5,186 1,064 2,000 18.65 51.08 812
Average 670 7,889 650 9,209 a/ 51 5,128 1,052 2,165 20.46 56.05 813
Growth Rate (in percent)
17-18 149.03 -1.81 113.94 11.03 -1.61 -1.81 -1.81 86.44 83.64 83.64 -28.95
18-19 -28.95 2.66 -54.91 -6.44 0.21 2.66 2.66 -31.62 -32.59 -32.59 20.09
Average 60.04 0.43 29.51 2.30 -0.70 0.43 0.43 27.41 25.52 25.52 -4.43
Corn Appendix Table 2. Results of Probit analysis on willingness of corn farmers to adopt GAP 
practices
Willingness to adopt 
GAP
Coef. Std. Err. Z P>z
YrsInSchool -.021 .0272 .596 .440
Sex -.401** .1775 5.105 .024
HHIncome .000 .0000 1.999 .157
HHSize .022 .0326 .463 .496
FarmSize -.002 .0168 .011 .917
FarmOwn .012 .1825 .004 .949
DistFarmtoMarket -.038** .0148 6.429 .011
FAW -.113 .1782 .399 .527
IPM -.172 .1966 .763 .382
MajorMarket .207 .1780 1.346 .246
MemOrg -.255 .1959 1.696 .193
AccExt .082 .1920 .183 .668
AccCredit .033 .1902 .030 .862
AccAgriIns .061 .1955 .096 .757
FarmMarketRoad .212 .1353 2.462 .117
cons -.622 .4025 2.388 .122
**Significant at 5% level; *Significant at 10% level
191
Hogs Appendices 
Hogs Appendix 1. Overview of the Hog Industry
Until the outbreak of the African Swine Fever (ASF) in the third quarter of 2019, the country’s swine industry had 
increasing pig herd. The industry had been one of the most important contributors to agriculture sectoral 
performance, contributing more than PhP 200 billion or 15.2% to total agricultural output in 2019. 
Backyard and commercial farms make up the industry. Backyard farms are mostly found in rural areas with one sow 
and at most ten heads. Commercial farms vary a lot in size from the smallest commercial farms with two sows and 
from 11 to 20 heads to the large farms, some of which are known to have 5,000 heads. The largest commercial farms 
are typically integrated, with some farms going into contract growing.
Backyard farms dominate the industry, accounting for 62% of total inventory (Hogs Appendix Fig. 1). However, about 
75% of the swine herds in Central Luzon and CALABARZON are raised in commercial farms (Hogs Appendix Fig. 2).
ASF Outbreak
The country’s swine population had consistently grown from 12.7 million heads in 2016 to 13.01 in 2019 (Hogs 
Appendix Table 8). Central Luzon had the largest inventory, accounting for 18% in 2016 to 17% in 2019 of total herd. 
CALABARZON and Western and Central Visayas followed, having respectively 12% and 11% share of country’s pig 
inventory. Following the ASF outbreak, hog population declined by 13% from 13 m heads in 2019 to 11.269 M in 
2020. Hardest hit region was Central Luzon, which suffered a 51-percent decline of its herd. 
CALABARZON’s swine population likewise declined due to the ASF outbreak by 13.8%. Other regions also 
experienced a slight decline in swine inventory in 2020. However, major producing regions namely Central Visayas, 
Western Visayas and Northern Mindanao continued to expand their respective herds in 2020 despite the outbreak. 
By the third quarter of 2020, CALABARZON had the largest swine inventory in the country, followed by Western 
Visayas and Central Visayas. 
Twenty-five provinces were affected by the disease causing the continuous decrease in hog production (DA Strategic 
Communications, 2020). From July to September 2020, the total hog produced was estimated at 508.91 thousand 
MT, live weight, which was 7.7% lower from the previous year quarter’s output of 551.62 thousand MT, live weight. 
By December 2020, the DA reported that almost 350,000 hogs have been culled to prevent the spread of the virus 
and a total of P56 billion has been lost to the hogs’ industry. Currently, prevention and control of the disease, 
quarantine procedures, monitoring of movements, inspection, education campaign and other eradication programs 
are carried out by the authorities and stakeholders to addressing the problem. 
Pork production was also increasing from 2.23 million MT in 2016 to 2.29 million MT in 2019, but fell to 2.1 m MT in 
2020 (Hogs Appendix Table 9), a year-to-year decrease of 4.5%. Central Luzon and CALABARZON were hardest hit, 
their pork outputs cut by 23% and 12%, respectively. Visayas and Despite the ASF outbreak, Mindanao sustained the 
growth of its pork output.
Following the decline in production, the farmgate prices of live hogs in 2020 showed a sharp increase from P100/kg 
liveweight in January to P162/kg live weight in December (Hogs Appendix Fig. 3). This is in contrast to the trend in 
the previous year, where prices in started at P120 in January and ended at below P100 in December. 
In the last quarter of 2020, prices of pork across the country increased resulting to price cap regulations by the 
government in the early 2021. Shipments from Mindanao started in February 2021 to buffer the supply in Luzon and 
stabilize prices, coupled with the plan to increase the minimum access volume and lowering of tariffs of imported 
pork. In addition, the DA allocated P280 million for the establishment of cold storage warehouses with meat cutting 
192
facilities to lessen the trading of live animals in the country, and P400 million budget to assist and help the hog 
raisers recover from the disease outbreak (Simeon, 2020).
Meat Facilities
There are 117 slaughterhouses accredited as AA by the NMIS, 27 of which are found in CALABARZON, 19 in Central 
Luzon and 16 in the National Capital Region (Hogs Appendix Table 10). There are only 8 AAA-slaughterhouses, and 
3 of them are found in CALABARZON. 
Of the 76 AA-accredited meat cutting plants, 39 are found in NCR, 13 in Central Luzon, and 10 in CALABARZON. For 
the AAA meat cutting plants, 6 out of 8 are found in CALABAZON. 
The 22 AA-accredited meat distribution centers are mostly found in Luzon. Thus, while these facilities are fairly 
evenly spread throughout the country, nonetheless three regions have the largest concentration of these facilities, 
namely CALABARZON with 46 facilities, NCR with 39 and Central Luzon with 36 units. 
Situation in Batangas
At the provincial level, Batangas has the largest hogs’ inventory in CALABARZON, contributing up to 45% of the 
region’s herd. (Hogs Appendix Table 11). With chicken, hogs’ industry is a major contributor to the economy of the 
province. More than 75% of the hogs are in commercial farms. In February 2019, the first case of ASF was reported 
and confirmed in the province by the Office of the Provincial Veterinarian (OPV) (Macaraig, 2020), although 
officially the outbreak was reported sometime in August 2019. The province, along with the different national 
government agencies, had coordinated in controlling the spread of the ASF virus. In August 2020, the DA provided 
P272.5 million worth of assistance to ramp up the agricultural sector of the province (DA Communications Group, 
2020).
As of November 2020, 934,166 hogs have been affected (Elarmo, 2020). Vigorous efforts were conducted by the 
OPV to control the spread of the ASF in the province. Aside from culling and information and education campaigns, 
18 disinfection sites were also established, and the movement of the commodity was strictly monitored, “Cash for 
Work” programs for the affected hog farmers were provided, and repopulation efforts were made to allow farmers 
to recover from ASF losses. 
The DA and Tanauan City Government established the first government-owned slaughterhouse in the City, the 
Triple A “AAA”, to boost the hog industry. The facility is located in a 1.9 ha area, which is composed of a cold chain 
network, meat laboratory, wastewater treatment area, and modernized system that can process 500 head per 8-
hour shift (DA Communications Group, 2020). The facility, targeted to start operating in April 2021, is expected to 
help ensure food safety, sustain livelihoods, and the economy of the country recover from the disease outbreak. 
193
Hogs Appendix 2. Hogs Probit Models
Probit models are used to explore the factors affecting significantly the decision of producers to adopt a given 
improved technology or management practice. The model is formulated and estimated using the data from the 
survey conducted in this baseline study. The general form of the model is 𝑌𝑖 = 𝐴 +∝
𝒕 𝑿𝑖 +∈𝑖 where 𝑌𝑖
is a binary 
variable with values of 0 and 1, representing the adoption decision of producer i. 𝑿𝑖
is a vector of explanatory 
variables attributable to producer I, while ∝ is a vector of same dimension representing the coefficients of each of 
the explanatory variable in 𝑿. 𝐴 and ∈𝑖 are respectively the constant and error terms, respectively of the probit 
model. 
For the hog producers, the model specified in this study is the following:
𝑌𝑖𝑗 = 𝐴𝑗 + ∑ 𝛼𝑘𝑆𝐸𝐷𝐶𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑆𝐸𝐷𝐶
+ ∑ 𝛽𝑘𝐹𝐴𝑅𝑀𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐹𝐴𝑅𝑀
+
∑ 𝜇𝑘𝑀𝑘𝑖 + ∑ 𝛿𝑘𝐼𝑁𝑆𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑀 ∀ 𝑘 𝑖𝑛 𝐼𝑁𝑆
+ ∑ 𝛾𝑘𝐼𝑁𝐹𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐼𝑁𝐹
+ 𝜀𝑖𝑖
𝑌𝑖𝑗 is 1 if respondent i adopts technology/practice j,
J=1 is ASF Management; j=2 is Biosecurity; j=3 is GHP Certification, j=4 is Cold Chain, j=5 is Slaughterhouse, j=6 is 
Cutting Plant, j=7 is ISO Certification, j=8 is HACCP Certification
𝑺𝑬𝑫𝑪𝒌𝒊 is the vector of socio-economic demographic cultural variables attributable to producer i and used to 
explain the adoption decision j of producer I, where k=1 is education; k=2 is age; k=3 is ethnicity, k=4 is gender, 
k=5 is household income, k=6 is non-farm income; and k=7 is household size.
𝑭𝑨𝑹𝑴𝒌𝒊 is the vector of farm characteristics attributable to producer i and used to explain the adoption decision j 
of producer i, where k=1 is Sow level; k=2 is Inventory level for weaning to finish; k=3 is Farm ownership (e.g. sole 
proprietorship, partnership, etc.); k=4 is Integrator; k=5 is number of years in business; k=6 is distance from main 
market; k=7 is Breed type (e.g. native or commercial breed)
𝑴𝒌𝒊 is the vector of market-related variables attributable to producer I and used to explain the adoption decision j 
of producer I, where k=1 is premium price for quality; k=2 is major market (e.g. trader, consolidator, processor); 
k=3 is source of market information.
𝑰𝑵𝑺𝒌𝒊 is the vector of institutional variables attributable to producer i and used to explain the adoption decision j 
of producer I, where k=1 is membership in organization; k=2 is access to extension service; k=3 is availability of 
technology in the area; k=4 is contractual arrangements; k=5 is access to credit; k=6 is access to livestock 
insurance; k=7 is beneficiary of government program; and k=8 is financial inclusion.
𝑰𝑵𝑭𝒌𝒊 is the vector of infrastructural variables attributable to producer i and used to explain the adoption decision 
j of producer i, where k=1 is access to farm to market roads; k=2 is road condition; k=3 is access to the internet; 
.k=4 is trucking services; k=5 is access to slaughterhouse; and k=6 is access to cutting plant.
𝐴𝑗
, 𝜀𝑖𝑖 are respectively the constant and error terms of the model.
𝛼𝑘, 𝛽𝑘,𝜇𝑘, 𝛿𝑘 and 𝛾𝑘 are the vectors of coefficients for each of the variable k in vectors SEDC, FARM, M, INS, and 
INF respectively.
194
Hogs Appendix Table 1. Trading by Hog Producers
Volume traded by producers: 118,707 MT
Product form Sold to Selling method Mode of Payment
Live hogs 94%
Traders 83%
Pick up 97% Cash 93%
Delivered 2%
Check 2%
Direct 
selling 17%
Consignment
Both 1% 1%
Combination 4%
Carcass 5%
Traders 65%
Pick up 100%
Cash 94%
Direct 
selling 35% Consignment
6%
Meat cuts 1%
Traders 67%
Pick up 100% Cash 100% Direct 
selling 33%
Hogs Appendix Table 2. Trading by Hog Traders
Volume traded by traders: 306,695.43 MT
Product 
form Sold to Mode of Delivery Mode of Payment Price 
setter
Live 
hogs 
(11%)
Traders 50% Delivered 50% Cash 75%
Markets (public 100% Trader
markets/groceries) 50% Pick up 50%
Cash and 
consignment
25%
Carcass 
(28%)
Traders 40%
Delivered 30%
Cash 100%
10% Grower
Pick up 50%
Markets (public 
markets/groceries) 60% 90% Trader
Both 20%
Meat 
cuts 
(75%)
Markets (public 
markets/groceries) 100%
Delivered 29.63%
Cash 92.59%
3.70% Grower
Pick up 59.26%
88.89
%
Trader
Cash and 
consignment
7.41%
Both 11.11% 7.41% Both
Process
ed 
(2.7%)
Markets (public 
markets/groceries) 100% Pick up 100% Cash 100% 100% Trader
195
Hogs Appendix Table 3. Awareness and Adoption of Specific GAHP Requirements by Hog Farmers 
in Batangas, in percent
Specific GHAP Requirement Aware Currently Adopting Willingness to adopt (for those 
not adopting)
Feed and Nutrition
Feeding standard/ technologies 86 87 63
 Use of prebiotics 86 85 70
 Use of probiotics 64 86 53
Food safety assurance system 94 98 13
 Feed quality control 96 95 14
 Food defense systems 95 97 14
 Use of antibiotics 97 95 47
 Others (vitamins) 57 57 0
Improved Production Technologies
Animal genetics/breed selection 87 54 51
Water for Pigs
Water quality monitoring 87 86 22
Waste management 96 96 13
 with ECC permit 3 3 0
Recording
Production record 96 78 45
Animal Health
Disease management program 95 95 28
 Vaccination 96 97 40
 Presence of veterinarian 92 85 27
Farm Management
Production Operation Manual 79 45 45
Hygiene and sanitation program 99 99 75
Biosecurity measures 96 93 48
 Use of vehicle dip 61 6 15
 Foot bath (farm entrance & all 
buildings) 80 33 44
 Shower 76 21 36
 Downtime 86 85 30
 Use of PPE 93 85 25
Climate mitigation 91 92 0
 Use of tunnel vent 58 7 16
 Other climate adaptation 72 71 1
Animal Welfare
Proper animal handling and restraining 
of animals 96 97 40
Use of tools to minimize stress and 
injury to animals 92 85 27
Animal Transport 
Use of BAI accredited transport vehicles 1 0 1
Sanitation of vehicles 1 2 0
196
Hogs Appendix Table 4. Awareness and Adoption of Specific GAHP Requirements by Hog Traders 
in Batangas
Specific GHAP Requirement Aware Currently 
Adopting
Willingness to adopt (for 
those not adopting)
Recording by traders (n=36) 94 58 25
Proper handling and restraining of animals (n=27) 100 100
use of tools to minimize stress of animals (n=26) 100 92
Use of BAI accredited transport (n=28) 50 43 21
Sanitation of vehicles (n=28) 96 93
Hogs Appendix Table 5. Probit Model for African Swine Fever Management
ASF Management Coefficient Std. Error z P>z
Sex -0.381 0.271 -1.41 0.160
Age -0.003 0.011 -0.25 0.806
No. of Years in School -0.062 0.044 -1.39 0.163
Household Monthly Income .000 0.000 0.82 0.412
Household Size -0.091* 0.047 -1.93 0.054
Type of Breed 0.923** 0.442 2.09 0.037
Good FMR condition -0.490* 0.279 -1.76 0.079
Contractual arrangement 0.799* 0.474 1.69 0.092
Major Market -0.693 0.444 -1.56 0.118
Source market info -0.709 0.580 -1.22 0.222
cons 2.923 1.217 2.40 0.016
**Significant at 5% level; *Significant at 10% level
Hogs Appendix Table 6. Probit Model for Biosecurity Measures
Biosecurity Measures Coefficient Std. Error z P>z
Sex -0.158 0.239 -0.66 0.509
Age 0.029** 0.012 2.43 0.015
No. of Years in School -0.066* 0.041 -1.61 0.107
Household Monthly Income 0.000 0.000 1.41 0.159
Household Size -0.096** 0.045 -2.12 0.034
Sow level 0.033 0.031 1.07 0.283
No. of years in hog industry -0.032** 0.012 -2.74 0.006
Type of breed 0.827* 0.439 1.88 0.060
Membership to Organization -0.380 0.249 -1.53 0.127
Access to extension services 0.250 0.254 0.99 0.324
constant 0.601 0.905 0.66 0.507
**Significant at 5% level; *Significant at 10% level
Hogs Appendix Table 7. Probit Model for GAHP Certification
GAHP Certification Coefficient Std. Error z P>z
Sex 1.764** 0.850 2.08 0.038
Age -0.022 0.019 -1.14 0.253
No. of Years in School 0.045 0.066 0.68 0.496
Household Monthly Income 0.000 0.000 -0.98 0.327
Household Size -0.104 0.119 -0.87 0.385
Sow level -0.101** 0.038 -2.66 0.008
197
Inventory level for Weanling to Finish 0.207* 0.115 1.79 0.073
Distance of Farm to Market 0.012** 0.004 3.38 0.001
Membership to Organization 0.638 0.404 1.58 0.114
Access to agricultural insurance 1.456** 0.504 2.89 0.004
constant -2.878 1.464 -1.97 0.049
**Significant at 5% level; *Significant at 10% level
Hogs Appendix Table 8. Swine Inventory by Region, 2016-2020
Oct 2016 Oct. 2017 Oct. 2018 Oct. 2019 Oct. 2020
PHILIPPINES 12,787,340 13,013,912 13,127,670 13,010,644 11,269,387
CAR 209,218 225,979 251,067 278,174 261,986
Ilocos Region 569,839 587,952 605,174 618,680 465,342
Cagayan Valley 433,839 464,713 471,079 446,607 314,931
Central Luzon 2,304,152 2,285,420 2,296,872 2,206,809 1,082,137
CALABARZON 1,584,517 1,606,244 1,593,545 1,574,047 1,356,854
MIMAROPA 595,219 598,822 565,042 524,348 517,857
Bicol Region 942,223 1,022,670 1,014,967 964,393 880,798
Western Visayas 1,290,996 1,274,439 1,303,060 1,271,228 1,260,108
Central Visayas 1,022,472 1,085,929 1,068,669 1,112,957 1,204,227
Eastern Visayas 370,305 329,131 323,170 302,044 278,168
Zamboanga Peninsula 573,798 576,320 588,108 618,897 634,201
Northern Mindanao 974,344 1,022,269 1,030,361 1,058,769 1,049,098
Davao Region 879,444 893,778 930,592 934,370 898,650
SOCCSKSARGEN 766,754 774,227 808,304 812,742 782,203
Caraga 228,355 223,631 232,711 238,298 225,894
ARMM 41,865 42,388 44,949 48,281 56,933
Source: PSA, 2021
Hogs Appendix Table 9. Volume of Hogs’ Production by Region, 2016-2020 (MT)
REGION 2016 2017 2018 2019 2020
PHILIPPINES 2,231,660 2,265,015 2,319,764 2,296,651 2,142,646
CAR 26,361 25,833 26,655 26,647 25,781
Ilocos Region 86,553 90,065 94,684 94,568 92,223
Cagayan Valley 71,356 72,869 71,805 72,488 68,921
Central Luzon 462,430 447,517 472,552 417,748 322,409
CALABARZON 365,056 371,713 381,590 395,545 348,511
MIMAROPA Region 79,585 83,047 80,840 79,381 79,794
Bicol Region 121,543 126,603 130,063 133,246 119,880
Western Visayas 188,758 186,600 187,105 191,899 195,297
Central Visayas 175,105 192,199 194,472 192,758 192,871
Eastern Visayas 76,390 76,448 77,972 77,522 81,954
Zamboanga Peninsula 80,051 82,199 82,084 82,135 82,950
Northern Mindanao 177,672 188,448 196,623 200,965 210,031
Davao Region 149,157 151,599 154,784 155,894 150,190
198
SOCCSKSARGEN 119,047 117,741 117,291 124,594 122,808
Caraga 42,388 42,188 40,689 40,495 38,491
ARMM 10,208 9,946 10,555 10,767 10,527
Source: PSA, 2021
Hogs Appendix Table 10. Number of National Meat Inspection Services Accredited Meat 
Establishments by Classification and Region
Region No. of accredited 
slaughterhouses
No. of accredited 
meat cutting plant
No. of accredited meat 
distribution centers
AA AAA AA AAA AA
NCR 16 1 39 0 2
CAR 3 0 0 0 1
Ilocos Region 11 0 0 0 7
Cagayan Valley 3 0 0 0 5
Central Luzon 19 0 13 1 2
CALABARZON 27 3 10 6 0
MIMAROPA 2 0 2 0 0
Bicol 4 0 1 0 3
Western Visayas 4 0 2 0 0
Central Visayas 5 1 2 0 0
Eastern Visayas 1 0 1 0 1
Zamboanga 1 0 0 0 0
Northern Mindanao 5 0 3 0 1
Davao 7 2 1 1 0
SOCCSAKSARGEN 5 1 0 0 0
Caraga 4 0 2 0 0
TOTAL 117 8 76 8 22
Source: NMIS, 2021.
Hogs Appendix Table 11. Hogs Inventory in CALABARZON
Region 2016 2017 2018 2019 2020
CALABARZON 1,584,517 1,606,244 1,593,545 1,574,047 1,356,854
Batangas 749,021 751,053 743,403 742,507 618,993
Cavite 137,526 141,319 139,161 146,401 161,592
Laguna 169,865 173,413 158,927 179,499 98,712
Quezon 234,021 235,128 237,554 244,371 226,179
Rizal 294,084 305,331 314,500 261,269 251,378
Source: PSA 2021
199
Hogs Appendix Figure 1. Hog Inventory by Farm Type, 2020
 Source of basic data: PSA, 2021.
Hogs Appendix Figure 2. Hog Inventory by Type of Farm, by Region
Source of basic data: PSA, 2021.
Backyard
62%
Commercial
38%
Backyard Commercial
0
200000
400000
600000
800000
1000000
1200000
1400000
1600000
1800000
2000000
2019 BACKYARD 2019 COMMERCIAL 2020 BACKYARD 2020 COMMERCIAL
200
Hogs Appendix Figure 3. Farm Gate Price of Hogs, 2019 and 2020 (P/kg liveweight)
Source of basic data: PSA, 2021.
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
160.00
180.00
2019 2020
201
Chicken Appendices 
Chicken Appendix 1. Overview of the Chicken Industry
The chicken industry has been a consistent leader of the country’s agriculture sector. Chicken inventory has 
steadily increased from 175 million birds in 2016 to 186 million in 2020 (Chicken Appendix Table 11). About half of 
the industry is in the five largest producing regions, namely Central Luzon (15%), CALABARZON (13%), Northern 
Mindanao (12%), Western Visayas (10%), and Central Visayas (11%). The industry raises three types of chickens, 
the dominant being the native and improved variety making up 45% of total inventory, followed by broilers (33%), 
and layers (22%) (Chicken Appendix Figure 1).
By major producing regions, Central Luzon and Northern Mindanao raise mostly chicken for meat. Respectively, 
their broilers are 49% and 42% of their poultry. CALABARZON, in contrast, grow layers, which is 62% of its poultry 
inventory (Chicken Appendix Figure 2). Improved native chicken varieties are mostly found in Western Visayas and 
Central Visayas, respectively making up 62% and 48% of their poultry production. The volume of chicken 
production has also steadily increased, from 1.67 million MT in 2016 to 1.81 million in MT in 2020 (Chicken 
Appendix Table 12). Top in the list is Central Luzon which contributed 35% to total output in 2020, followed by 
CALABARZON with nearly 18% in 2020. Northern Mindanao and Western and Central Visayas came with output 
shares of 9% and 6%, respectively.
There are 147 poultry dressing plants that are accredited by NMIS, as of December 2021 (Chicken Appendix Table 
13). Majority are classified as AA, while the rest are certified as AAA plants. Most of these facilities are found in 
Luzon, 27 plants in Central Luzon and 18 in CALABARZON. In Mindanao, majority of the facilities are in Northern 
Mindanao (16) and Davao (12), while Western and Central Visayas host 14 and 12 facilities, respectively. Farmgate 
prices of broilers had been relatively volatile (Chicken Annex Figure 3). Prices in 2018 exceeded those in 2019 and 
2020, particularly in the months of January through August, but were lowest in December. The highest observed 
farmgate price was PhP98/kg live weight in October. Farmgate prices in 2020 fluctuated, reaching their bottom at 
PhP61/kg live weight in October, and spiking to reach their highest of PhP93/kg in December. Retail prices 
exhibited hardly any trend, their level stuck in the band from PhP122 to PhP138/kg, with monthly variation not 
exceeding P10/kg. 
Batangas Provincial Profile 
Batangas holds more than half of the chicken inventory in CALABARZON from 2016-2020 (Chicken Appendix Table 
14). Although the region’s inventory had generally fluctuated in this period, a positive growth of provincial chicken 
output was observed. In 2020, the province holds 14.3M birds, 11 M of which are layers (Chicken Appendix Table 
15). Broilers were only 23% of the provincial chicken inventory. 
Batangas is a first-class province. With its total area of 316,581 hectares, the province has the second largest 
international seaport of the country in Batangas City. Its capital has been classified as a Regional Growth Center 
and Regional Agro-Industrial Center for Special Economic Zone (City Government of Batangas, n.d). 
Thirty-four municipalities and 1,078 barangays make up the province. Based on the 2015 census, the population 
was 2,694,335 individuals, growing per year at the rate of 2.41% from 2010 to 2015. In 2020, the population was 
projected to increase to 2,981,736, its growth significantly attributed to the migration into the province from the 
rest of the country.
Batangas can be a poster province for economic growth. As of May 2015, it hosted 18 operating economic zones 
and industrial parks and 849 business enterprises. The livestock industry, largely poultry and hogs, has marked 
imprint on the provincial economy. Sixty-five (65) of businesses are feed mills, four (4) are slaughterhouses, and 
four (4) poultry dressing plants, all accredited by NMIS. The industry complements other vibrant sectors of the 
202
economy like manufacturing and tourism. The province offers 34 famous tourism sites and boasts of 3,696,343 
arrivals of local and foreign visitors in 2015.
Crops, livestock, poultry, and fisheries play a significant role in the province’s agriculture. Major crops include rice, 
coconut, sugarcane, fruit, corn, vegetables, root crops, and coffee. Sugarcane tops agricultural output at 1.07 
million MT, but comes only second to … in terms of the harvested land area (24,290 ha) (Chicken Appendix Table 
16). 
Aside from producing various crops, Batangas is a suitable location for backyard and commercial type of animal 
farms. The PSA (2021) recorded six major farm animals raised in the province, namely chicken, swine, cattle, goat, 
duck and carabao (Chicken Appendix Table 17). As of July 2020, chicken tops its commercial animal herd with 15 
million heads, followed by swine, cattle and goat.
The fishery sector in the province is classified as commercial, municipal and aquaculture in nature. Among these, 
aquaculture has the highest contribution in terms of volume (54,354 MT) and value (PhP7.20 million) (Chicken 
Appendix Table 18). Sales from acquaculture make up at least 80% of the province’s total fishery production 
The province has a high literacy rate of 96.5%, considered among the highest in the country. Scholarships and 
improvement of school facilities are part of the program for education. Increasing job opportunities, allocating 
funds for the cooperatives and livelihood, construction of food terminal, and other activities were set to improve 
the livelihood sector of the province. Ensuring safety and security of the people, properties and its environment is 
pursued by the government through the program.
203
Chicken Appendix 2. Chicken Broiler Probit Models
Probit models are used to explore the factors affecting significantly the decision of producers to adopt a given 
improved technology or management practice. The model is formulated and estimated using the data from the 
survey conducted in this baseline study. The general form of the model is 𝑌𝑖 = 𝐴 +∝
𝒕 𝑿𝑖 +∈𝑖 where 𝑌𝑖
is a binary 
variable with values of 0 and 1, representing the adoption decision of producer i. 𝑿𝑖
is a vector of explanatory 
variables attributable to producer I, while ∝ is a vector of same dimension representing the coefficients of each of 
the explanatory variable in 𝑿. 𝐴 and ∈𝑖 are respectively the constant and error terms, respectively of the probit 
model. 
For the chicken broiler producers, the model specified in this study is the following:
𝑌𝑖𝑗 = 𝐴𝑗 + ∑ 𝛼𝑘𝑆𝐸𝐷𝐶𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑆𝐸𝐷𝐶
+ ∑ 𝛽𝑘𝐹𝐴𝑅𝑀𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐹𝐴𝑅𝑀
+
∑ 𝜇𝑘𝑀𝑘𝑖 + ∑ 𝛿𝑘𝐼𝑁𝑆𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑀 ∀ 𝑘 𝑖𝑛 𝐼𝑁𝑆
+ ∑ 𝛾𝑘𝐼𝑁𝐹𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐼𝑁𝐹
+ 𝜀𝑖𝑖
𝑌𝑖𝑗 is 1 if respondent i adopts technology/practice j,
J=1 is Avian Influenza Management; j=2 is Biosecurity; j=3 is GHP Certification, j=4 is Cold Chain, j=5 is Dressing 
plant; j=6 is Cutting Plant, j=7 is ISO Certification, j=8 is HACCP Certification
𝑺𝑬𝑫𝑪𝒌𝒊 is the vector of socio-economic demographic cultural variables attributable to producer i and used to 
explain the adoption decision j of producer I, where k=1 is education; k=2 is age; k=3 is ethnicity, k=4 is gender, 
k=5 is household income, k=6 is non-farm income; and k=7 is household size.
𝑭𝑨𝑹𝑴𝒌𝒊 is the vector of farm characteristics attributable to producer i and used to explain the adoption decision j 
of producer i, where k=1 is flock level; k=2 is farm ownership (e.g. sole proprietorship, partnership, etc.) ; k=3 is 
Integrator; k=4 is number of years in business; k=5 is distance from main market; k=6 is Breed type (e.g. native or 
commercial breed)
𝑴𝒌𝒊 is the vector of market-related variables attributable to producer I and used to explain the adoption decision j 
of producer I, where k=1 is premium price for quality; k=2 is major market (e.g. trader, consolidator, processor); 
k=3 is source of market information.
𝑰𝑵𝑺𝒌𝒊 is the vector of institutional variables attributable to producer i and used to explain the adoption decision j 
of producer I, where k=1 is membership in organization; k=2 is access to extension service; k=3 is availability of 
technology in the area; k=4 is contractual arrangements; k=5 is access to credit; k=6 is access to livestock 
insurance; k=7 is beneficiary of government program; and k=8 is financial inclusion.
𝑰𝑵𝑭𝒌𝒊 is the vector of infrastructural variables attributable to producer i and used to explain the adoption decision 
j of producer i, where k=1 is access to farm to market roads; k=2 is road condition; k=3 is access to the internet; 
.k=4 is trucking services; k=5 is access to slaughterhouse; and k=6 is access to dressing plant.
𝐴𝑗
, 𝜀𝑖𝑖 are respectively the constant and error terms of the model.
𝛼𝑘, 𝛽𝑘,𝜇𝑘, 𝛿𝑘 and 𝛾𝑘 are the vectors of coefficients for each of the variable k in vectors SEDC, FARM, M, INS, and 
INF respectively.
204
Chicken Appendix Table 1. Details of Animal Genetics of Broiler Raisers in Batangas
Details % Details % Details %
Breed/strain of day-old chick 
used Source of day-old chick Issues on quality of day-old chicks
45 days (cobbs) 88.54% Registered Hatchery 82.81% Small 33.61%
30 to 35 days 3.13% Own Farm/Hatchery 3.13% Crippled 19.33%
Class A 2.08% Other sources 14.06% Lame 14.29%
Contract 
Growers 6.25% Cough/other disease 10.08%
Other sources Mortality 6.72%
Poultry/vet supply shop 50.00% Lightweight 5.88%
Agent/viajero 30.77% Not uniform in size 3.36%
Integrator 19.23% Diarrhea 2.52%
With physical 
deformities 5.00%
Chicken Appendix Table 2. Trading by Broiler Producers
Volume traded by producers: 105,946 MT
Product Form Sold to Mode of Delivery Mode of Payment
Live
Chicken 83.8%
Direct Consumers
Processors
Contract grower
Public Markets
Traders/haulers
33.33%
24.59%
20.77%
12.57%
8.74%
Delivery
Pick-up
Both
17.14%
50.71%
32.15%
Cash
Check
Consignment
Installment
Credit
97.14%
3.57%
2.14%
4.29%
5%
Dressed
Chicken 16.2%
Public Markets
Traders
85.19%
14.81%
Delivery
Pick-up
Both
37%
25.92%
37.04%
Cash
Installment
96.3%
3.7%
Chicken Appendix Table 3. Trading by Broiler Traders
 Volume traded by traders: 542,104 MT
Product Form Sold to Mode of Delivery Mode of 
Payment
Who determines 
the price
Live
Chicken 17.07%
Processors
Public markets
66.67%
33.33%
Delivered
Pick-up
Both
14.29%
57.14%
28.57%
Cash 100%
Trader
Grower
Both
76.47%
14.71%
8.82%
Dressed
Chicken 82.93%
Traders
Public markets
5.88%
94.12%
Delivered
Pick-up
Both
26.47%
67.65%
5.88%
Cash
Credit
91.89%
8.11%
Trader 
Grower
Both
14.29%
42.86%
42.86%
Chicken Appendix Table 4. SPS Issues in Bringing Day-Old Chicks into the Farm and 
Corresponding Solutions
SPS Issues Percent Solution Percent
Crippled 39.13 Throw away/cull 47.8
Mortality 26.09 Antibiotics 26.1
Diarrhea 17.39 Isolate 15.2
205
Chicken Appendix Table 5. Risk Factors in Broiler Production
Risk factors No. reporting (n=192) Percent
Feed Adulteration 24 12.57%
Avian Flu 33 17.19%
Others:
Cough/Colds 57 67.86%
Wheezing 7 8.33%
Heat Stroke 6 7.14%
Chronic Respiratory Disease 3 3.57%
Diarrhea 3 3.57%
Lame 2 2.38%
Small eyes 2 2.38%
New Cancer Disease 1 1.19%
Bacterial Infection 1 1.19%
Stunted growth 1 1.19%
High Blood 1 1.19%
Earthquake 19 9.90%
Landslide 1 0.52%
Typhoon/Flood 58 30.21%
Labor Dispute 1 0.52%
Others:
Taal Volcano eruption 2 40.00%
Increase in the price of production inputs (chick) 1 20.00%
Lack of support from the government 1 20.00%
Price instability 1 20.00%
Chicken Appendix Table 6. Awareness and Adoption of Specific GAHP Requirements by Broiler 
Farmers in Batangas, in percent
Specific GAHP Requirement Aware Currently Adopting Willingness to adopt (for 
those not adopting)
Feed and Nutrition
Feeding standard/ technologies 81.25 73.44 92.16
 Use of prebiotics 53.65 45.83 82.69
 Use of probiotics 53.13 46.88 80.39
Food safety assurance system 88.54 85.42 100.00
 Feed quality control 86.46 84.90 100.00
 Food defense systems 77.60 76.04 93.75
 Use of antibiotics 92.19 82.29 80.00
 Others (vitamins at) 1.04 1.04 0.00
Improved Production Technologies
Animal genetics/breed selection 67.71 45.31 74.29
Water for Broiler
Water quality monitoring 87.50 84.90 93.10
Waste management 79.17 70.31 77.97
 with ECC permit 18 18 -
Recording
Sick 13.04 Cleaning/showering 10.9
Stunted growth 4.35
206
Specific GAHP Requirement Aware Currently Adopting Willingness to adopt (for 
those not adopting)
Production record 86.46 75.00 81.25
Animal Health
Disease management program 76.69 72.40 96.23
 Avian influenza management 60.42 38.54 88.98
 Vaccination 74.48 48.44 72.73
 Presence of veterinarian 71.35 49.48 59.79
Farm Management
Production Operation Manual 58.85 32.29 77.69
Hygiene and sanitation program 82.29 77.60 83.72
Biosecurity measures 82.81 79.69 92.31
 Use of vehicle dip 51.04 25.00 43.75
 Foot bath (farm entrance & all buildings)
 Shower 51.56 32.29 46.92
 Downtime 56.77 28.13 55.40
 Use of PPE 67.71 39.58 46.55
Climate mitigation 84.90 81.25 86.11
 Use of tunnel vent 47.40 20.31 50.32
 Other climate adaptation 100.00 100.00 100.00
Animal Welfare
Animal Transport 
Sanitation of vehicles 19.61 4.58 41.78
Chicken Appendix Table 7. Awareness and Adoption of Specific GAHP Requirements by Broiler 
Traders in Batangas
Specific GAHP Requirement Aware Currently 
adopting
Willingness to adopt
(for those not adopting)
Recording by traders (n=16) 100.00 68.75 80.00
Animal welfare (n=16) 75.00 62.5 100.00
Use of animal crates (n=16) 87.5 68.75 60.00
Use of BAI accredited transport (n=16) 43.75 18.75 76.92
Sanitation of vehicles (n=15) 100.00 85.71 100.00
Chicken Appendix Table 8. Probit Model for Avian Influenza Management
Avian Flu Management Coefficient Std. Error z P>z
Sex 0.191 0.228 0.840 0.402
Age -0.006 0.010 -0.570 0.570
No. of years in school -0.002 0.045 -0.040 0.969
Household monthly income 0.000 0.000 1.570 0.117
Household size -0.009 0.058 -0.160 0.873
Distance of farm to market 0.039** 0.017 2.370 0.018
Major market 1.142** 0.247 4.630 0.000
Access to extension services 0.794** 0.275 2.890 0.004
Access to credit 0.386* 0.226 1.710 0.087
Access to agricultural insurance 1.022** 0.470 2.170 0.030
cons -1.271 0.811 -1.570 0.117
**Significant at 5% level; *Significant at 10% level
207
Chicken Appendix Table 9. Probit Model for Biosecurity Measures
Biosecurity measures Coefficient Std. Error z P>z
Sex -0.036 0.248 -0.140 0.886
Age -0.010 0.011 -0.900 0.369
No. of years in school 0.089* 0.050 1.780 0.076
Household monthly income 0.000** 0.000 2.400 0.016
Household size 0.002 0.065 0.030 0.973
Contractual arrangement -0.897* 0.460 -1.950 0.051
Access to credit 0.740** 0.285 2.590 0.009
Access to extension services 0.501 0.338 1.480 0.139
Distance of farm to market 0.013 0.020 0.670 0.504
FMR condition -0.238 0.265 -0.900 0.370
cons 0.481 0.893 0.540 0.590
**Significant at 5% level; *Significant at 10% level
Chicken Appendix Table 10. Probit Model for GAHP Certification
GAHP Certification Coefficient Std. 
Error z P>z
Sex 0.041 0.387 0.110 0.916
Age -0.018 0.014 -1.330 0.183
No. of years in school 0.008 0.056 0.140 0.889
Household monthly income 0.000 0.000 -1.490 0.136
Household size -0.012 0.086 -0.130 0.893
Ethnicity -1.462** 0.516 -2.840 0.005
Years in chicken industry 0.050** 0.023 2.150 0.031
Access to credit -0.797** 0.393 -2.030 0.043
Access to agricultural insurance 1.562** 0.394 3.970 0.000
FMR condition -0.522* 0.324 -1.610 0.108
cons 0.910 1.186 0.770 0.443
**Significant at 5% level; *Significant at 10% level
Chicken Appendix Table 11. Chicken Inventory by Region, 2016-2020
REGION 2016 2017 2018 2019 2020
PHILIPPINES 175,358,349 181,792,452 194,688,840 192,802,612 186,331,913
CAR 1,497,279 1,627,326 1,709,387 1,749,289 1,759,904
Ilocos Region 8,449,085 9,532,432 9,816,192 10,141,227 10,898,138
Cagayan Valley 6,590,500 6,693,675 7,140,813 6,742,849 6,819,278
Central Luzon 28,927,347 28,150,343 38,086,964 35,399,462 28,203,395
CALABARZON 26,951,303 27,887,178 26,583,650 27,241,118 24,186,253
MIMAROPA Region 4,358,163 4,479,362 4,661,519 4,429,348 4,230,521
Bicol Region 10,159,151 10,618,500 10,021,510 9,441,799 9,378,232
Western Visayas 19,840,890 20,066,771 19,780,328 18,886,094 19,857,117
Central Visayas 14,444,654 14,586,503 16,334,785 19,421,310 20,967,843
Eastern Visayas 2,938,827 3,365,703 3,268,844 2,960,007 3,186,046
Zamboanga Peninsula 6,466,543 6,465,559 8,288,883 7,413,435 8,327,214
Northern Mindanao 20,972,791 22,340,271 22,927,439 23,528,236 23,512,591
Davao Region 11,654,729 12,086,104 11,608,307 11,157,281 10,522,579
208
REGION 2016 2017 2018 2019 2020
SOCCSKSARGEN 8,207,139 10,086,040 10,296,172 9,962,673 10,328,183
Caraga 2,164,051 2,094,397 2,460,845 2,410,687 2,361,794
ARMM 1,735,897 1,712,288 1,703,202 1,917,797 1,792,825
Source: PSA, 2021
Chicken Appendix Table 12. Volume of Chicken Production, by Region 2016-2020 (MT)
REGION 2016 2017 2018 2019 2020
PHILIPPINES 1,674,504.59 1,745,888.43 1,836,663.60 1,927,413.97 1,809,852.55
CAR 7,601.70 7,924.37 7,277.52 6,621.97 6,136.17
Ilocos Region 78,759.99 78,079.38 84,932.89 84,230.56 84,534.68
Cagayan Valley 60,644.04 58,777.35 57,893.71 55,371.63 53,692.64
Central Luzon 590,992.50 624,686.33 658,909.35 699,655.40 635,384.37
CALABARZON 328,429.85 328,645.74 330,940.14 343,264.69 317,186.18
MIMAROPA Region 10,300.72 10,154.41 10,867.74 11,173.62 10,905.00
Bicol Region 42,240.73 43,967.27 47,177.55 54,884.12 46,287.59
Western Visayas 95,834.77 103,817.82 110,011.54 117,438.62 117,019.37
Central Visayas 99,742.96 104,845.20 115,114.18 118,627.83 108,704.57
Eastern Visayas 36,293.82 49,319.44 55,000.24 62,321.68 56,587.80
Zamboanga Peninsula 30,203.51 31,986.25 34,236.37 36,476.01 35,847.67
Northern Mindanao 152,801.50 159,085.55 164,672.34 170,020.52 170,931.62
Davao Region 72,007.20 71,758.06 76,341.31 81,089.70 74,380.04
SOCCSKSARGEN 49,843.88 53,402.53 61,915.98 65,563.46 71,208.93
Caraga 13,864.19 14,590.80 16,276.63 15,513.40 15,411.55
ARMM 4,943.22 4,847.93 5,096.13 5,160.77 5,634.38
Source: PSA, 2020 
Chicken Appendix Table 13. Number of National Meat Inspection Services Accredited Poultry 
Dressing Plants, by Region
REGION AA AAA
CAR 1 -
Ilocos Region 12 2
Cagayan Valley 5 1
Central Luzon 22 15
CALABARZON 7 11
MIMAROPA Region 2 -
Bicol Region 7 1
Western Visayas 14 -
Central Visayas 14 2
Eastern Visayas 7 2
Zamboanga Peninsula 6 -
Northern Mindanao 13 3
Davao Region 8 4
SOCCSKSARGEN 5 -
Caraga 2 -
ARMM 1 -
Total 126 41
Source: NMIS
209
Chicken Appendix Table 14. Chicken Inventory in CALABARZON
2016 2017 2018 2019 2020
CALABARZON 26,951,303 27,887,178 26,583,650 27,241,118 24,186,253
 Batangas 13,183,781 13,151,796 13,618,916 14,091,114 14,315,306
 Cavite 2,248,070 2,050,302 2,061,526 1,909,791 1,799,613
 Laguna 2,597,362 3,323,847 2,393,087 3,042,974 1,346,135
 Quezon 4,849,381 5,029,906 4,830,374 4,841,494 3,808,393
 Rizal 4,072,709 4,331,327 3,679,747 3,355,745 2,916,806
Source: PSA, 2021
Chicken Appendix Table 15. Chicken Inventory by Type of Farm, CALABARZON, 2020
TOTAL Broiler Layer Native/Improved
CALABARZON 24,186,253 6,970,236 14,746,753 2,469,264
 Batangas 14,315,306 1,690,550 11,847,500 777,256
 Cavite 1,799,613 1,174,432 500,357 124,824
 Laguna 1,346,135 1,015,536 290,118 40,481
 Quezon 3,808,393 1,935,412 378,778 1,494,203
 Rizal 2,916,806 1,154,306 1,730,000 32,500
Source: PSA, 2021
Chicken Appendix Table 16. Major Crops, by Area and Production, Batangas, 2019
Commodity Area (ha) Production (MT)
Coconut 36,305 100,709
Sugarcane 24,290 1,075,726
Mango 10,820 36,463
Rice 8,627 33,001
Banana 5,530 40,919
Coffee 3,752 489
Vegetables 3,623 31,349
Corn 3,273 10,456
Rootcrops 1,064 16,335
Note: Data used for rice and corn were from year 2020
Source: PSA, 2021
Chicken Appendix Table 17. Animal Inventory by Type of Farm in Batangas, July 2020
Animal Type of Farm Number of head
Carabao TOTAL 46,980
Backyard 46,980
Commercial -
Cattle TOTAL 125,825
Backyard 125,825
Commercial 3,198
Goat TOTAL 122,700
Backyard 122,358
Commercial 342
210
Swine TOTAL 749,658
Backyard 160,890
Commercial 588,768
Chicken TOTAL 15,069,529
Broiler 2,085,232
Layer 11,706,797
Native/Improved 1,277,500
Ducks TOTAL 13,000
Backyard 13,000
Commercial -
Source: PSA, 2021
Chicken Appendix Table 18. Volume and Value of Fisheries in Batangas, by type, 2020
Type Volume (MT) Value (PhP)
Commercial Fisheries 3,741 445,942
Municipal Fisheries 7,762 815,325
Aquaculture 54,354 5,948,377
TOTAL 65,857 7,209,646
Source: PSA, 2021
Chicken Appendix Figure 1. Chicken Inventory by type of farm, Philippines
Broiler 
33%
Layer 
22%
Native/Improved 
45%
 Broiler Layer Native/Improved
211
Chicken Appendix Figure 2. Chicken Inventory by type of farm by region, 2020
Chicken Appendix Figure 3. Farmgate price of broilers, P/kg, 2018-2020
Source of basic data: PSA 2021
0.00
20.00
40.00
60.00
80.00
100.00
120.00
2018 2019 2020
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
CAR
Ilocos Region
Cagayan Valley
Central Luzon
CALABARZON
MIMAROPA Region
Bicol Region
Western Visayas
Central Visayas
Eastern Visayas
Zamboanga Peninsula
Northern Mindanao
Davao Region
SOCCSKSARGEN
Caraga
 ARMM
 Broiler Layer Native/Improved
212
Milkfish Appendices 
Milkfish Appendix 1. Overview of the Milkfish Industry
The Philippines is one the world’s top commercial producers of Milkfish (Francisco, 2020). Together with Indonesia, 
it accounts for about 95% of the world’s supply of the commodity 
The top producing regions and provinces are Ilocos Regions (Pangasinan), Western Visayas (Capiz and Negros 
Occidental), Central Luzon (Bulacan and Pampanga), and CALABARZON (Laguna). On the average, Ilocos Region 
contributed nearly 27% to total yearly output from 2011 to 2019; Western Visayas, 21%; Central Luzon, 16%; and 
CALARZON, 14% (Milkfish Appendix Figure 1). Annual quantity and value of production in the last ten years are 
presented in Milkfish Appendix Table 13.
Pangasinan is the country’s top milkfish producer. Agriculture-based production is the major source of income of 
majority of its 2.96 million population, with aquaculture being the major income source for households near the 
coastal and places with brackish water source. Favored species being cultured are milkfish, Malaga and prawns. 
Recent available data indicates that the province produced 105,700 mt of milkfish in 2019. Its capital city, Dagupan, 
is known as the “Bangus Capital of the World” being the central of business hub for milkfish in fresh and various 
processed forms. 
The province has a total of 11,200 ha of brackish water fish ponds. About 90-95% of fishpond operators are 
milkfish growers (i.e, fingerlings to marketable size) while 5-10 % are into culture of milkfish fry to fingerlings. Of its 
44 municipalities/cities, 17 have milkfish ponds and 6 have fish cages. BFAR maintains a registry of all milkfish 
farms both fishponds and fish cages.
Milkfish Processors and Product Lines
There are two huge processing plants in Pangasinan: (1) Korea-Philippines Seafood Processing Complex in 
Dagupan; and (2) Anjo Farms in San Fabian. Both plants are accredited under the Hazard Analysis Critical Control 
Point (HACCP) as well as by the European Union for the sanitary standards set on imported food products. HACCP 
is a systematic preventive approach to food safety, which is a requirement of every importing country.
ANJO FARMS, INC.
Anjo Farms Incorporated primarily deals with seafood processing, shrimp paste production, and milkfish 
processing. It exports sme of its products to foreign markets in Europe, Asia and the Middle East.
It claims to be the first and only Kosher-certified Bangus processing plant in the Philippines. It is a HALAL certified 
company. All of its fish products come from Bonuanbangus grown in Pangasinan
213
Milkfish Product Lines
Bangus (MilkFish) Sisig
Bangus Prime Belly (Barbecue)
Bangus Prime Belly (Teriaki)
Bangus Prime Belly (adobo)
Bangus Prime Belly (Curry)
Product Description
-Fresh Frozen Minced Prime Belly Cuts (400g net) 
-Convenient and Ready to Eat (Microwaveable) 
-NO Transfat; NO Preservatives; NO msg
-E.U. Accredited 
-HACCP Certified 
-HALAL Certified 
-KOSHER Certified 
KPSPC-Korea Philippines Seafood Processing Complex
The complex was built on a 1,500-square meter lot owned by the city government in Barangay BonuanBinloc 
through a USD 2.2M grant from the Korean International Cooperation Agency (KOICA)
Then Director of the BFAR-NIFTDC, Dr. Westly Rosario, said that this state-of-the-art triple-A standard processing 
facility completes the major facilities needed to ensure the expanding but sustainable bangus industry in Dagupan 
and Pangasinan.
Main product is deboned milkfish. Daily target production is 3000 pcs or 1.2 tons. Manpower requirement for 
fulltime operation is 80 (recently reduced to 40 due to the pandemic situation)
214
One of the small-scale processing plants later established in the region was the BinmaleyFisherfolk Association￾operated plant from Binmaley (the first recipient of the provincial government’s fish processing livelihood project).
The BinmaleyRural Improvement Club (BRIC) was a recipient of the Department of Trade and Industry’s Shared 
Service Facilities (SSF) Program for MSMEs: PHP 1 million worth of equipment (Food-grade stainless steel smoking 
chamber, stainless tables, double-chamber vacuum packaging machine, chest freezer, industrial pressure cooker, 
tools) 
Monthly average capacity was 3,000 to 10,000 kg (later increased to 18,000 kg) of fresh milkfish.
Milkfish Appendix 2. Milkfish Probit Models
Probit models are used to explore the factors affecting significantly the decision of producers to adopt a given 
improved technology or management practice. The model is formulated and estimated using the data from the 
survey conducted in this baseline study. The general form of the model is 𝑌𝑖 = 𝐴 +∝
𝒕 𝑿𝑖 +∈𝑖 where 𝑌𝑖
is a binary 
variable with values of 0 and 1, representing the adoption decision of producer i. 𝑿𝑖
is a vector of explanatory 
variables attributable to producer I, while ∝ is a vector of same dimension representing the coefficients of each of 
the explanatory variable in 𝑿. 𝐴 and ∈𝑖 are respectively the constant and error terms, respectively of the probit 
model. 
For the milkfish producers, the model specified in this study is the following:
𝑌𝑖𝑗 = 𝐴𝑗 + ∑ 𝛼𝑘𝑆𝐸𝐷𝐶𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑆𝐸𝐷𝐶
+ ∑ 𝛽𝑘𝐹𝐴𝑅𝑀𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐹𝐴𝑅𝑀
+
∑ 𝜇𝑘𝑀𝑘𝑖 + ∑ 𝛿𝑘𝐼𝑁𝑆𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑀 ∀ 𝑘 𝑖𝑛 𝐼𝑁𝑆
+ ∑ 𝛾𝑘𝐼𝑁𝐹𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐼𝑁𝐹
+ 𝜀𝑖𝑖
𝑌𝑖𝑗 is 1 if respondent i adopts technology/practice j,
j=1 is management of fish diseases; j=2 is bio-security; j=3 is good aquaculture practices certification; j=4 is cold 
chain; j=5 is deboning plant; j=6 is harvest and postharvest technology; j=7 ISO Certification;j=8 HACCP 
Certification; and J=9 is Improved Fingerling/Nursery Mgt.
215
𝑭𝑨𝑹𝑴𝒌𝒊 is the vector of farm characteristics attributable to producer i and used to explain the adoption decision j 
of producer i, where k=1 is farm size/stocking level; k=2 is farm ownership (e.g. sole proprietorship, partnership, 
etc.) ; k=3 is Integrator; k=4 is number of years in business; k=5 is distance from main market; k=6 is Breed type 
(e.g. native or commercial breed)
𝑭𝑨𝑹𝑴𝒌𝒊 is the vector of farm characteristics attributable to producer i and used to explain the adoption decision j 
of producer i, where k=1 is Farm size/stocking level;k=2 is Farm ownership (e.g. sole proprietorship, partnership, 
etc); k=3 is Integrator; k=4 is number of years in business; k=5 is distance from main market; k=6 is Farm type (e.g. 
hatchery/nursery, grow-out); k=7 is culture type (e.g. intensive, extensive); stocking density
𝑴𝒌𝒊 is the vector of market-related variables attributable to producer I and used to explain the adoption decision j 
of producer I, where k=1 is premium price for quality; k=2 is major market (e.g. trader, consolidator, processor); 
k=3 is source of market information.
𝑰𝑵𝑺𝒌𝒊 is the vector of institutional variables attributable to producer i and used to explain the adoption decision j 
of producer I, where k=1 is membership in organization; k=2 is access to extension service; k=3 is availability of 
technology in the area; k=4 is contractual arrangements; k=5 is access to credit; k=6 is access to livestock 
insurance; k=7 is beneficiary of government program; and k=8 is financial inclusion.
𝑰𝑵𝑭𝒌𝒊 is the vector of infrastructural variables attributable to producer i and used to explain the adoption decision 
j of producer i, where k=1 is access to farm to market roads; k=2 is road condition; k=3 is access to the internet; 
.k=4 is trucking services; k=5 is access to ice plant; and k=6 is access to cold chain facility.
𝐴𝑗
, 𝜀𝑖𝑖 are respectively the constant and error terms of the model.
𝛼𝑘, 𝛽𝑘,𝜇𝑘, 𝛿𝑘 and 𝛾𝑘 are the vectors of coefficients for each of the variable k in vectors SEDC, FARM, M, INS, and 
INF respectively.
Milkfish Appendix Table 1. Fry source
Number Percent
Source of Fry (n = 233)
Imported 42
Local 190
Both 1
Origin of Fry (n = 233)
Hatchery 152
Wild/fry gatherer 81
Note: 67 are using fingerlings instead of fry
216
Milkfish Appendix Table 2. Access to support services
Number Percent
Attended training on productivity improvement
Yes 36 12
No 264 88
Type of training
 Fishpond management 12
Pond preparation 2
Fish processing 2
Fishpond facilities 1
Fingerling management 5
Feed management 11
Milkfish 
production 3
Training on food 
safety
Yes 12 4
No 288 96
Type of training
Deboning 1
Feed nutrient 2
Pond management 1
Food safety 7
About HACCP 1
Access to extension services
Yes 94 31
No 206 69
Access to credit
Yes 71 24
No 229 76
Sources of credit
Formal 13
Informal 50
Both 8
Milkfish Appendix Table 3. Current Acclimatization Practice and Adoption of Improve Technology
Number Percent
217
Current Practice (n=300)
Partially Adjusting Fry to the Water in 
pond to adapt 69 23.0 
Manual Observation And Checking 62 20.7 
Estimate water salinity and temperature 32 10.7 
Manual Monitoring/inspection 46 15.3 
Manual Checking Of Temperatures 23 7.7 
Get water sample to test/ taste 18 6.0 
Partially submerging fry to the pond water 15 5.0 
Monitored by BFAR 12 4.0 
Cultural Method 11 3.7 
Proper Application of Salinity Test 11 3.7 
Partially Adjusting Fry to the Water in 
pond to adapt 9 3.0 
Monitor using Refractometer 1 0.3 
Willing to adopt
Yes 257 85.7 
No 43 14.3 
Reasons for adopting (n=257)
For Better Production 93 36.2 
For high survival rate 85 33.1 
Used to Old Ways 29 11.3 
improve production 21 8.2 
To Expand Knowledge/improve practice 20 7.8 
To monitor the water parameters 11 4.3 
Convenience 9 3.5 
For high survival of fry/fingerlings 5 1.9 
To know the water situation 4 1.6 
Milkfish Appendix Table 4. Survival Rate of Fry to Fingerling, by source
Hatchery Wild
Survival rate Imported Local All Sources
n = 41 n = 94 n=50 n = 185
20-30 2.4 9.6 6 7.0 
40-50 48.8 52.1 14 41.1 
60-70 12.2 19.1 32 21.1 
80-90 31.7 52 21.1 
> 90 2 0.5 
Average 63 67 69 67.0 
218
Milkfish Appendix Table 5. Adoption of Good Aquaculture Practices
Item
Aware of the 
Practice
Rate of Adoption 
among those who 
are aware
Percent Reporting
Pond preparation 96.0 82.0
Tilling and soil conditioning 74.0 72.0
Liming 52.3 100.0
Fertilization 64.5 100.0
Natural food production 72.0 79.0
Pest/Predator control/Eradication 70.0 91.9
Flushing 51.7 77.4
Water level 68.7 70.9
Water quality 37.3 73.2
Use of other inputs (probiotics. Rice bran) 30.3 48.4
Water management 
Tidal 48.7 77.4
Use of pumps 57.3 80.8
Presence of drainage canal 
Central canal 36.7 60.0
Peripheral canal 36.0 73.1
Aeration 20.0 38.3
Effluent discharge 
Physicochemical parameter 
Ammonia buildup 11.7 11.4
Dissolved oxygen 30.3 39.6
Temperature 23.7 57.7
Presence of predators 64.7 61.3
Disease symptoms 36.7 69.1
Harvesting Flushing 100.0 36.0
Total drainage 100.0 23.0
Gill net 100.0 35.0
Fish corral 100.0 6.0
Post harvest handling 14.0 42.9
219
Milkfish Appendix Table 6. Problems on water quality and low fry survival rate
Number Percent
Poor brackish water quality
Yes 186 62
No 114 38
Mitigating measure
Drain and change pond water by flushing 59 34.1 
Use Proper Water Management And Sanitation 28 16.2 
Use water pump 19 11.0 
Proper Water Management 17 9.8 
Check the dikes and screen to ensure entry of good quality water 16 9.2 
By Letting It Flow 14 8.1 
Wait for rainfall 5 2.9 
Pre-Harvest 4 2.3 
Nothing 4 2.3 
Monitor/Observe the water quality by tasting and smelling 7 4.1 
Low survival rate of fry
Yes 185 61.7 
No 115 38.3 
Mitigating Measure
Monitor and Observe the cause of low Survival Rate 64 34.6 
Change the stock/buy new stock 54 29.2 
Proper handling management 45 24.3 
Use 0f Nets to Catch Bird Eating Fish/predators 16 8.6 
Letting it go 12 6.5 
Used of chemicals to eradicate birds Eating Fish 5 2.7 
Use of Chemicals to Eradicate Bird Eating Fish 3 1.6 
Changing Water 2 1.1 
Lessening the Use of Chemicals 1 0.5 
Additional Compartments 1 0.5 
minimize stress/handling fish 1 0.5 
Put Aerator/aeration 1 0.5 
Put Malaga rabbit dish 1 0.5 
Separation of small and big fish 1 0.5 
220
Milkfish Appendix Table 7. Disease of milkfish
Percent 
Reporting 
Disease symptom (97)
please, specify: 
Bruises In Gills/Body scales removed 26.3 
Malnourish/thin/no appetite 20.6 
Gasping due to lack of oxygen
oxygen lack 15.0 
has ticks, white spots 13.1 
Loss of Oxygen, Finrot, Fungus, ulcer, lice 6.9 
Discolored patches on the skin/dark skin /Finrot/ Lack of Oxygen 3.1 
Ulcers/ Open wounds 3.1 
Lice,Fungus,Loss of oxgyen/Gill flukes 1.9 
Loss of Oxygen, Finrot, Fungus,Red Skin 1.9 
Yellowing of Liver/damage gall bladder 1.9 
No Appetite, Blindness, Wounds 1.3 
Red Eyes 1.3 
Small Tail 1.3 
Unbalance their swim/ red eye 1.3
Blackened Tail 0.6 
Red Gills 0.6 
Stage when disease mentioned occured (197)
(Fry to fingerling; Fingerling stage; Grow out 
stage; Others)
Grow out stage 33.7 
Fry to fingerling 33.7 
Fingerling stage 29.5 
Fingerlings and Growout stage 3.1 
Cause of the disease observed 
(Genetic materials; Production and 
management related; Water 
quality/management; Feeds; Others)
Water Quality/ Management 72.6 
Production and Management related 15.2 
Genetic Material (e.g, SPS Issue) 5.6 
Bird attack 5.1 
Temperature 1.0 
Predators 0.5
221
Milkfish Appendix Table 8. Probable cause of mortality
Percent Reporting n 
=300
Water Quality 27.3 
Climate Change 23.0 
Presence of Birds 18.0 
Temperature and Weather 14.3 
Poor Water Quality 12.3 
Lack of oxygen, stressed 12.0 
Predators 10.0 
Birds Eating Fish 4.7 
Water Management/Water Contamination 3.3 
Physio-chemical parameters 1.7 
Fish kill/Red tide 1.3 
Feeding management/inadequate feed 1.3 
Water Pollution 1.3 
Salinity, rainfall 1.0 
Heat from The Sun 1.0 
Over Crowding 1.0
Poor Management 0.7 
Genetics 0.7 
High Tide and Low Tide 0.3 
Milkfish Appendix Table 9. Probit Results on GAP Certification
GAqPCert Coef. Std. Err. z P>z [95% Conf. Interval]
Ethnicity 1.0458** .2046928 5.11 0.000 .6446092 1.44699
HHSize .0709072* .0407704 1.74 0.082 -.0090014 .1508157
TotalProdArea 5.45e-06* 2.79e-06 1.95 0.051 -2.39e-08 .0000109
MembershipToOrg .5687858** .2782354 2.04 0.041 .0234545 1.114117
AccessToExtn .7718919** .3390524 2.28 0.023 .1073614 1.436422
AccessToCrdt .3861189* .2397157 1.61 0.107 -.0837152 .855953
AccessToInsrnce 1.646446** .4478729 3.68 0.000 .7686312 2.524261
ColdStorage 1.872881** .4192919 4.47 0.000 1.051084 2.694678
_cons -1.142001 .2632342 -4.34 0.000 -1.65793 -.626071
**Significant at 5% level; *Significant at 10% level
Milkfish Appendix Table 10. Probit results on disease management
DiseaseMgt Coef. Std. Err. z P>z
No.ofYrsInSchool .097** .031 3.11 0.002
Age .017** .007 2.55 0.011
TotalProdArea .000** .000 2.76 0.006
FngrlingProdOperation 1.019** .272 3.74 0.000
Grow-out Brackish Oprtn .744** .328 2.27 0.023
GrwOutSeaCageOprtn .707* .403 1.76 0.079
Fry Origin 1.238** .221 5.61 0.000
cons -3.496 .650 -5.38 0.000
**Significant at 5% level; *Significant at 10% level
222
Milkfish Appendix Table 11. Production by farm type
Cost of production per cycle
Grow-out 
Pond
per ha
Cage
Per Cage
Nursery
per ha
Total Cost 83,095.00 29,955.00 
 
95,630.00 
Percent of total
Fry/Fingerling 36 2 29
Feeds 47 70 52
Materials 10 10 12
Utilities 3 6 5
Labor Cost 4 12 2
100 100 100
Milkfish production per cycle
Average
Area
Total Production Sold Consumed/
Quantity
(kg) Value (Pesos) Quantity (kg)
Value
(Pesos) Waste (kg)
Grow-out Pond
Per ha 1.92 ha 2,005.63 169,691.44 1,836.69 
 
156,190.82 168.94 
Cage Culture 1,154.06 98,439.49 1,014.80 
 
86,353.97 139.26 
Nursery pieces Value pieces Value
per ha 4.91 ha 70,752.00 318,384.00 
 
70,752.00 
 
318,384.00 
Cost and return per cycle
Amount (Pesos)
Grow out pond (per ha)
Value 169,691.44 
Cost 83,095.00 
Net 
Return 86,596.44 
Grow out cage 
Value 98,439.49 
Cost 29,955.00 
Net 
Return 68,484.49 
Nursery
Value 318,384.00 
Cost 95,630.00 
Net 
Return 222,754.00 
223
Milkfish Appendix Table 12. Probit results on cold storage facilities
Cold Storage Coef. Std. Err. z P>z [95% Conf. Interval]
Age -.0236618* .014134 -1.67 0.094 -.051364 .0040404
Ethnicity 1.497182 .9982793 1.50 0.134 -.4594094 3.453773
HHSize -.2014562** .098193 -2.05 0.040 -.393911 -.0090014
Grow-out Brackish 
Oprtn
.6182307 .6760817 0.91 0.360 -.7068651 1.943326
GrwOutSeaCageOprtn 4.451495** .7890941 5.64 0.000 2.904899 5.998091
Fry Origin 1.016559* .590722 1.72 0.085 -.1412345 2.174353
AccessToInsrnce -1.247404** .5939913 -2.10 0.036 -2.411605 -.0832022
_cons -2.577655 1.422072 -1.81 0.070 -5.364866 .2095545
**Significant at 5% level; *Significant at 10% level
Milkfish Appendix Table 13. Technology adoption by traders
Adopting Percent
Number of traders 33
Washing with pond water/sea water 20
 
61 
Pre Chilling 21
 
64 
Icing 15
 
45 
Using refrigerated van 19
 
58 
Utilizing the available ice plant in the area 33
 
100 
Minimize contact in dirty surface 33
 
100 
Sorting and grading 33
 
100 
Preventing physical damage 33
 
100 
Packing in wooden/styro boxes or metal container "bañera" 33
 
100 
Labeling 23
 
70 
Cleaning/degutting 21
 
64 
Using rigid wooden container for shipment in commercial cargo 23
 
70 
Deboning 33
 
100 
Marinating 33
 
100 
Frozing Whole/Prime cuts (belly/back 33
 
100 
Freezing fresh milkfish in cold storage 33
 
100 
224
Milkfish Appendix Figure 1. Regional Percentage Contribution to Milkfish Production
(Source of Basic Data: PSA)
0.95 
26.85 
0.14 
15.96 
14.02 
0.81 
1.19 
20.58 
1.38 
2.12 
2.39 3.78 
4.79 2.41 
0.81 1.91 
NCR
Ilocos Region
Cagayan Valley
Central Luzon
CALABARZON
MIMAROPA
Bicol
Western Visayas
Central Visayas
Eastern Visayas
225
Coco Sugar Appendices 
Coco Sugar Appendix 1. Overview of the Coco Sugar Industry
The coconut sap sugar, being a natural sweetener, targets the health-conscious market. The increasing number of 
diabetic people in the world hit 346 million in 2011 according to the World Health Organization with 23.6 million in 
the US and 8 million in the Philippines. This implied the need for a healthier sweetener like coco sugar. The 
projected requirement for alternative sweetener in 2016 according to the World Health Organization is almost 
30,000 metric tons based on the assumption of 5 percent target diabetics. Hence, consumers all over the world are 
now shifting to organic and natural products like coconut sap sugar which has a low glycemic index of 35, rich in 
phytochemicals, key vitamins and minerals.
Philippines ranks first among the top most exporting countries in the world contributing 52% of the total export 
volume, followed by Indonesia with 24 % and Thailand with 13% (Coco Sugar Appendix Figure 1). Top ranking 
producers in the country are Northern Mindanao (sharing 32%), XI (19%), and XII (21%) with Region IV-A picking up 
in terms of production capacity. There is an increasing demand for coconut sap sugar or coco sugar due to its 
nutritional value as healthy product hence the competitive advantage of the Philippines in the global market in 
terms of quality has to be protected by setting quality standards and pursuing clinical researches to promote this 
high-value product. Moreover, this product is seen to emancipate the coconut farmer from poverty, 
mainstreaming the coconut tappers and the village processors in the supply-value chain of the industry. 
Mindanao is the largest producer of coco sugar and where several established local brands of coco sugar can be 
found. The provinces of Misamis Oriental and Davao del Sur are major producers in the island. Both are among the 
top ten coconut producing provinces in the Philippines with Misamis Oriental ranking 7th and Davao del Sur, 10th
.
Data from the Philippine Coconut Authority – Market Development Department (PCA-MDD) revealed that from 
10,000 kilograms of the country’s coco sugar export volume in 2009, it has already increased to around 40,000 
kilograms in the following year and still continues to increase up to the present. Coco sugar in the Philippines is 
being exported to Japan, US, Middle East, Hong Kong, South Korea, Norway, France, Canada, Switzerland, 
Australia, and New Zealand. The monthly export performance is shown in Coco Sugar Appendix Figure 2.
Contamination in coco sugar may happen in all phases of production from tapping of coco sap to processing and 
packaging. Cleanliness and sanitation should therefore be observed in all phases to avoid wastage and losses. 
Hence, a quality control officer is assigned to ensure the quality of the product. Targeting the export market 
requires compliance to food safety laws of the importing country to ensure the safety and traceability of the 
exporter’s coconut sugar. One particular requirement is to have a HACCP system in place which guarantees the 
food safety of the product. The exporter must test for contamination such elements as plastic residues, metal and 
dirt, cleaning agents, pesticides, heavy metals and food-borne micro-organisms. Two out of seven PCA-registered 
coco sugar processors in Northern Mindanao and all manufacturer-exporters in the Davao Region have HACCP and 
other certifications like Kosher, HALAL, JAS, ISO and others
 
226
Coco Sugar Appendix 2. Coco Sugar Probit Models
Probit models are used to explore the factors affecting significantly the decision of producers to adopt a given 
improved technology or management practice. The model is formulated and estimated using the data from the 
survey conducted in this baseline study. The general form of the model is 𝑌𝑖 = 𝐴 +∝
𝒕 𝑿𝑖 +∈𝑖 where 𝑌𝑖
is a binary 
variable with values of 0 and 1, representing the adoption decision of producer i. 𝑿𝑖
is a vector of explanatory 
variables attributable to producer I, while ∝ is a vector of same dimension representing the coefficients of each of 
the explanatory variable in 𝑿. 𝐴 and ∈𝑖 are respectively the constant and error terms, respectively of the probit 
model. 
For the coco sugar producers, the model specified in this study is the following:
𝑌𝑖𝑗 = 𝐴𝑗 + ∑ 𝛼𝑘𝑆𝐸𝐷𝐶𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑆𝐸𝐷𝐶
+ ∑ 𝛽𝑘𝐹𝐴𝑅𝑀𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐹𝐴𝑅𝑀
+
∑ 𝜇𝑘𝑀𝑘𝑖 + ∑ 𝛿𝑘𝐼𝑁𝑆𝑘𝑖
∀ 𝑘 𝑖𝑛 𝑀 ∀ 𝑘 𝑖𝑛 𝐼𝑁𝑆
+ ∑ 𝛾𝑘𝐼𝑁𝐹𝑘𝑖
∀ 𝑘 𝑖𝑛 𝐼𝑁𝐹
+ 𝜀𝑖𝑖
𝑌𝑖𝑗 is 1 if respondent I adopts technology/practice j,
J=1 is General Cultural Mgt; J=2 Nutrient Mgt Sap Mgt; J=3 Postharvest Mgt; J=4 Consolidated Farming; J=5 GAP 
Certification; J=6 Organic farming Sap use (e.g. solely for coco-sugar or for other products).
𝑺𝑬𝑫𝑪𝒌𝒊 is the vector of socio-economic demographic cultural variables attributable to producer i and used to 
explain the adoption decision j of producer I, where k=1 is education; k=2 is age; k=3 is ethnicity, k=4 is gender, 
k=5 is household income, k=6 is non-farm income; and k=7 is household size.
𝑭𝑨𝑹𝑴𝒌𝒊 is the vector of farm characteristics attributable to producer i and used to explain the adoption decision j 
of producer i, where k=1 is farm size; and k=2 is distance from market; k=3 is accessibility; k=4 is CSI infestation. 
and k=6 is volume of sap collection.
𝑴𝒌𝒊 is the vector of market-related variables attributable to producer I and used to explain the adoption decision j 
of producer I, where k=1 is premium price for quality; k=2 is major market (e.g. trader, consolidator, processor); 
k=3 is source of market information.
𝑰𝑵𝑺𝒌𝒊 is the vector of institutional variables attributable to producer i and used to explain the adoption decision j 
of producer I, where k=1 is membership in organization; k=2 is access to extension service; k=3 is availability of 
technology in the area; k=4 is contractual arrangements; k=5 is access to credit; k=6 is access to crop insurance; 
k=7 is beneficiary of government program; and k=8 is financial inclusion.
𝑰𝑵𝑭𝒌𝒊 is the vector of infrastructural variables attributable to producer i and used to explain the adoption decision 
j of producer I, where k=1 is access to farm to market roads; k=2 is road condition; and k=3 is access to the 
internet.
𝐴𝑗
, 𝜀𝑖𝑖 are respectively the constant and error terms of the model.
𝛼𝑘, 𝛽𝑘,𝜇𝑘, 𝛿𝑘 and 𝛾𝑘 are the vectors of coefficients for each of the variable k in vectors SEDC, FARM, M, INS, and 
INm respectively.
227
Coco Sugar Appendix Table 1. Probit results on adoption of PNS
pnscert Coef. Std. Err. z P>z 95% Conf. Interval
Sex -1.004263* .5292331 -1.90 0.058 -2.041541 .0330149
HHIncome 6.76e-06 7.44e-06 0.91 0.364 -7.83e-06 .0000213
FrmtoMrkt -.0842702* .0445478 -1.89 0.059 -.1715823 .003042
Sap 1.077541** .3213068 3.35 0.001 .4477914 1.707291
Syrup 1.000534** .3130267 3.20 0.001 .3870128 1.614055
MjrMrkt -.6001066** .2288467 -2.62 0.009 -1.048638 -.1515753
AccExtn .9653239** .2161902 4.47 0.000 .5415989 1.389049
AccCrdt .4981938** .2446146 2.04 0.042 .018758 .9776296
BnfcryGovt .4824654 .4293938 1.12 0.261 -.359131 1.324062
AccInsrnce .858233** .398996 2.15 0.031 .0762153 1.640251
_cons -1.209705 .6113288 -1.98 0.048 -2.407887 -.0115226
**Significant at 5% level; *Significant at 10% level
Coco Sugar Appendix Table 2. Marketing of coco sugar and by-products
Variable No. Reporting 
(n=259) Percent
Perform Grading and Classification
 No 259 100.00%
Compliance to product packaging and labelling requirement of buyer
 No 80 66.12%
 Yes 41 33.88%
Usual packaging material used
 Paper 2 0.95%
 Bottle 1 0.47%
 Plastic 208 98.58%
 Carton -
 Sachet -
Compliance to Philippine National Standards
No 180 69.50%
Yes 76 29.34%
Partially observed 3 1.16%
Issues on product development, branding and labeling
None
Percent of production rejection encountered
<5 254 98.07%
5 to 10 3 1.16%
>10 2 0.77%
Causes of product rejection
228
Overcooked 5 33.33%
Fermentation 5 33.33%
Over supply 3 20.00%
Contamination 2 13.33%
Selling/marketing methods
Direct selling 259 100.00%
Online marketing -
Others, identify: -
Mode of delivery
Delivered 243 93.82%
Pick-up 16 6.18%
Both -
Mode of payment
Cash 164 59.64%
Weekly Payment 39 14.18%
Consignment 33 12.00%
Check 24 8.73%
Credit 15 5.45%
Average distance of farm to market (km) 8.96
Farm to market road condition
Fair 188 72.59%
Good 60 23.17%
Poor 11 4.25%
Coco Sugar Appendix Table 3. Problems encountered in coco sugar production
Risk Factors
No. 
Reporting 
(n=259)
Percent
Low yield of sap from existing coconut varieties in the area
No 84 32.43%
Yes 175 67.57%
Limited number of dwarf coconut trees in the area
No 201 77.61%
Yes 58 22.39%
Limited skilled manpower in collecting sap
No 254 98.07%
Yes 5 1.93%
High risk in collecting sap due to tall trees 
No 179 69.11%
Yes 80 30.89%
229
High labor cost
No 256 98.84%
Yes 3 1.16%
Fermentation problem due to delays in collection and contamination 
No 114 44.02%
Yes 145 55.98%
Adulteration due to high cost of labor
No 259 100.00%
Yes 0 0%
Lack of sanitation in storage facilities 
No 247 95.37%
Yes 12 4.63%
Price competitiveness
No 234 90.35%
Yes 25 9.65%
Follow-up Questions
Other by-products produced when coco sap is fermented
 Vinegar 178 0.98342541
 Honey 2 0.01104972
 Mixed to harvested sap 1 0.55%
 Omega 1 0.55%
 Tuba 1 0.55%
 Aminos 9 4.97%
 Ethyl alcohol 1 0.55%
 Pinakurat 1 0.55%
 Soy sauce 3 1.66%
 Tikoy 3 1.66%
Other by-products commercially viable
No 1 0.55%
Yes 182 99.45%
Note: Multiple responses for the follow-up questions
Coco Sugar Appendix Table 4. Mitigating measures to address the problems encountered in coco 
sugar farming
Risk factors Mitigating Measures No. reporting Percent
Low yield of sap 
from existing 
coconut varieties in 
the area
Applying fertilizer during low months 1 0.57%
Maintenance 4 2.29%
Fertilizer application, rest the tree for a while 4 2.29%
Tapping 2 1.14%
Watering 2 1.14%
230
Organic fertilizer application 14 8.00%
During dry season, rest the tree that produces small 
sap
7 4.00%
Use of salt as fertilizer 2 1.14%
None 139 79.43%
Limited number of 
dwarf coconut trees 
in the area
Continued tapping tall trees 6 10.34%
Planting more dwarf trees 22 37.93%
None 30 51.72%
Limited skilled 
manpower in 
collecting sap
Assisted by a family member 3 60%
Trained tappers 2 40%
High risk in 
collecting sap due to 
tall trees 
Careful collection 26 32.50%
Established bamboo bridge connected to other 
trees
1 1.25%
Fell down/massage the fractured area 1 1.25%
Get insured 31 38.75%
Tapping trees with the enough height 1 1.25%
Tappers undergo necessary training 1 1.25%
None 17 21.25%
Used of stairs in tapping 1 1.25%
Had established own techniques 1 1.25%
High labor cost None 3 100%
Fermentation 
problem due to 
delays in collection 
and contamination 
Reminding tappers about time duration 1 0.69%
Followed the exact time of harvest 7 4.83%
Mixed with newly harvest sap 8 5.52%
Follow PNS SOP 12 8.28%
Processed to other products 84 57.93%
Sanitation 1 0.69%
Share to neighbors 1 0.69%
Strict protocol rates 1 0.69%
None 30 20.69%
Lack of sanitation in 
storage facilities 
Keeping the are clean 9 75%
Personal expense to buy the cleaning materials 1 8.33%
None 2 16.67%
Price 
competitiveness
None, let the market decides 25 100%
231
Coco Sugar Appendix Table 5. Assistance and support services needed in coco sugar farming by 
agency involved
Assistance Needed Agency Involved
Any agency Government Private
No. 
reporting
Percent No. 
reporting
Percent No. 
reporting
Percent
Technical Assistance 21 19.63% 59 55.14% 2 1.87%
Training on coconut production 
and processing
0.00% 5 4.67% 0.00%
Trainings on value adding of 
coco products
0.00% 12 11.21% 3 2.80%
Training on tech improvement 1 0.93% 3 2.80% 0.00%
Capacity building 0.00% 1 0.93% 0.00%
Food safety 0.00% 1 0.93% 0.00%
Equipment and machineries
Blower 0.00% 2 2.74% 4 5.48%
Boiling facilities 0.00% 1 1.37% 1 1.37%
Chainsaw 0.00% 4 5.48% 5 6.85%
Containers 0.00% 0.00% 3 4.11%
Hauling trucks 0.00% 1 1.37% 10 13.70%
Mechanized oven 0.00% 2 2.74% 2 2.74%
Mower and digger 0.00% 1 1.37% 0.00%
pH meter 2 2.74% 16 21.92% 0.00%
Syrup production equipment 4 5.48% 5 6.85% 3 4.11%
Tapping knife and other utensils 0.00% 1 1.37% 6 8.22%
Infrastructure and storage 
facilities
Building/concrete facility 1 1.43% 6 8.57% 3 4.29%
Processing facility 3 4.29% 16 22.86% 4 5.71%
Repair assistance 0.00% 2 2.86% 3 4.29%
Roofing materials 0.00% 0.00% 3 4.29%
Storage facility 3 4.29% 18 25.71% 8 11.43%
Financial assistance
Working capital 29 24.37% 62 52.10% 15 12.61%
Calamity assistance 2 1.68% 3 2.52% 0.00%
Loan 1 0.84% 7 5.88% 0.00%
Market assistance and linkaging
Market and linkage 3 9.38% 23 71.88% 2 6.25%
Price instability 0.00% 2 6.25% 0.00%
Forums and seminars 0.00% 2 6.25% 0.00%
Training on GMP-HACCP
Training on GMP-HACCP 3 0.25 9 0.75 0.00%
232
Seal of quality assurance/trade 
marking
Seal of quality 4 44.44% 2 22.22% 0.00%
Training on quality assurance 0.00% 3 33.33% 0.00%
FDA/Organic certification
Organic certification 4 44.44% 5 55.56% 0.00%
Coco Sugar Appendix Table 6. Probit results on improved packaging
imprvdpckgng Coef. Std. Err. z P>z 95% Conf. Interval
Age -.0219964** .0085845 -2.56 0.010 -.0388216 -.0051712
HHIncome .0000103* 6.45e-06 1.60 0.109 -2.29e-06 .000023
HHSize -.0495304 .0505565 -0.98 0.327 -.1486194 .0495587
FrmtoMrkt -.1101939** .0464874 -2.37 0.018 -.2013076 -.0190803
AccCrdt .5933656** .2130567 2.79 0.005 .1757821 1.010949
FmrCond .6194546** .2304274 2.69 0.007 .1678252 1.071084
AccInsrnce 1.655269** .2427524 6.82 0.000 1.179483 2.131055
_cons -.3777561 .4140578 -0.91 0.362 -1.189294 .4337823
**Significant at 5% level; *Significant at 10% level
Coco Sugar Appendix Figure 1. Coco Sugar Producers in the World and in the Philippines
233
Coco Sugar Appendix Figure 2. Monthly Average Export Performance, 2017-2020
0.00
50,000.00
100,000.00
150,000.00
Januar…
April '17
July '17
Octob…
Januar…
April '18
July '18
Octob…
Januar…
April '19
July '19
Octob…
Januar…
April '20
July '20
Octob…
Volume in KGs
Monthly Exports Performance of Coconut Sap Sugar
HS Code: 1702
Volume in KG
2017-2020