Baseline Survey Report of Cashew Producers and Processors MozaCajú Project Prepared for TechnoServe – Mozambique and the Aga Khan Foundation – Mozambique By TANGO International January 2014 1 Table of Contents Introduction......................................................................................................................................... 2 Methodology ....................................................................................................................................... 2 Producers’ Level Findings..................................................................................................................... 6 Demographic Characteristics.................................................................................................................... 6 Cashew Tree Cultivation............................................................................................................................ 8 Tree holding and acquisition................................................................................................................. 8 Age of trees......................................................................................................................................... 10 Planting material................................................................................................................................. 12 Post-harvest loss................................................................................................................................. 14 Reasons for planting new trees .......................................................................................................... 17 Labor ................................................................................................................................................... 19 Cashew nut harvesting methods ........................................................................................................ 20 Storage practices and equipment....................................................................................................... 22 Production Practices ............................................................................................................................... 24 Improved production techniques and technologies........................................................................... 24 Training ................................................................................................................................................... 26 Access to extension............................................................................................................................. 28 Extension knowledge .......................................................................................................................... 29 Extension quality................................................................................................................................. 29 Production and Sales............................................................................................................................... 30 Average sales ...................................................................................................................................... 30 Variation in production....................................................................................................................... 32 Prices and product types .................................................................................................................... 34 Buyers ................................................................................................................................................. 36 Management Practices........................................................................................................................... 39 Group Participation................................................................................................................................. 42 Access to Credit....................................................................................................................................... 46 Main Problems in the Community........................................................................................................... 47 Processor Level Findings .................................................................................................................... 48 Conclusions........................................................................................................................................ 56 Cashew Producers................................................................................................................................... 56 Cashew processors.................................................................................................................................. 56 Annex 1. Producer-Level Project Indicators............................................................................................... 58 Annex 2. Producer Level Indicators Calculation ......................................................................................... 72 Annex 3. Processor Level Indicators........................................................................................................... 76 Annex 4. Producer Questionnaire .............................................................................................................. 78 Annex 5. Selected Communities by District and Province.......................................................................... 90 Annex 6. Processor Topical Outline............................................................................................................ 92 2 Introduction This report presents the results of the baseline survey of cashew producers undertaken for the MozaCajú project implemented by TechnoServe, in partnership with the Aga Khan Foundation, under a grant from the United States Department of Agriculture (USDA) in 14 districts in Cabo Delgado, Nampula, and Zambezia Provinces, Mozambique. The survey was undertaken between October and December 2013. The purpose of this baseline survey is to provide baseline values for MozaCajú project indicators measured at the level of cashew producers, and also to provide general information about conditions, cashew production and marketing activities, and problems faced by cashew farmers within the MozaCajú project area. These baseline results will serve as the benchmark values to be used for measuring project impacts on cashew producers over the life of the MozaCajú project. In addition, the producer survey has been designed to collect information relevant for TechnoServe’s ‘shared value’ approach to develop linkages among agents in value chains. In the case of this project, the survey collects information from cashew producers about their perceptions of the most serious problems in their communities. This information may be used to inform strategies that processing companies may pursue to establish and strengthen long-term ties with cashew producers and the communities in which cashew factory workers live. The producer survey is a statistically representative sample of cashew producers within the 14 districts of the MozaCajú project area, so the results from the survey may be considered as representative of all cashew producers within the project area. Methodology The survey of cashew producers is designed to capture information to compute all project indicators at the level of cashew producers, as well as additional background information about household demographic characteristics, cashew production and marketing practices, training received, farm management practices, membership in farmer groups, access to and use of credit for cashew production, and assessments of principal problems in the communities where the producers reside. This last information is to provide information about possible areas where processing companies could provide support to communities under TechnoServe’s ‘shared value’ approach. The producer level project indicators are provided in Annex 1. Details for calculation of the producer level indicators are provided in Annex 2. Processor level indicators (taken from the processor baseline report) are provided in Annex 3.The full producer questionnaire is provided in Annex 4. The survey of cashew producers is designed to be a statistically representative sample of cashew producers within the 14 districts of the project area. Under this design, the results from the survey may be considered as representative of all cashew producers within the project area. The sample was also designed to provide a sufficient level of statistical accuracy of estimates at the district level, so that comparisons across districts can be made with a certain degree of statistical confidence. 3 In order to meet these sampling requirements, the sample size was computed to be able to detect a difference in cashew productivity per tree (kg/tree) of 30% between any pair of the 14 districts in the project area with a 95% statistical confidence and 80% statistical power. The required minimum sample was computed using the following formula:1 n = D [(Zα + Zβ) 2 * (sd1 2 + sd2 2) / (X2 - X1) 2] Where: n = required minimum sample size per survey round or comparison group D = design effect for complex surveys (value = 2). The two-stage process for selecting cashew producers in each district is described below. X1 = the estimated level of an indicator in one district (assumed to be 1.0) X2 = the expected level of the indicator another district such that the quantity (X2 - X1) is the size of the magnitude of difference in the indicator between districts that it is desired to be able to detect (assumed to be 1.30, or a change of 30%) sd1 and sd2 = expected standard deviations for the indicators for the respective districts being compared (assuming Coefficient of Variation of 0.5, sd1= 0.5 and sd2=0.65 ) Zα = the z-score corresponding to the degree of confidence with which it is desired to be able to conclude that an observed change of size (X2 - X1) would not have occurred by chance (statistical confidence) Zβ = the z-score corresponding to the degree of confidence with which it is desired to be certain of detecting a change of size (X2 - X1) if one actually occurred (statistical power). Assuming that the standardized expected productivity of cashew trees in a given district, X1 is 1.0 and we want to be able to detect a difference of 30% in productivity of cashew trees between this district and any other district in the sample, then X2 = 1.30. Assume that the coefficient variation (standard deviation / mean) of the productivity of cashews is 0.5, consistent with other estimates of variation in cashew productivity of smallholder producers in Africa, then sd1 = 0.5 (1.0 * 0.5), and sd2 = 0.65 (1.30 * 0.5). Using a confidence level of 95% (Zα = 1.645) and a power level of 80% (Zβ = 0.840). A design effect of 2.0 is used, which combines the offsetting effects of a 2-stage clustered design with a stratified sample of survey sites. Plugging these parameter values into the sample size formula gives: n = D [(Zα + Zβ) 2 * (sd1 2 + sd2 2 ) / (X2 - X1) 2 ] = 2.0[(1.645 + 0.840)2 * (0.52 + 0.652) / (1.30 – 1.0)2] = 67.3 Correcting for a non-response factor of 5%, the minimum target sample size to be selected is = 67.3 * 1.05 = 70.7 ≈72 (This figure was chosen for logistical purposes, to have an even number of households per district) 1 Magnani, Robert. Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), 1997. 4 The sample selection process is designed to provide an unbiased sample of cashew producers. As described above, the sample was stratified into 14 districts across the three provinces of Cabo Delgado, Nampula, and Zambezia, where the project will operate. Because an equal number of producers (72) were selected from each district, but the districts all have different populations, sample weights were applied to each district to adjust for the differences in the proportion of households sampled from each district compared to the proportion of households residing in each district. The weighting is based on population, so the implicit assumption is that the relative proportions of cashew producers across districts are equal to the relative proportion of the population across the districts. Because the districts are very large geographically, the MozaCajú project will operate in particular administrative posts (identified by project staff prior to the baseline) rather than across districts as a whole. For this baseline, the selection of producers within the districts was done in a two￾stage process. First, a total of four communities were selected from the total list of communities within the identified administrative posts in each district. Second, within the selected communities, a total of 18 households were interviewed. The four communities per district were selected based on probability proportional to size (PPS), so that each household within the district had an equal chance of being selected. Annex 5 provides the selected communities by district and province. The preferred means to select respondents for a randomly selected sample is to draw from complete lists of all respondents. The sample frame for the producer survey includes households that produce cashews. Since there are no lists of cashew producers available, a random walk procedure was used to select respondents for the survey. Within the selected communities, enumerators would begin from a central location in a village, and each move along a separate path, randomly chosen by the team supervisor. Interviewers would skip a fixed-number of households based on the last digits of serial numbers from randomly selected bank notes, and ask the individual at the selected home whether members of that household produced cashews. If they responded positively, the household was interviewed, and if negatively, the next household along the path would be asked if they produced cashews. In this way, only households that produce cashews were included in the sample. All of the results presented in this report are broken down in three different ways: 1. Province (Cabo Delgado, Nampula, Zambezia) 2. Gender of household head 3. Category of volume of cashew sales The third category is to permit comparisons of characteristics by “scale” of cashew farmer. The three categories are defined as the terciles (three groups with equal numbers of cases), based on the ranking of the volume of sales of cashews and cashew products (fruit, juice and processed products) per household. Thus the households in the “Low” category are the 33% of households with the lowest value of cashew sales in the sample, the “High” are the 33% of households with the highest value of cashew sales, and the “Mid” category are the households that fall in the middle in terms of the value of their cashew sales (Error! Reference source not found.). 5 For the purpose of analysis, sample weights have been applied to data collected from the sample in order for the information presented in the following tables to reflect the respective population proportions in each of the districts. Sample weights were calculated using the following formula2: Wi = 1 / Pi Wi = sampling weight for districti Pi = probability of selection for a sampled household in districti (72 / district population / avg. household size) A normalization factor, equivalent to the proportion of total households in the sample to total households in the 14 sampled districts (1,008 / 161,7523 ) is then applied to the weights so that all of the computed household counts in the data analysis correspond with the number of households sampled. Table 1: Sample Weights Province District Pop. % # HH Sampled (a) Sample Weight (b) Weighted # HH (a * b) % Cabo Delgado Mueda 44,669 4.8% 72 0.672 48 4.8% Nangade 61,371 6.6% 72 0.924 67 6.6% Palma 2,843 0.3% 72 0.043 3 0.3% Muidumbe 50,766 5.5% 72 0.764 55 5.5% Mocimboa da Praia 17,268 1.9% 72 0.260 19 1.9% Metuge 30,101 3.2% 72 0.453 33 3.2% Chiure 72,687 7.8% 72 1.094 79 7.8% Macomia 61,205 6.6% 72 0.921 66 6.6% Total 340,910 36.7% 576 N/A 369 36.7% Nampula Meconta 19,033 2.0% 72 0.286 21 2.0% Mogovolas 127,783 13.7% 72 1.923 138 13.7% Angoche 116,395 12.5% 72 1.752 126 12.5% Moma 76,238 8.2% 72 1.148 83 8.2% Total 339,449 36.7% 288 N/A 368 36.7% Zambezia Gile 87,355 9.4% 72 1.315 95 9.4% Pebane 162,361 17.5% 72 2.444 176 17.5% Total 249,716 26.5% 144 N/A 271 26.5% Total 930,075 100.0% 1,008 N/A 1008 100.0% Sample Weight = [District Population / Avg. HH Size (5.75) / Households Sampled per District (72)]*Normalization Factor (.0062) Indicator values in Annex 1 have been inflated to population values using the sample weights in Table 1 without the normalization factor. Thus the estimates are based on the proportion of the surveyed households in the total population in each district. 2 Magnani, Robert. Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), 1997. 3 The number of households in the population is calculated using an estimate of the number of members per household across the 14 districts: 930.075 / 5.75 = 161,752. 6 Table 2: Characteristics of cashew sales categories Sales Categories Low Mid High Range of value of sales (USD/HH) 0-25.67 26.67-58.33 60 – 5,866.67 Mean value of cashew sales (USD/HH) 14.51 39.15 295.55 Median value of cashew sales (USD/HH) 16.67 40 133.33 N= 257 291 275 The determination of the total area planted in cashew trees is very problematic for smallholder producers in Mozambique. Some producers have their trees in well-designed orchards, with well￾defined spacing between trees, while others have trees widely dispersed in very unorganized patterns. Thus, two producers with the same number of trees may have those trees planted over very different areas. In order to standardize the area, we have computed the “effective” area in cashews based on the number of cashews that the farmer has. In particular, we estimated the median area per tree, based on the reported number of cashew trees farmed, and the reported area planted in cashews, from the sample. The median area per cultivated tree computed from the sample is 286 square meters (35 trees per ha). We computed the effective area in cashews by multiplying the number of trees cultivated by the farmer times 286 square meters. This is the measure of area used for the total area under cashew production, as well as the area under specific techniques and technologies. Throughout the body of the report, text highlighted in red denotes indicators that are officially tracked as part of the MozaCajú Performance Monitoring Plan (PMP) created by the United States Department of Agriculture (USDA). Producers’ Level Findings Demographic Characteristics In the three provinces selected for this study, 20.1% of households were female-headed. The proportion of female-headed households was slightly higher in Zambezia Province (23.2%) (Error! Reference source not found.). Error! Reference source not found. indicates that the percentage of female-headed households was highest in the low sales category (23.6%) and lowest in the high sales category (13.9%) and that the difference is statistically significant. Table 3: % of female-headed households by province Province Cabo Delgado Nampula Zambezia Total % of female-headed households 18.70% 19.30% 23.20% 20.10% N= 369 369 269 1008 p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado. Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 7 Table 4: % of female-headed households by sales category Sales Categories Low Mid High Total % of female-headed households 23.60% 19.50% 13.9%3 18.90% N= 258 291 277 826 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low. Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Male-headed households were significantly older than female-headed households by 5.3 years. The oldest male-headed households were in Cabo Delgado (mean age of 52.0 years) and the youngest were found in Nampula (mean age of 41.4 years). Households were significantly larger in male-headed households (mean of 5.8 persons) and the largest households were found in Cabo Delgado (mean of 6 persons) while the smallest households were found in Zambezia (mean of 5.1 persons) (Error! Reference source not found.). Table 5: Age of heads of household and average household size by gender of head of household and province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Average age HoH 46.9* 41.6 52.0 41.4 43.3 3 45.9 N= 796 196 369 362 260 992 Average household size 5.8* 5.0 6.0 5.8 5.1 2,3 5.7 N= 805 203 369 369 269 1008 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. When households were disaggregated between high, medium, and low sales terciles, the average age of the head of household was significantly higher for households that were in the high sales tercile (48.5 years). The same was true for size of household: larger households were found in the high sales category. In summary, households that were in the high sales tercile were larger and were predominantly headed by older men (Error! Reference source not found.). Table 6: Average age of head of household and household size by sales categories Sales Categories Total Low Mid High Average age HoH 40.6 44.4 48.5 3 44.6 N= 251 288 275 814 Average household size 5.2 5.4 2 6.5 3 5.7 N= 258 291 277 826 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. The percentage of female respondents who were heads of households and who could not read or write was higher (68.8 percent) than the percentage of males who were head of households (53.1 percent) and the difference is significant (Table 7). Only 23.3% of females could read and 8 write as compared to 35.5% of men. The percentage of household heads that could not read and write was higher in Cabo Delgado (72.4%) and lowest in Zambezia (46.1 %). Zambezia and Nampula were the provinces where the highest proportion of literate heads of household could be found (39.7% and 36.7%, respectively). Table 7: Literacy by gender and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Can't read or write 53.1* 68.80% 72.40% 47.3% 1 46.1% 3 56.20% Can only read 11.50% 7.90% 3.00% 16.0% 1 14.2% 3 10.80% Can read and write 35.5%* 23.30% 24.70% 36.7% 1 39.7% 3 33.00% N= 801 202 369 368 267 1003 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Cashew Tree Cultivation Tree holding and acquisition Cashew nut farmers were asked questions regarding the number of trees they own, their number of productive trees, and whether their trees were planted in a concentrated or dispersed manner. Male-headed households owned significantly more trees than female-headed households (at the median, 92 versus 75) and also had more trees under cultivation (75 versus 54). In addition, male￾headed households were more likely to plant their trees in a concentrated manner (25.4%) as opposed to female-headed households, who tended to plant theirs in a more dispersed way (Table 8). The vast majority of trees owned by both male and female-headed households were under cultivation. Cashew farming households in the province of Cabo Delgado, at the median, owned the most trees. However, many trees that these households owned were not used for cashew production (only 72%). This is interesting since households in this province had the fewest number of young trees (immature) and the largest number of trees at peak productive age (Error! Reference source not found.). There are several possible reasons why the trees aren’t used in cultivation, including old age, being in poor condition, or not bearing fruit at all (for various reasons). Cashew farming households in Nampula and Zambezia, on the other hand, owned fewer trees (medians of 75 and 80, respectively) than farmers in Cabo Delgado (median of 117) but the majority of these trees were used for production (82.7% and 84.8%, respectively). 9 Table 8: Tree holding and tree density by gender head of household and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Avg. # trees owned 195.0* 135 252.1 143.2 1 140.6 3 182.8 Median # trees owned 92 75 117 75 80 80 N= 796 203 369 362 267 998 Avg. # trees cultivated 154.5* 100.5 188.5 124.0 1 108.6 3 143.7 Median # trees cultivated 75 54 75 57 75 70 N= 799 201 369 364 267 1000 Avg. Trees cultivated / Trees owned per farmer 79.1% 80.1% 72.0% 82.7%1 84.8%3 79.3% N= 790 201 369 358 264 991 % farmers planting concentrated (vs. dispersed) 25.4%* 15.8% 14.4% 33.3% 1 22.7%2,3 23.6% N= 794 203 367 366 264 997 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Households belonging to the high sales category owned significantly more trees and had more productive trees compared with households in the medium and low sales categories. It is interesting to note that for all households actively selling cashew, regardless of the sales categories they belonged to, the average number of trees used for cashew production was high. In addition, most farmers planted their trees in a dispersed manner, as opposed to a more efficient concentrated planting density. Table 9 shows that the two main ways that households acquired cashew trees were through inheritance (56.1%) and purchase (31.5%). It is worth noting that the questionnaire only allowed for one response and the findings may not reflect households who have obtained trees through a number of different methods. Female-headed households primarily acquired cashew trees through inheritance (67.0%) as opposed to 53.2% for their male counterparts. Male-headed households, on the other hand, could purchase trees far more easily than female-headed households (33.2% versus 24.1%). Not surprisingly, households that belong to the high sales category were able to purchase trees more easily than households in the medium and low sales categories (37.2% versus 32.3% and 23.2%, respectively). Across all sales categories, households acquired trees mainly through inheritance (55%, Table 10). 10 Table 9: Tree acquisition by gender head of household and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Inheritance 53.2%* 67.0% 55.1% 65.2% 1 45.0%2,3 56.1% Purchase 33.2%* 24.1% 38.4% 22.7% 1 33.8% 2 31.5% Family Member 3.7% 4.9% 5.9% 1.6% 1 4.5% 4.0% Rental 0.5% 0.0% 0.5% 0.5% 0.0% 0.4% Other 9.2%* 3.9% 0.0% 9.9% 1 16.7%2,3 8.1% N= 802 203 370 365 269 1004 Other= planted (themselves) *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 10: Tree acquisition by sales categories Sales Categories Low Mid High Total Inheritance 57.9% 52.6% 54.9% 55.0% Purchase 23.2% 32.3% 1 37.2% 3 31.1% Family Member 4.7% 3.8% 3.6% 4.0% Rental 0.0% 1.0% 0.4% 0.5% Other 14.2% 10.3% 4.0%2,3 9.4% N = 254 291 277 822 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Age of trees Farming households in the province of Cabo Delgado reported having cultivated cashew trees significantly longer than households in the two other provinces (Table 11). In Cabo Delgado, 66% of farming households reported their trees to be at peak production age as opposed to less than 50% in the two other provinces. This could be explained by the fact that in Nampula and Zambezia, cashew trees were significantly younger than in Cabo Delgado. Female-headed households reported cultivating significantly more young trees than male-headed households. On the other hand, male-headed households had more trees in peak production years. When comparing households in the three sales categories, it is not surprising that households in the highest sales tercile had been cultivating cashew trees longer and had more trees in peak production years than households in the other two terciles (Table 12). Male-headed households had planted more new trees in the past 12 months than female-headed households, as had households in the province of Zambezia (Table 13) and households belonging to the high sales category (Table 14). Among those farmers who did not report planting new trees in the previous twelve months, the two main reasons cited were lack of access to cuts or germilings and lack of money. These two issues were more prominent among female-headed households, households in Zambezia and Nampula provinces, and households in the low and mid sales terciles (Table 15 and Table 16). 11 Table 11: Age of trees and farmer experience by gender head of household and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Avg. years of cashew cultivation 15.7 14.9 17.2 14.7 1 13.3 3 15.5 N= 641 137 349 270 160 778 How many trees are young? (<9 years) 18.9% 30.3%* 11.7% 28.5% 1 24.4% 3 21.2% N= 801 203 369 367 267 1004 How many trees are in peak production years? (9-25 years) 54.3%* 47.2% 66.0% 44.0% 1 46.9% 3 52.8% N= 803 202 369 367 269 1006 How many trees are in declining production years? (>25 years) 16.2% 14.9% 12.5% 18.6% 1 17.1% 3 15.9% N= 800 200 369 361 269 1000 How many trees are old? (no age given) 11.0%* 7.9% 9.9% 9.9% 11.8% 10.4% N= 803 202 369 367 269 1006 p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado *p<0.10: Female different than Male Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 12: Age of trees and farmer experience by sales categories Sales Categories Low Mid High Total Avg. years of cashew cultivation 13.5 14.4 17.52,3 15.2 N= 199 222 227 649 How many trees are young? (<9 years) 24.8% 22.4% 16.9%2,3 21.3% N= 258 286 277 822 How many trees are in peak production years? (9-25 years) 48.6% 48.1% 60.5%2,3 52.4% N= 258 290 275 824 How many trees are in declining production years? (>25 years) 16.5% 18.2% 15.2% 2 16.6% N= 252 291 276 818 How many trees are old? (no age given) 10.5% 11.8% 7.9% 2 10.1% N= 258 289 277 824 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 13: Average number of newly planted trees by gender of head of household and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total How many new trees planted (previous 12 months) 8.4* 4.3 10.0 4.7 8.4 2,3 7.6 N= 790 192 361 363 258 982 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 12 Table 14: Average number of newly planted trees by sales categories Sales Categories Low Mid High Total How many new trees planted (previous 12 months) 4.5 5.4 1 15.0 3 8.4 N= 253 278 270 801 1: Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 15: Reasons why no new trees were planted in the last 12 months by gender head of household and province (among those households not planting new trees) Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total No access to local cuts or germilings 52.5%* 63.8% 34.4% 68.7% 1 71.1% 3 55.7% Lack of money 11.0% 8.7% 16.5% 4.7% 1 9.4% 10.4% No market exists 7.4% 9.4% 19.2% 0.0%1 0.8% 3 7.8% Requires too much labor 11.0% 6.7% 14.3% 8.4% 3.9% 3 9.7% Other 18.1% 11.4% 15.6% 18.2% 14.8% 16.4% N= 419 149 224 214 128 566 *p<0.10: Female different than Male *p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 16: Reasons why no new trees were planted in the previous 12 months by sales categories (among new households not planting new trees) Sales Categories Low Mid High Total No access to local cuts or germilings 61.5% 62.4% 41.4%2,3 55.5% Lack of money 4.9% 8.9% 12.1% 8.6% No market exists 4.2% 5.1% 5.0% 4.8% Requires too much labor 8.4% 5.7% 20.7%2,3 11.4% Other 21.0% 17.8% 20.7% 19.8% N= 143 157 140 440 Other = lack of land/space; time constraints; problems with personal health p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Planting material Across gender and provinces, the most common planting material was seeds (55.7%), distantly followed by shoots/grafts (10.4%) that were mostly grown in farmers’ own nurseries (Table 17 and Table 19). The lack of commercial nurseries might be one reason why farmers maintained their own nurseries. Male-headed households and households in the high sales tercile were able to purchase more shoots/grafts (Table 18). 13 Table 17: Type of planting material used by gender of head of household and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Seeds (semente) 75.1%* 92.6% 34.4% 68.7% 1 71.1% 3 55.7% Shoot/Graft (enxerto) 6.1% 1.9% 16.5% 4.7% 1 9.4% 10.4% Local cut (muda) 18.8%* 5.6% 19.2% 0.0%1 0.8% 3 7.8% N= 377 54 224 214 128 566 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 18: Type of planting material by sales categories Sales Categories Total Low Mid High Seeds (semente) 61.5% 62.4% 41.4%2,3 55.5% Shoot/Graft (enxerto) 4.9% 8.9% 12.1% 8.6% Local cut (muda) 4.2% 5.1% 5.0% 4.8% N= 143 157 140 440 <0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 19: Source of planting material by gender of head of household and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Own nursery 72.7% 74.1% 87.6% 56.9%1 73.8%2,3 72.7% Neighboring producers 9.8% 5.6% 5.5% 16.4%1 5.7%2 9.3% Trader 9.0% 9.3% 3.4% 14.4%1 9.9% 9.3% NGO 0.5% 1.9% 0.0% 1.4% 0.7% 0.7% Other 8.0% 9.3% 3.4% 11.0%1 9.9% 8.1% N= 377 54 145 146 141 432 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 20: Source of planting material by sales categories Sales Categories Low Mid High Total Own nursery 70.8% 62.3% 78.2%2 70.5% Neighboring producers 9.7% 13.1% 6.0% 9.6% Trader 6.2% 15.4% 8.3% 10.1% NGO 0.0% 0.8% 1.5% 0.8% Other 13.3% 8.5% 6.0% 9.0% N= 113 130 133 376 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 14 In the vast majority of instances where farmers responded “other” in Table 19 and Table 20, the source was from their own trees (“seeded personally”). Other sources included family or the government. Table 21: Existence of nursery in the community by gender of head of household and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total No 82.4% 80.8% 96.5% 77.9%1 68.4%2,3 82.2% Yes 10.0% 6.4% 3.0% 9.5% 17.1%2,3 9.2% Don't know 7.6%* 12.8% 0.5% 12.5%1 14.5%3 8.7% N= 803 203 369 367 269 1005 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 22: Existence of nursery in the community by sales categories Sales Categories Total Low Mid High No 78.3% 79.5% 91.7%2,3 83.2% Yes 10.9% 9.0% 3.2%2,3 7.7% Don't know 10.9% 11.5% 5.1%2,3 9.1% N= 258 288 277 823 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Post-harvest loss Post-harvest loss was reported in roughly half of surveyed households. Farmers in Nampula province most frequently suffered losses, with close to 60% indicating they had losses in the most recent harvest (Table 23). The two main sources of loss across all farmers were spoilage (61.2%) and theft (37.8%). Female-headed households and households in Zambezia province were most likely to be affected by these two sources of loss (Table 25). Table 23: Post-harvest loss from most recent harvest by gender of head of household and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total No 44.4%* 35.0% 48.9% 33.1%1 46.2%2 42.5% Yes 51.5% 55.7% 50.5% 58.9% 45.5%2 52.2% Don't know 4.2%* 9.4% 0.5% 8.1%1 8.3%3 5.3% N= 793 203 370 360 266 996 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 15 Table 24: Post-harvest loss from most recent harvest by sales categories Sales Categories Total Low Mid High No 43.6% 42.2% 36.5% 40.7% Yes 49.8% 51.2% 60.1% 53.7% Don't know 6.6% 6.6% 3.3% 5.5% N= 257 287 271 815 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 25: Sources of loss by gender of head of household and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Spoilage 57.9%* 73.2% 48.1% 59.7%1 84.5%2,3 61.2% Theft 36.1% 43.8% 32.1% 30.3% 59.6%2,3 37.8% Other 30.0%* 16.7% 36.6% 26.6%1 13.3%2,3 27.1% N= 409 114 189 213 121 523 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Note: More than one response is possible for this question, therefore disaggregated proportions may sum to more than 100%. Table 26: Source of loss by sales categories Sales Categories Total Low Mid High Spoilage 57.4% 69.9%1 51.1%2 59.3% Theft 40.2% 38.8% 29.0% 35.6% Other 25.9% 17.1% 31.8%2 25.1% N= 129 149 163 440 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Note: More than one response is possible for this question, therefore disaggregated proportions may sum to more than 100%. The most frequently cited “other” sources of loss were disease, pests, and uncontrolled burning. Additional responses included: weather (drought, wind, or sun), lack (or delay in delivery) of spray, and wild animals. The most common pests and diseases affecting production were the coconut insect, cashew beetle, and blemishing (Table 27). The cashew beetle appears to be particularly problematic for female-headed households and for farmers in Zambezia. 16 Table 27: Main pests/diseases affecting trees by gender of head of household and by province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total None 1.0%* 0.1% 0.5% 1.8%1 0.0%2 0.8% Atracnose 23.3% 22.3% 27.5% 18.1%1 23.8% 23.1% Mildew 23.4%* 34.2% 30.4% 21.8%1 24.1% 25.6% Spots/Blemishes 61.7% 60.8% 57.4% 56.8% 73.4%2,3 61.5% Coconut Insect 41.8% 38.0% 38.2% 43.2% 42.1% 41.1% Cashew Beetle 44.1%* 52.9% 32.3% 50.4%1 58.3%3 45.9% Ants 53.1% 49.0% 35.9% 68.5%1 52.8%2,3 52.3% Other 10.6%* 6.5% 9.5% 12.8%2 6.0% 9.8% N= 802 203 369 366 269 1004 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Note: More than one response is possible for this question, therefore disaggregated proportions may sum to more than 100%. Table 28: Main pests/diseases affecting trees by sales categories Sales Categories Low Mid High Total None 2.3% 0.9% 0.0%3 1.0% Atracnose 25.7% 20.7% 26.6% 24.3% Mildew 20.7% 22.5% 17.6% 20.3% Spots/Blemishes 52.6% 59.8% 69.6%2,3 60.8% Coconut Insect 36.4% 41.0% 39.3% 39.0% Cashew Beetle 39.5% 55.5%1 48.5% 48.2% Ants 61.7% 49.6%1 40.8%2,3 50.4% Other 12.4% 10.4% 7.1% 9.9% N= 257 291 275 823 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Note: More than one response is possible for this question, therefore disaggregated proportions may sum to more than 100%. Other pests/diseases mentioned include: fungus and unknown pests. Producers were asked whether they used chemicals or spraying services for their trees in order to minimize losses. Female-headed households were less likely to use chemicals or spraying services. Farmers in Cabo Delgado appear to have substantially greater access and/or means available to procure chemical products, having reported their use at triple the rate of the other two provinces (Table 29). Not surprisingly, farmers in the highest sales category were more likely to use chemicals and spraying services compared to farmers with lower sales. It should be noted that spraying services were reported at a much higher rate than chemical use (45.2% vs. 19.9%), although spraying inherently involves using chemicals. 17 Table 29: Use of chemical products or spraying services by gender of head of household and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Do you use any chemical products (pesticides, fungicides, fertilizer)? No 71.8%* 79.3% 64.0% 80.0%1 77.0%3 73.3% Yes 21.5%* 13.8% 35.8% 11.0%1 10.4%3 19.9% Don't know 6.7% 6.9% 0.3% 9.0%1 12.6%3 6.8% N= 801 203 369 365 269 1004 Have you used any spraying services? No 48.8%* 69.7% 49.2% 48.8% 63.9%2,3 53.0% Yes 49.3%* 28.4% 50.8% 49.3% 32.0%2,3 45.2% Don't know 1.9% 2.0% 0.0% 1.9%1 4.1%3 1.8% N= 803 201 370 365 269 1004 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 30: Use of chemicals or spraying services by sales categories Sales Categories Low Mid High Total Do you use any chemical products (pesticides, fungicides, fertilizer)? No 82.0% 78.6% 61.4%2,3 73.8% Yes 9.8% 12.1% 37.5%2,3 20.0% Don't know 8.2% 9.3% 1.1%2,3 6.2% N= 255 290 277 822 Have you used any spraying services? 25.6% 20.7% 26.5% 24.1% No 66.5% 60.8% 26.0%2,3 50.90 Yes 32.7% 37.1% 72.9%2,3 47.8% Don't know 0.8% 2.1% 1.1% 1.3% N= 254 291 277 822 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Reasons for planting new trees Overall, most farmers responded that they intended to plant trees in the upcoming year. Approximately 85% of all farmers reported affirmatively, with a slightly lower proportion of female-headed households vs. male-headed households (Table 31). For those households that reported they did not intend to plant trees, lack of money and weak demand were the most cited reasons (Table 33). Farmers in Cabo Delgado were more likely to cite weak demand/low prices as a reason for not planting in the upcoming year, granted the absolute number of farmers this comprises was low (45.8% of N=48, Table 33). 18 Table 31: Intent to plant trees next year, by gender head of household and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total No 9.5% 14.3%* 12.2% 9.5% 9.3% 10.4% Yes 88.1% 74.9%* 87.0% 83.4% 85.9% 85.4% Don't know 2.5% 10.8%* 0.8% 7.1%1 4.8%3 4.2% N= 804 203 370 367 270 1007 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 32: Intent to plant trees next year, by sales categories Sales Categories Low Mid High Total No 15.1% 9.0%1 10.1% 11.3% Yes 79.8% 84.1% 86.6%3 83.6% Don't know 5.0% 6.9% 3.2%2 5.1% N= 258 289 277 824 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 33: Reasons for not planting trees next year, by gender head of household and by province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Lack of money 51.8% 64.3% 41.7% 62.7%1 65.5%3 55.5% Weak demand/low prices 27.1% 21.4% 45.8% 17.6%1 3.4%3 25.0% Already produce all that I want or am able to 0.0% 0.0% 2.1% 0.0% 0.0% 0.8% Other 21.2% 14.3% 10.4% 19.6% 31.0%3 18.8% N= 85 42 48 51 29 128 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 34: Reasons for not planting trees next year by sales categories Sales Categories 19 Low Mid High Total Lack of money 44.2% 66.7% 59.4% 56.1% Weak demand/low prices 32.6% 12.8% 28.1% 24.6% Already produce all that I want or am able to 23.3% 20.5% 12.5% 19.3% Other 23.3% 20.5% 12.5% 19.3% N= 43 39 32 114 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Other reasons cited for not anticipating planting in the upcoming year included lack of land, lack of labor, age/sickness, and lack of motivation. Labor On average, 30% of surveyed farmers reported using contracted labor. This percentage was higher in Cabo Delgado (41%), perhaps reflecting the somewhat larger scale of farmers surveyed in that province. Male-headed households were also significantly more likely to contract labor (32% vs. 20%, Table 35). Table 35: Use of contracted labor by gender of head of household and by province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total No 67.5%* 80.3% 58.9% 76.5%1 77.0%3 70.1% Yes 32.2%* 19.7% 41.1% 23.5%1 22.3%3 29.7% Don't know 0.2% 0.0% 0.0% 0.0% 0.7% 0.2% N= 801 203 370 366 269 1005 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 36: Use of contracted labor by sales categories Sales Categories Low Mid High Total No 89.8% 73.4%1 40.8%2,3 67.5% Yes 10.2% 26.6%1 59.2%2,3 32.5% Don't know 0.0% 0.0% 0.0% 0.0% N= 254 290 277 821 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. The most common form of payment for hired labor was cash, with roughly 65% of farmers hiring labor reporting to use this form of payment. Payment in cash was significantly higher in Cabo Delgado compared to the other two provinces, perhaps suggesting a tighter labor market for agricultural workers who demand payment in cash vs. cashew/other products (Table 37). Table 37: Method of payment for hired labor by gender head of household and by province Gender HoH Province 20 Male Female Cabo Delgado Nampula Zambezia Total Cash 64.6% 59.5% 88.1% 32.2%1 47.4%3 63.7% Exchange of cashew products 15.2% 8.1% 7.3% 16.1%1 29.8%3 14.2% Exchange of other products 20.2% 32.4% 4.6% 51.7%1 22.8%2,3 22.0% N= 257 37 151 87 57 295 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 38: Method of payment for hired labor by sales categories Sales Categories Low Mid High Total Cash 51.9% 45.8% 70.7%2 62.0% Exchange of cashew products 25.9% 23.6% 7.9%2 14.1% Exchange of other products 22.2% 30.6% 21.3% 24.0% N= 27 72 164 263 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Cashew nut harvesting methods Nearly all farmers surveyed reported harvesting fruit once it fell from the tree (95.6%, Table 39). Once harvested, most farmers dried using the ground, most typically within farmers’ homes (84.4%, Table 41). While still not very prevalent, households in Zambezia reported using sacks more frequently for drying (14.1%, Table 41). Households in Cabo Delgado were more likely to dry cashew nuts for a shorter period of time, between 1-3 days, then households in the other two provinces. By contrast, households in Nampula and Zambezia more commonly dried their cashew nuts for a longer period (Table 43). Table 39: Cashew harvesting method by gender head of household and by province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Pick the fruit from the tree 4.6% 4.0% 1.6% 5.8%1 6.4%3 4.4% Collect fruit after it falls from tree 95.4% 96.0% 98.4% 94.2%1 93.6%3 95.6% N= 796 202 369 362 267 998 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 40: Cashew harvesting method by sales categories 21 Sales Categories Low Mid High Total Pick the fruit from the tree 4.3% 3.8% 6.5% 4.9% Collect fruit after it falls from tree 95.7% 96.2% 93.5% 95.1% N= 254 286 277 817 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 41: Surface used to dry cashew nuts by gender of head of household and by province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Solid ground 83.3% 88.2% 83.0% 86.8% 82.9% 84.4% Canvas/Tarp 2.7% 3.4% 3.5% 2.5% 2.6% 2.9% Sacks 9.6% 3.4%* 4.3% 8.2%1 14.1%2 8.4% Bamboo/cane/stick mat 2.5% 1.5% 3.8% 2.2% 0.4% 2.3% Other 1.9% 3.4% 5.4% 0.3%1 0.0% 2.1% N= 802 203 370 365 269 1004 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 42: Surface used to dry cashew nuts by sales categories Sales Categories Low Mid High Total Solid ground 89.8% 82.0% 76.3% 82.5% Canvas/Tarp 1.2% 2.4% 6.1% 3.3% Sacks 5.5% 10.4% 13.3% 9.8% Bamboo/cane/stick mat 2.3% 3.1% 0.7% 2.1% Other 1.2% 2.1% 3.6% 2.3% N= 256 289 278 823 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 43: Cashew nut drying times by gender head of household and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia 1 - 3 days 34.8% 49.0%* 53.1% 17.5% 43.5% 37.6% 4 - 5 days 29.1% 31.7% 25.2% 34.5% 29.0% 29.6% More than 5 days 36.2% 19.3%* 21.7% 47.9% 27.5% 32.8% N= 802 202 369 365 269 1003 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 44: Cashew nuts drying time by sales categories Sales Categories 22 Low Mid High Total 1 - 3 days 33.5% 27.8%1 29.2%2,3 30.0% 4 - 5 days 33.5% 31.6% 27.4% 30.8% More than 5 days 33.1% 40.5%1 43.3%2 39.2% N= 254 291 277 822 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Storage practices and equipment Storage practices were fairly similar across all provinces, gender, and sales categories. The majority of farmers reported storing their cashew production in sacks (76%) with the remaining most frequently piling their harvest outside (22%, Table 45). The vast majority of farmers reported that the cashew storage locations they used were ventilated (Table 47). The reported need for additional equipment for farming and/or processing was universal at 99% of farmers (Table 49 and Table 50). Table 45: Cashew nut storage practices by gender of head of household and by province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Sacks 77.3% 69.2%* 82.9% 69.1%1 74.0%3 75.5% Pile outdoors 20.4% 28.9%* 13.8% 29.%1 24.2%3 22.1% Boxes 1.1% 1.0% 1.9% 1.1% 0.0%3 1.1% Other 1.2% 1.0% 1.4% 0.8% 1.9% 1.3% N= 805 201 369 369 269 1007 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 46: Cashew nuts storage practices by sales categories Sales Categories Low Mid High Total Sacks 68.3% 74.4% 86.6%2,3 76.6% Pile outdoors 27.8% 25.3% 11.6%2,3 21.5% Boxes 1.5% 0.0%1 1.1% 0.8% Other 2.3% 0.3%1 0.7% 1.1% N= 259 289 277 825 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 47: Presence of ventilation in storage facility by gender of head of household and by province 23 Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total No 2.9% 8.4%* 1.6% 5.2%1 5.6%3 4.0% Yes 93.5% 85.2%* 98.1% 89.6%1 86.6%3 91.9% Don't know 3.6% 6.4% 0.3% 5.2%1 7.8%3 4.1% N= 801 203 370 365 269 1004 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 48: Presence of ventilation in storage facility by sales categories Sales Categories Low Mid High Total No 2.7% 6.6%1 2.9%2 4.1% Yes 92.2% 89.3% 96.4%2,3 92.6% Don't know 5.1% 4.1% 0.7%2,3 3.3% N= 255 290 277 822 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 49: Need for material/new equipment to produce/process cashew nuts by gender of head of household and by province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total No 0.1% 0.5% 0.3% 0.0% 0.0% 0.1% Yes 99.4% 99.0% 99.7% 99.1% 99.2% 99.4% Don't know 0.5% 0.5% 0.0% 0.9% 0.8% 0.5% N= 784 196 369 351 259 979 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 50: Need for material/new equipment to produce/process cashew nuts by sales categories Sales Categories Low Mid High Total No 0.0% 0.0% 0.4% 0.1% Yes 98.8% 99.3% 99.6% 99.2% Don't know 1.2% 0.7% 0.0% 0.6% N= 247 276 274 797 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 24 Production Practices Farmers were asked about use of new techniques and technologies. Adoption rates were high (above 95%) across gender, province, and sales tercile lines (Table 51 and Table 52). The most prevalent practices cited were cessation of crop residue burning, canopy pruning, and weeding; each practice had a total subscription of nearly 80% (Table 55). Application of organic inputs, grafting, and fungicide were at the low end with less than 6% of producers using these techniques. Fertilizer use was significantly higher in Cabo Delgado (22.9%) than in the other regions (both under 3%). It should be noted that this baseline survey did not delve into details on the quality of the techniques/technologies being implemented. For instance, while canopy pruning was commonly practiced, the extent to which this pruning was done well cannot be ascertained from these figures. Intercropping was practiced significantly less in the high sales tercile (24.1%) as compared to the other sales categories (over 40% each). The use of fertilizer and spraying were significantly higher in the top sales category (21% and 50.8%, respectively). The percentage of farmers fertilizing in the low and mid categories was below 7% (Table 56). In Table 53 and Table 54, the definition of improved techniques or technologies was limited to a smaller portfolio of improved practices: spraying, fertilizer, fungicide, grafting, and the use of organic inputs. Using this definition, only 40.5% of all farmers sampled were applying these improved practices. Farmers in Cabo Delgado were significantly more likely to apply one of these practices than farmers in the other provinces (51.5% vs. 39% and 27.4%). These practices were also more common among male-headed households (43.4% vs. 29%). Given the near universal prevalence of weeding and the avoidance of burning land or crop residue, it was decided that these did not warrant inclusion as the types of ‘improved’ techniques that the MozaCajú project will aim to implement. As such, the figure of 40.5% of farmers should be seen as the ‘official’ baseline figure used in reporting the percentage of farmers applying improved techniques or technologies. Improved production techniques and technologies Table 51: Effective area under improved techniques or technologies (inclusive of all practices initially listed in the baseline) by gender of HoH and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Avg. effective area (ha) 4.42* 2.87 5.39 3.54 1 3.1 3 4.11 N= 799 201 369 364 267 1000 Avg. # hectares (effective area) under improved techniques/technologies 4.08* 2.72 5.27 2.96 1 2.92 3 3.81 N= 784 194 365 355 258 978 % farmers applying improved techniques/technologies 98.2% 96.5% 98.7% 98.6% 95.8%2,3 97.9% N= 805 203 369 369 269 1008 *p<0.10: male different than female p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 25 Table 52: Effective area under improved techniques or technologies (inclusive of all practices initially listed in the baseline) by sales categories Sales Categories Low Mid High Total Avg. effective area (ha) 1.84 2.85 8.852,3 4.56 N= 255 287 275 818 Avg. # hectares (effective area) under improved techniques/technologies 1.69 2.62 8.142,3 4.18 N= 254 281 270 805 % farmers applying improved techniques/technologies 99.7% 96.8% 98.5% 98.3% N= 258 291 277 826 p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 53: Effective area under improved techniques or technologies (reduced # of practices) by gender of HoH and province Gender HoH Province Male Female Cabo Delgado Nampula Zambezia Total Avg. effective area (ha) 6.44* 4.54 8.65 4.621 3.223 6.18 N= 359 58 191 142 85 418 Avg. # hectares (effective area) under improved techniques/technologies 4.81* 3.28 6.76 2.84 1 2.68 3 4.59 N= 359 58 191 142 85 418 % farmers applying improved techniques/technologies 43.4%* 29.0% 51.5% 39.0%1 27.4%2,3 40.5% N= 802 203 369 366 269 1004 *p<0.10: male different than female p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 54: Effective area under improved techniques or technologies (reduced # of practices) by sales category Sales Categories Low Mid High Total Avg. effective area (ha) 2.22 3.02 10.992,3 6.57 N= 88 105 171 365 Avg. # hectares (effective area) under improved techniques/technologies 1.77 2.37 7.922,3 4.83 N= 88 105 171 365 % farmers applying improved techniques/technologies 31.7% 34.0% 63.3%2,3 43.1% N= 257 291 275 823 p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 55: Improved techniques and technologies by gender HoH and province 26 Gender HoH Province Male Female Total Cabo Delgado Nampula Zambezia Total Mulching 50.8% 42.6% 49.0% 64.5%1,3 41.0% 39.4% 49.2% Intercrop bean 36.2% 46.5% 38.3% 41.1% 33.1%1,2 41.6% 38.3% Intercrop other 53.3% 57.6% 54.1% 54.4% 50.2%2 59.1% 54.1% Pruning 79.5% 77.7% 79.2% 68.2%1,3 85.3% 85.9% 79.2% Organic inputs 5.4% 5.0% 5.3% 5.5% 6.4% 3.6% 5.3% Fertilizer 10.9% 5.6% 9.9% 22.9%1,3 2.6% 1.8% 9.9% Grafting 2.9% 2.2% 2.7% 1.8% 2.9% 3.8% 2.7% Weeding 79.6% 75.0% 78.6% 86.3% 69.0%1 81.3%2 78.6% Spraying 34.1% 21.1% 31.5% 34.1% 34.1% 24.1%2,3 31.5% Fungicide 1.0% 2.1% 1.2% 2.7%1 0.0% 0.9% 1.2% Burn Avoidance 82.2% 75.5% 80.8% 83.1% 78.8% 80.5% 80.8% N= 805 203 808 369 269 269 907 *p<0.10: male different than female p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 56: Improved techniques and technologies by sales categories Sales Categories Low Mid High Total Mulching 42.9% 43.3% 43.9% 43.4% Intercrop bean 41.3% 42.1% 24.1%2,3 35.8% Intercrop other 53.5% 61.6% 54.1% 56.5% Pruning 80.1% 83.9% 83.0% 82.4% Organic inputs 6.8% 3.2% 4.7% 4.9% Fertilizer 4.6% 6.6% 21.0%2,3 10.8% Grafting 4.3% 4.3% 1.3% 3.3% Weeding 67.0%1,3 80.6% 86.6% 78.4% Spraying 26.6% 26.0% 50.8%2,3 34.5% Fungicide 1.9% 0.8% 1.4% 1.3% Burn Avoidance 86.2% 80.6% 85.3% 83.9% N= 258 291 277 826 p<010; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Training Few farmers (between 3% and 4% of the total) reported receiving short-term agricultural productivity training (Table 57). Among those farmers that did receive training, the types of trainings received are disaggregated by the gender of the head of household, province, and sales categories in Table 59 and Table 60. Significance testing was not carried out for these indicators because of low numbers. Table 57: % of households receiving short-term training by gender HoH and by province 27 Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % farmers receiving short￾term agricultural sector productivity training 3.9%* 0.6% 2.9% 4.6% 1.8% 3.2% N= 805 203 369 369 269 1008 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 58: % of households receiving short-term training by sales categories Sales Categories Total Low Mid High % farmers receiving short-term agricultural sector productivity training 1.8% 4.4% 5.5% 3 4.0% N= 258 291 277 826 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 59: % of farmers receiving specific trainings by gender of HoH and province (of those farmers who reported receiving training) Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Pruning 79.1% 100.0% 67.3% 82.0% 100.0% 79.8% Spacing 46.8% 0.0% 34.7% 36.0% 100.0% 45.1% Weeding 76.7% 100.0% 42.5% 93.3% 100.0% 77.5% Spraying 51.3% 0.0% 38.0% 56.6% 50.0% 49.5% Drying 26.1% 0.0% 14.8% 24.7% 50.0% 25.2% Intercropping 33.9% 0.0% 45.4% 19.7% 50.0% 32.7% Planting 37.6% 0.0% 25.7% 24.7% 100.0% 36.3% Grafting 14.5% 0.0% 17.1% 1.7% 50.0% 14.0% Organic 10.7% 0.0% 8.5% 0.0% 50.0% 10.3% Harvest Timing 35.6% 100.0% 31.8% 38.2% 50.0% 37.9% Sorting 44.8% 100.0% 17.2% 50.2% 100.0% 46.7% Storage 30.5% 100.0% 27.5% 31.5% 50.0% 32.9% Fertilizer Use 24.3% 0.0% 15.1% 6.7% 100.0% 23.4% Pesticide Use 14.3% 0.0% 8.5% 6.7% 50.0% 13.8% Burn Avoidance 66.6% 0.0% 52.6% 61.4% 100.0% 64.3% Mulching 37.8% 100.0% 28.4% 44.4% 50.0% 40.0% Other 10.7% 0.0% 8.5% 0.0% 50.0% 10.3% N= 32 1 11 17 5 33 Table 60: % of farmers receiving specific trainings by sales categories 28 Sales Categories Total Low Mid High Pruning 100.0% 71.9% 80.3% 79.8% Spacing 75.8% 48.8% 32.5% 45.1% Weeding 100.0% 80.4% 68.1% 77.5% Spraying 24.2% 53.7% 53.8% 49.5% Drying 24.2% 19.1% 30.7% 25.2% Intercropping 0.0% 38.0% 38.5% 32.7% Planting 75.8% 34.1% 25.9% 36.3% Grafting 0.0% 21.3% 12.2% 14.0% Organic 0.0% 19.1% 6.1% 10.3% Harvest Timing 48.4% 41.2% 31.7% 37.9% Sorting 100.0% 21.3% 51.5% 46.7% Storage 48.4% 22.6% 36.8% 32.9% Fertilizer Use 51.6% 22.6% 15.4% 23.4% Pesticide Use 0.0% 19.1% 13.6% 13.8% Burn Avoidance 75.8% 53.0% 70.2% 64.3% Mulching 48.4% 53.0% 26.4% 40.0% Other 0.0% 19.1% 6.1% 10.3% N= 5 13 15 33 Access to extension Access to extension was gender blind (Table 61). Farmers in Zambezia reported very low access to extension officers (1.9%) as compared to farmers in Cabo Delgado (17.1%) and Nampula (15.3%). While still low on an absolute basis, three times as many farmers (21.3%) in the highest sales tercile reported having access to extension as compared to the lowest sales tercile (7.1%) (Table 62). Table 61: Extension access by gender HoH and province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Yes 12.3% 12.4% 17.1% 15.3% 1.9%2,3 12.4% No 79.2% 80.6% 82.9% 72.2%1 85.0%2 79.5% Don't know 8.5% 7.0% 0.0% 12.5%1 13.1%3 8.2% N= 803 201 369 367 267 1003 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 62: Extension access by sales categories 29 Sales Categories Total Low Mid High Yes 7.1% 10.7% 22.0%2,3 13.4% No 85.4% 78.3% 74.0%3 79.0% Don't know 7.5% 11.0% 4.0%2 7.6% N= 254 290 277 821 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Extension knowledge For the small number of farmers that reported using extension services, most were confident in the abilities of the officer supporting them (70%, Table 63). Table 63: % of farmers satisfied with the knowledge of their extension officer by gender HoH and province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Yes 73.3% 59.3% 68.3% 74.6% 50.0% 70.0% No 19.8% 33.3% 31.7% 15.3% 0.0% 22.3% Don't know 6.9% 7.4% 0.0% 10.2% 50.0% 7.7% N= 101 27 63 59 8 130 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 64: % of farmers satisfied with the knowledge of their extension officer by sales categories Sales Categories Total Low Mid High Yes 54.2% 62.5% 82.0% 70.9% No 29.2% 25.0% 16.4% 21.4% Don't know 16.7% 12.5% 1.6% 7.7% N= 24 32 61 117 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Extension quality It should be noted that there was an error in the coding of the tables for the responses for this question. The first response that should have been labeled “Very Unsatisfied” was errantly labeled “Very Satisfied”. Therefore, any interpretations of the results in this table should be made cautiously. Comparing Cabo Delgado and Nampula, where comparatively more farmers had access to extension officers, levels of satisfaction with the quality of extension was higher in Nampula (Table 65). 30 Table 65: % of farmers satisfied with the quality of extension services received, by gender HoH and province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Very unsatisfied 29.5% 31.8% 29.9%1 2.0% 0.0% 29.9% Unsatisfied 25.3% 45.5% 29.9%1,3 40.8%2 100.0% 29.9% Satisfied 42.1% 22.7% 37.6%1 53.1% 0.0% 37.6% Very satisfied 3.2% 0.0% 2.6% 4.1% 0.0% 2.6% N= 95 22 63 49 5 117 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 66: % of farmers satisfied with the quality of extension services received, by sales category Sales Categories Total Low Mid High Very unsatisfied 20.0% 33.3% 27.6% 28.2% Unsatisfied 26.7% 30.0% 31.0% 30.1% Satisfied 53.3% 36.7% 36.2% 38.8% Very satisfied 0.0% 0.0% 5.2% 2.9% N= 15 30 58 103 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Production and Sales Average sales Self-reported data on sales are often problematic in terms of accuracy. Surveyed farmers reported receiving, on average, $117 in total sales (median: $40) across all cashew products. Roughly 75% of surveyed farmers reported selling cashew nuts (826 farmers, Table 67), while about half (53 farmers) reported receiving income from the sale of cashew byproducts (wine, juice, and fruit). Farmers in Cabo Delgado reported significantly higher levels of sales per farmer than in the other two provinces. The difference is likely explained by the much higher area under production and the higher number of trees cultivated by the average farmer in Cabo Delgado, compared to farmers in the other two provinces. This is also consistent with the greater number of trees in peak productivity years and use of fertilizer in Cabo Delgado. It should be noted, however, that in a number of the sampled districts of Cabo Delgado – namely Metuge, Macomia, and Chiure – large numbers of producers were not actively selling. The low denominator for Cabo Delgado reflects larger numbers of non-selling producers. Any interpretation the sales data should take this into account. Table 67: Average and median sales per farmer (USD) in the previous 12 months, by gender of HoH and province 31 Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Avg. sales per farmer (nuts, wine, juice, and fruit) (USD) 125.33* 81.1 244.94 79.151 45.993 116.97 Median sales per farmer (nuts, wine, juice, and fruit) (USD) 41.67 26.67 80 33.67 31.67 40 N= 670 156 237 345 244 826 Avg. sales per farmer cashew nuts only (USD) 111.64 74.81 226.49 71.841 41.763 104.52 Median sales per farmer cashew nuts only (USD) 33.33 26.67 53.33 26.67 26.67 26.67 N= 601 144 199 330 216 745 Avg. sales per farmer other (wine, juice and fruit) (USD) 39.77* 23.74 84.75 17.241 15.493 37.24 Median sales per farmer other (wine, juice, and fruit) (USD) 15.88 6.67 34.74 9.74 11.67 13.33 N= 424 80 153 207 144 503 *p<0.10: Female different than Male. p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 68: Average and median sales per farmer (USD) in the previous 12 months, by sales category Sales Categories Total Low Mid High Avg. sales per farmer (nuts, wine, juice, and fruit) (USD) 14.53 39.15 294.002,3 117 Median sales per farmer (nuts, wine, juice, and fruit) (USD) 16.67 40 133.33 40 N= 258 291 277 826 Avg. sales per farmer cashew nuts only (USD) 13.8 31.7 260.72,3 104.5 Median sales per farmer cashew nuts only (USD) 13.33 26.67 98.13 26.67 N= 215 276 254 745 Avg. sales per farmer other (wine, juice and fruit) (USD) 6.2 15.3 74.32,3 37.2 Median sales per farmer other (wine, juice, and fruit) (USD) 5 11.67 33.33 13.33 N= 124 173 206 503 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 32 Variation in production Farmers, by and large, reported a decrease in production over the past five campaigns. On average, 71-73% of farmers reported declining production (Table 69 and Table 70). Table 69: Variation in production over the last five campaigns, by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % Farmers reduced production 70.4% 74.2% 74.3% 71.1% 67.0% 71.2% % Farmers maintained production 21.6% 15.7% 15.1% 21.6% 26.2%3 20.4% % Farmers increased production 7.9% 10.1% 10.5% 7.3% 6.7% 8.4% N= 795 198 370 356 267 993 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 70: Variation in production over the last five campaigns by sales category Sales Categories Total Low Mid High % Farmers reporting reduced production 76.2% 74.7% 68.5% 73.1% % Farmers reporting maintained production 14.5% 18.7% 22.0% 18.5% % Farmers reporting increased production 9.3% 6.6% 9.5% 8.4% N= 248 289 273 810 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. For those smaller number of farmers reporting an increased level of production, the main reasons cited included an increased number of trees in production and better management of trees (Table 71 and Table 72). Table 71: Reasons for increase in production by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Increase in number of trees in production 53.8% 48.0% 38.0% 56.0% 78.7%3 52.5% Better management of trees 42.9% 43.9% 39.4% 24.8% 78.7%2,3 43.1% Use of better/more inputs 4.6% 5.6% 5.8% 6.6% 0.0% 4.8% Increased availability of labor 11.6% 11.1% 24.6% 0.0%1 0.0%3 11.5% More profitable to produce 7.2% 12.4% 0.7% 16.1%1 13.8% 8.4% Obtained credit for investment 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Other 22.5% 5.8% 2.0% 36.7%1 27.7%3 18.6% N= 63 20 39 26 18 83 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 33 Table 72: Reasons for increase in production by sales category Sales Categories Total Low Mid High Increase in number of trees in production 55.5% 54.1% 38.4% 48.4% Better management of trees 46.4% 52.4% 40.0% 45.6% Use of better/more inputs 0.0% 3.6% 8.3% 4.2% Increased availability of labor 8.8% 11.7% 15.8% 12.3% More profitable to produce 18.4% 1.5% 9.3% 10.2% Obtained credit for investment 0.0% 0.0% 0.0% 0.0% Other 21.4% 11.7% 31.2% 22.6% N= 23 19 26 68 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. “Spraying became available” compromised the vast majority of “Other” responses for why production had improved. Among those farmers reporting production decreases, the most common reasons given were tree diseases and pests, at 67% and 61% (Error! Reference source not found. and Table 74). Farmers in Zambezia and Nampula were more likely to report declining production due to the age of their trees. Production decreases due to tree age were also most common for farmers in the lowest sales tercile. Table 73: Reasons for decrease in production by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Disease (trees) 65.9% 72.8% 81.0% 64.3%1 50.9%2,3 67.4% Pests 60.1% 62.6% 60.4% 72.4%1 44.2%2,3 60.6% Trees very old 24.8% 22.4% 9.7% 26.4%1 43.7%2,3 24.3% Lack of labor 19.1%* 27.1% 20.2% 20.4% 22.2% 20.8% Not profitable to produce 10.3% 7.5% 7.5% 3.1% 22.3%2,3 9.7% Climate change 6.7%* 14.3% 4.7% 6.3% 16.5%2,3 8.3% Erosion 3.3%* 0.7% 1.2% 3.0% 4.9%3 2.8% Other 17.6% 16.2% 13.1% 25.4%1 12.6%2 17.3% N= 560 147 275 253 179 707 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 34 Table 74: Reasons for decreases in production by sales category Sales Categories Total Low Mid High Disease (trees) 49.2% 66.3%1 79.1%2,3 64.9% Pests 55.5% 59.9% 60.6% 58.7% Trees very old 27.1% 30.8% 17.1%2,3 25.3% Lack of labor 21.7% 23.1% 23.9% 22.9% Not profitable to produce 9.3% 11.9% 6.5% 9.4% Climate change 9.8% 9.8% 8.5% 9.4% Erosion 3.4% 3.2% 1.6% 2.8% Other 27.1% 10.9%1 10.6%3 16.0% N= 189 216 187 593 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Theft, lack of spraying services, uncontrolled burning, wild animals, and weather (drought) were the most common (in order of frequency) “other” reasons given for decreases in production. Prices and product types Few farmers were satisfied with the prices they received for their marketed product. Low levels of satisfaction were consistent across gender, province, and sales levels (Table 75 and Table 76). Table 75: % of farmers satisfied with prices received for cashew nuts by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % Farmers satisfied with price received for cashew nuts with the shell? 4.2% 2.5% 7.7% 2.1%1 0.9%3 3.9% N= 794 195 368 354 267 989 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 76: % of farmers satisfied with prices received for cashew nuts by sales categories Sales Categories Total Low Mid High % Farmers satisfied with price received for cashew nuts with the shell? 3.9% 3.9% 4.5% 4.1% N= 246 288 273 807 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 35 A higher proportion of farmers in Zambezia and Nampula reported sales of cashew byproducts. This was particularly true of cashew wine where between one-quarter and one-third of farmers in those two provinces reported sales(Table 77). Interestingly, farmers in the highest sales tercile also reported higher sales of wine and fruit (Table 79 and Table 82), suggesting that the higher earning farmers in Nampula and Zambezia have more opportunities to market their byproducts. Table 77: % of farmers producing cashew wine by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % producing cashew wine 25.1%* 15.9% 14.6% 23.0%1 35.4%2,3 23.3% N= 804 198 368 365 269 1003 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 78: % of farmers producing cashew wine by sales category Sales Categories Total Low Mid High % Producing cashew wine 22.0% 30.4%1 31.8%3 28.3% N= 253 291 274 817 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 79: % of farmers producing cashew juice by gender of HoH and province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % Producing cashew juice 9.4%* 5.8% 4.3% 12.6%1 9.5%3 8.7% N= 795 195 367 358 264 990 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 80: % of farmers producing cashew juice by sales category Sales Categories Total Low Mid High % producing cashew juice 11.6% 9.6% 10.2% 10.4% N= 248 288 273 808 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 36 Table 81: % of farmers selling cashew fruit by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % selling cashew fruit 34.2%* 24.9% 31.3% 38.8%1 25.1%2 32.4% N = 802 203 369 366 269 1004 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 82: % of farmers selling cashew fruit by sales category Sales Categories Total Low Mid High % selling cashew fruit 28.2% 37.2%1 51.2%2,3 39.1% N= 257 291 275 823 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Buyers A reasonably small percentage of farmers reported that they had encountered a situation where a buyer promised to purchase cashew nuts but did not show or failed to follow through on a purchase (less than a quarter of farmers overall) (Table 83 and Table 84). Table 83: % of farmers encountering a situation where a buyer promised to buy cashew nuts but did not show by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % of farmers 21.6%* 13.8% 16.0% 23.1%1 21.6% 20.1% N= 792 195 368 355 264 987 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 84: % of farmers encountering a situation where a buyer promised to buy cashew nuts but did not show by sales category Sales Categories Total Low Mid High % of farmers 16.9% 21.8% 28.8%3 22.6% N= 248 289 271 808 1: Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 37 When asked what was most important when marketing their product, most farmers reported price as the determining factor (84%, Table 85 and Table 86). Buyers appear to mostly compete on price, infrequently competing on the basis of additional service offerings. Only 7.5% of survey respondents reported having inputs advanced to them by buyers in exchange for supply guarantees (Table 87). Table 85: Farmers’ most important factor in choosing a buyer by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Best price offered 83.6% 87.3% 77.7% 85.6%1 92.1%2,3 84.3% Confidence that sale will go through 1.8% 3.0% 2.2% 1.7% 1.9% 2.0% Offers inputs and other services 1.1% 0.5% 0.8% 0.6% 1.9% 1.0% Only one buyer (no choice) 6.3% 5.6% 4.1% 10.1%1 3.7%2 6.2% Other 7.2% 3.6% 15.3% 2.0%1 .4%3 6.5% N= 793 197 367 355 267 990 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 86: Farmers’ most important factor in choosing a buyer by sales category Sales Categories Total Low Mid High Best price offered 82.9% 89.5% 79.7%2 84.2% Confidence that sale will go through 2.4% 1.4% 1.5% 1.7% Offers inputs and other services 0.8% 1.4% 0.4% 0.9% Only one buyer (no choice) 10.0% 3.8%1 4.4%3 5.9% Other 4.0% 3.8% 14.0%2,3 7.3% N= 251 287 271 809 1: Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Almost exclusively, the other reason given for choosing a buyer was that there was no ability to choose (e.g. “never chose”, “isn’t possible to choose”). 38 Table 87: % of farmers that had a buyer advance inputs in exchange for cashew nut supply guarantees by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % of farmers 8.0% 5.4% 5.9% 8.6% 8.3% 7.5% N= 775 186 370 338 253 961 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 88: % of farmers that had a buyer advance inputs in exchange for cashew nut supply guarantees by sales category Sales Categories Total Low Mid High % of farmers 4.7% 9.6% 10.5%3 8.5% N= 235 280 266 781 1: Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Farmers sold cashew nuts an average of one time in the most recent campaign (Table 89 and Table 90). Table 89: Average number of times farmers sold cashew nuts during the most recent campaign in which they sold, by gender of HoH and province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia How many times did farmers sell cashew nuts during most recent campaign 1.3* 1.1 0.7 1.81 1.42,3 1.3 N= 737 181 369 319 229 918 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula; 3Zambezia different than Cabo Delgado Table 90: Average number of times farmers sold cashew nuts during the most recent campaign in which they sold, by sales category Sales Categories Total Low Mid High How many times did farmers sell cashew nuts during most recent campaign 1.4 1.5 1.4 1.5 N= 240 283 261 783 *p<0.101: Mid different than Low; 2: High different than Mid ; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 39 Farmersin Nampula reported significantly higher yields per cultivated tree (4.4 kg/tree, Table 91) relative to the other two provinces. This may suggest that higher sales reported (per farmer) in Cabo Delgado district are solely a function of greater area planted as opposed to higher productivity of farmers in that province. It should be noted that regardless of the relatively higher productivity of Nampula farmers, 4 kg per tree, on an absolute basis, is a low yield compared to potential yields. Overall yield data in the MozaCajú project area show extremely low yields – with an average yield of 3.2 kg per tree. Table 91: Average and median yield in kg per tree cultivated by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Average yield (kg / tree cultivated) 3.2 3.3 2.7 4.41 2.22 3.2 Median yield (kg / tree cultivated) 1.6 1.5 1.5 2 1.1 1.6 N= 709 188 325 328 245 897 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 92: Average and median yield in kg per tree cultivated by sales category Sales Categories Total Low Mid High Average yield (kg / tree cultivated) 2.5 2.7 4.62,3 3.3 Median yield (kg / tree cultivated) 1.5 1.2 2.4 1.6 N= 229 271 248 748 1: Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Management Practices Male farmers that head their household, as well as, farmers in Nampula regardless of gender, were more likely to keep a range of business records including production records, income and expense statements, and household asset records. Roughly 25-35% of farmers in Nampula engaged in these forms of recordkeeping (Table 93 Table 95, Table 97). The average for all farmers in the sample across all forms of recordkeeping was 14-22%. Table 93: % of farmers keeping production records by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % of farmers 15.6%* 6.4% 10.3% 25.8%1 2.2%2,3 13.8% N= 800 203 370 364 269 1003 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 40 Table 94: % of farmers keeping production records by sales category Sales Categories Total Low Mid High % of farmers 13.3% 16.6% 15.6% 15.2% N= 256 289 275 820 p<0.10: 1Mid different than Low; 2High different than Mid ; 3High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 95: % of farmers keeping a record of income and expenses by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % of farmers 17.1%* 3.5% 8.9% 26.8%1 5.2%2 14.4% N= 803 199 370 362 270 1002 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 96: % of farmers keeping a record of income and expenses by sales category Sales Categories Total Low Mid High % of farmers 16.1% 15.1% 17.8% 16.3% N= 254 291 276 821 p<0.10: 1Mid different than Low; 2High different than Mid ; 3High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 97: % of farmers keeping a record of household assets by gender of HoH and province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % of farmers 23.8%* 13.9% 14.9% 35.6%1 12.6%2 21.8% N= 802 202 370 365 270 1005 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 41 Table 98: % of farmers keeping a record of household assets by sales category Sales Categories Total Low Mid High % of farmers 20.3% 26.2% 30.2%3 25.7% N= 256 290 275 821 p<0.10: 1Mid different than Low; 2High different than Mid ; 3High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Few farmers surveyed were either familiar with or practiced organic production. Of the overall farmers sampled, 17% had heard of organic farming (Table 99) while only 13 farmers reported following organic standards as part of their farming practices (Table 103). Table 99: % of farmers that have heard of organic production by gender of HoH and province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % of farmers that have heard of organic production 19.5%* 7.5% 16.8% 18.7% 15.3% 17.1% N= 793 199 369 359 262 992 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 100: % of farmers who have heard of organic production by sales category Sales Categories Total Low Mid High % of farmers that have heard of organic production 12.8% 14.3% 22.3%2,3 16.6% N= 250 286 273 809 p<0.10: 1Mid different than Low; 2High different than Mid ; 3High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some Table 101: % of farmers that are familiar with the requirements for organic production by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % of farmers 22.6% 26.3% 53.2% 8.5%1 4.0%3 22.4% N= 164 19 62 71 50 183 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 42 Table 102: % of farmers that are familiar with requirements for organic production by sales category Sales Categories Total Low Mid High % of farmers 25.0% 13.0% 24.2% 20.9% N= 40 46 62 148 p<.10: 1Mid different than Low; 2High different than Mid ; 3High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 103: % of farmers that follow standards for organic production by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % of farmers 33.3% 0.0% 33.3% 20.0% 0.0% 28.3% N= 39 7 33 10 2 46 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 104: % of farmers that follow standards for organic production by sales category Sales Categories Total Low Mid High % of farmers 18.2% 42.9% 21.4% 25.0% N= 11 7 14 32 p<.10: 1Mid different than Low; 2High different than Mid ; 3High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Group Participation Awareness of producer associations was low among sampled farmers, with only 17% of farmers reporting an association existing in their community (Table 105). Among the 178 farmers who reported that a group did exist in their community, the participation rate was approximately 38% (Table 107). Table 105: % of farmers reporting producer associations in their area by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia No 68.9% 65.7% 92.1% 61.3%1 45.1%2,3 68.4% Yes 19.0% 11.1%* 5.4% 20.2%1 30.5%2,3 17.4% Don't know 12.0% 23.2%* 2.4% 18.5%1 24.4%3 14.1% N= 798 198 369 357 266 992 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado; Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 43 Table 106: % of farmers reporting producer associations in their area by sales categories Sales Categories Total Low Mid High No 69.2% 56.4%1 71.0%2 65.3% Yes 17.6% 23.5% 19.0% 20.2% Don't know 13.2% 20.1%1 9.9%2 14.5% N= 250 289 274 813 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 107: Cashew nut producer group membership by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia No 60.4% 75.0% 65.0% 39.7%1 82.5%2 61.8% Yes 39.6% 25.0% 35.0% 60.3%1 17.5%2 38.2% N= 154 24 20 78 80 178 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 108: Cashew nut producer group membership by sales categories Sales Categories Total Low Mid High No 54.2% 78.6%1 46.0%2 61.9% Yes 45.8% 21.4%1 54.0%2 38.1% N= 48 70 50 168 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Among those farmers who were members of a producer group, about half were members of a basic loose grouping and around half were members of a more formalized association (Table 109). Associational membership was much more common among farmers in Zambezia province. Only around 2% of farmers belonging to a group reported being members of a cooperative. Notably, a higher percentage of those in the high sales tercile were members of an association – 76% (Table 110). 44 Table 109: Membership in different producer groups by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Group 50.0% 33.3% 66.7% 53.5% 26.7% 48.4% Association 48.3% 66.7% 33.3% 46.5% 66.7% 50.0% Cooperative 1.7% 0.0% 0.0% 0.0% 6.7% 1.6% N= 58 6 6 43 15 64 *p<0.10: Female different than Male p<.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 110: Membership in different producer groups by gender of HoH and by province Sales Categories Total Low Mid High Group 77.8% 66.7% 20.7% 48.4% Association 22.2% 26.7% 75.9% 48.4% Cooperative 0.0% 6.7% 0.0% 1.6% Other 0.0% 0.0% 3.4% 1.6% N= 18 15 29 62 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. For those farmers that had joined producer groups, the main motivation for doing so was to obtain better prices for their cashew (Table 111). Table 111: Reasons for joining producers’ groups (among those who are members) by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Obtain better prices 46.6% 55.7% 41.6% 43.3% 64.4% 47.4% Access to credit 15.8% 15.3% 48.2% 7.8%1 27.4% 15.7% Access to inputs 5.1% 15.3% 24.1% 0.0%1 17.8%2 6.0% Access to storage 3.7% 29.0%* 0.0% 8.6% 0.0% 6.0% Other 24.7% 0.0% 0.0% 32.1% 0.0%2 22.5% N= 61 6 7 47 14 68 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 45 Table 112: Reasons for joining producers’ groups (among those who are members) by sales categories Sales Categories Low Mid High Total Obtain better prices 25.5% 40.4% 66.3%3 46.3% Access to credit 8.8% 13.1% 21.2% 15.1% Access to inputs 0.0% 20.5%1 3.4% 6.3% Access to storage 0.0% 11.5% 8.4% 6.3% Exchange of ideas experience 48.1% 23.1% 4.2%3 23.6% N= 22 15 27 64 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Other: Exchange of ideas and exchange of experience. Among the small number of farmers who were members of some type of producer group, around half reported that their groups had the capacity to find buyers (Table 113 and Table 114). Table 113: Group capacity to find buyers by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia No 15.5% 50.0%* 28.6% 9.3% 46.7%2 20.0% Yes 58.6% 16.7%* 57.1% 65.1% 20.0%2 53.8% Don't know 25.9% 33.3% 14.3% 25.6% 33.3% 26.2% N= 58 6 7 43 15 65 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 114: Group capacity to find buyers by sales categories Sales Categories Total Low Mid High No 11.1% 6.3% 35.7%2 21.0% Yes 50.0% 50.0% 60.7% 54.8% Don't know 38.9% 43.8% 3.6%2,3 24.2% N= 18 16 28 62 p<.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 46 The main reason cited by farmers for not joining any type of producer group was due to a lack of perceived benefit in the efficiency of such groups. The lack of existence of such groups was an equally important reason cited (Table 115 and Table 116). Table 115: Reasons for not becoming a member of a producer by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia Don't have time 26.1% 37.5% 46.2% 48.0% 15.4%2,3 27.2% Don't think it will be efficient 33.0% 31.3% 30.8% 28.0% 35.4% 33.0% It's very expensive to be a member 5.7% 0.0% 7.7% 8.0% 3.1% 4.9% Other 35.2% 31.3% 15.4% 16.0% 46.2%2,3 35.0% N= 88 16 13 25 65 103 *p<0.10: Female different than Male p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Table 116: Reasons for not becoming a member of a producer group by sales categories Sales Categories Total Low Mid High Don't have time 48.0% 22%1 17.4%3 27.6% Don't think it will be efficient 16.0% 46%1 26.1% 33.7% It's very expensive to be a member 4.0% 4.0% 8.7% 5.1% Other 32.0% 28.0% 47.8% 33.7% N= 25 50 23 98 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Access to Credit Availability of credit was generally low for all farmers surveyed. Overall, only 10% of farmers were aware that credit-providing organizations existed in their communities (Table 117). Interestingly, farmers with higher cashew sales more frequently reported availability of credit compared to farmers with fewer sales on average, though this is still in relation to low overall figures (Table 118). Table 117: % of farmers reporting the existence of formal/informal credit organizations in their communities by gender of HoH and by province Gender HoH Province Total Male Female Cabo Delgado Nampula Zambezia % of farmers 10.2% 11.2% 11.6% 17.0%1 0.0%2,3 10.5% N= 796 197 370 358 267 995 *p<0.10: Female different than Male; p<0.10: 1Nampula different than Cabo Delgado; 2Zambezia different than Nampula ; 3Zambezia different than Cabo Delgado Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. 47 Table 118: % of farmers reporting the existence of formal/informal credit organizations in their communities by sales category Sales Categories Total Low Mid High % of farmers 5.2% 8.3% 16.0%2,3 10.0% N= 250 289 275 814 p<0.10; 1:Mid different than Low; 2: High different than Mid; 3: High different than Low Note: A sample weight adjustment has been applied to all calculated figures in tables, including N values. In some instances, disaggregated N values (i.e. by province, sales tercile) may not sum to total N value due to rounding. Main Problems in the Community Farmers surveyed identified problems with water, health services, and education most frequently when asked what were the principal problems in their communities. Generally, female-headed households reported problems with access to health services more frequently than their male counterparts. All other problems were cited by fewer than 10% of respondents (Table 119). Table 119: % of farmers reporting 3 principal problems in their communities (in order of priority) by gender of HoH Type of problem Priority 1 Priority 2 Priority 3 Total Male Female Male Female Male Female Problems with water 30.8% 27.6% 24.5% 20.3% 11.8% 11.6% 30.2% Problems with health services 19.0%* 27.6% 19.5% 25.4% 12.4% 9.5% 20.7% Problems with education 11.0% 14.3% 6.2% 6.1% 7.4% 5.3% 11.7% Lack of buyers 10.3% 8.7% 10.2% 10.2% 17.8% 19.6% 10.0% Problems with roads 6.8% 3.1% 8.0% 8.1% 9.5% 10.6% 6.0% Other 5.3% 3.1% 5.8% 2.5% 11.8% 4.2% 4.8% Problems with electricity 3.9% 3.1% 3.3% 5.1% 4.7% 5.8% 3.7% Lack of access to capital and/or inputs 3.0% 1.5% 6.3% 4.6% 3.2%* 9.0% 2.7% Theft/crime 2.5% 5.1% 3.9% 4.6% 3.2% 3.2% 3.0% Under/unemployment 1.4% 0.5% 3.0% 2.5% 3.3% 4.2% 1.2% Climate change 1.4% 2.0% 1.8% 1.5% 1.4% 1.6% 1.5% Destruction of crops by wild animals 1.1% 0.5% 0.9% 1.0% 1.2% 2.1% 1.0% None 0.9% 1.0% 1.9% 1.0% 5.1% 3.7% 0.9% Irresponsibility of men 0.9% 0.0% 0.4% 0.0% 1.0% 0.5% 0.7% Lack of public transport 0.6% 1.0% 2.0% 1.5% 3.3% 3.2% 0.7% Poor community leadership/corruption 0.6% 0.0% 1.8% 1.0% 1.5% 3.2% 0.5% Untimely Pregnancy 0.4% 0.5% 0.3% 1.5% 0.9% 2.1% 0.4% Economic domination by immigrants 0.1% 0.5% 0.3% 3.0% 0.3% 0.5% 0.2% Other (Priority 1,2,3) = hunger, lack of a market/stores, lack of maternity assistance, lack of credit/funds, uncontrolled burns, low prices, lack of training, lack of equipment/tools, lack of old age insurance. 48 Processor Level Findings A total of six companies were interviewed in the study: Cabo Cajú, Export Trading Group, Gani Comercial, Condor, OLAM, and Indo-Africa Trading. Factories were visited in Pemba (Cabo Cajú), Chiure (Export Trading Group), Lumbo (Gani Comercial), Monapo (OLAM), Nametil (Condor), Angoche (Gani Comercial), Anchilo (Condor), and Murrupula (Indo-Africa). Because Cabo Cajú is not currently operating, this company is not included in the baseline project statistics, although the project has plans to collaborate with any entity that re-launches operations at this specific site. This facility is of particular interest to the project because the owner has expressed interest to restart the factory in order to get into organic production, with project support. For this reason it has been included in the baseline survey, even though it is not currently operational, and does not figure into the baseline statistics. Annex 6 provides the topical outline that was used to guide the interviews with processors. In addition to processors, the team interviewed representatives from the African Cashew Initiative and the Mozambique National Cashew Institute (INCAJU) to get additional background about the cashew industry in Mozambique, and the types of support being provided by these organizations. The following sections provide information collected from each of the companies. Cabo Cajú This company is not currently operating, but the owner has expressed interest to restart operations, with a focus on selling organically certified cashews. The plant has a 1,200 Metric Tons (MT) processing capacity. When the company was in operation, the owner focused on producing retail packaging. He sold locally and also exported, but after having problems with his international buyer (Delta Trading), he was unable to find sufficient market demand for his retail￾packaged product. The owner is interested in making the necessary investments and to establish linkages with producers to obtain organic certification. Export Trading Group (ETG) Export Trading Group is engaged in selling both raw cashew nuts (RCN) and raw kernels. For the current year, the company reports selling 1,400 MT of kernels. The Korosho processing facility at Chiure (Cabo Delgado) was visited by the data collection team. This plant currently processes 1,200 MT of RCN per year, but has recently constructed a major expansion that will double capacity to 2,400 MT next year. The building has already been constructed. A new plant is also planned to be built in Angoche. Shelling will be fully mechanized in the expanded facility. The plant currently has certification for Hazard Analysis and Critical Control Points (HACCP), Kosher, ISO19000, ISO22000 and Social Accountability. The company expresses an interest in obtaining organic certification. Export Trading Group (ETG) Sales 280 T Kernelsa Types of products sold Kernels and RCN 49 Export Trading Group (ETG) Locations US, UK, UAE , South Africa Future plans Increased capacity (doubling capacity at Chiure) Organic certification. Have taken over another factory in Nangade, where they plan to process approximately 600 MT next year. Chiure facility Processing Capacity 1,200 MT (plan to expand to 2,400 MT next year) Storage capacity 2,000 MT, plans to expand to 3,000 MT shelling (manual/machine) 10% machine, 90% manual (Plans to convert to all machine next year) % Wholes in final packaging 70% (72% last year with 100% manual deshelling) Processing (batch) Not currently batch process, but plan to start, for quality control purposes Traceability To district level, but not to kernel level, only for internal monitoring Certification HACCP, Kosher, ISO19000, ISO22000, Social Accountability Fumigation No Labor force 450 registered, currently 350 working Absentee rate 22% Services for workers Canteen, child care, health post (health worker visits weekly) Satellite processing activities No Food safety practices Training to workers, wash basins with soap, aprons and gloves to workers Food safety audits Have already had audits undertaken 50 Export Trading Group (ETG) Procurement of RCN Through own buyers Types of suppliers Associations/forum, brokers Consistent relationships with buyers Yes Services to suppliers Provide saplings (to improve farm-level yield) Main challenges Labor High turnover of workers and high absentee rate. Equipment Plant in process of being expanded. Plant will be shifting to fully mechanized shelling. Working capital Not a constraint a Estimated on basis of reported kernels/RCN ratio of 0.23, and processing of 1,200 MT of RCN. Condor Condor sells only raw kernels, about 80 percent sold to US buyers (Kraft, Costco). Condor has plants in Nametil and Anchilo. Last year, the company experimented with selling a small amount of Fair Trade certified kernel with support from the African Cashew Initiative (ACI). However, this was found to be a lot of trouble in terms of organizing the warehouse and batch processing, and for now, the company is not interested to continuing. The factory in Nametil has been conducting some deshelling in satellite operations in outlying areas, as a way to overcome labor shortages at the plant, but may discontinue this activity because of the management and security challenge. Condor Sales Approximately 1,800 MT raw kernels (whole and brokens) Types of products sold Kernels – wholes and brokens. Have no problem selling wholes, but problems finding buyers for brokens Locations 80% sold to US (Kraft, Costco), most of rest to Europe Costco buys some brokens, rest to India Sold 3.5 containers fair trade certified to Europe, with support from ACI Future plans Have plans to get African Cashew Alliance (ACA) Seal (industry certification), have started making investments in appropriate stocking materials to store kernels appropriately. 51 Condor Interested in investments to extract cashew nut shell liquid (CNSL) Nametil Anchilo Processing Capacity 3,500 – 4,000 MT 4,000 MT (expect 5,000 next year) Storage capacity 5,000 MT, at a combination of on￾site and rural warehouses 6,000 MT Shelling (manual/machine) 30 deshelling machines (20 additional have been purchased) 500 deshelling stations 100 deshelling machines 300 deshelling stations Breakage rate (deshelling) 20% machines, 8% manual Processing (batch) none For fair trade certification Traceability By district (warehouse), not to kernel level (for internal quality control purposes only) By district (warehouse) (By association, only for fair trade batch) Certification Plans for ACA certification next year Trial fair trade batch this year Fumigation Yes Yes Labor force 500 (67% female) 1,200 (65% female) Absentee rate 15% (currently 60% in deshelling) Services for workers Dormitory for workers living distant from plant, crèche, canteen Dormitory for workers living distant from plant, crèche, canteen Satellite processing activities Has used for scooping and peeling, but plans to discontinue Food safety practices None currently (washing facilities not currently functioning) Hand washing facilities, gloves, caps, aprons to workers 52 Condor Want to learn from Brazilians Food safety audits No No Procurement of RCN Through own buyers Through own buyers Types of suppliers Associations/forum, brokers Associations/forum, brokers Consistent relationships with buyers Yes Yes Services to suppliers Main challenges Labor Absenteeism, particularly in rainy season Absenteeism, particularly in rainy season Equipment Peeling machines do not work properly Problems of humidity in kernels Working capital Not a constraint Not a constraint OLAM OLAM is a large international firm that trades a wide range of agricultural products. In Mozambique, OLAM sells RCN as well as kernel. OLAM sells primarily to US markets. The company is interested in implementing complete traceability of the kernels it sells. OLAM Sales 2,880 MT of kernels (whole and brokens) Types of products sold RCN and kernels Locations US (Kraft, Costco) and Europe – 90%, South Africa – 10% Future plans Want to implement complete traceability Want to work on food safety Plant to start to work more directly with producers in Angoche Monapo Facility Processing Capacity 6,000 MT 53 OLAM Storage capacity shelling (manual/machine) 65% machine, 35% manual Breakage rate (deshelling) 8-12% mechanical; 6-12% manual Processing (batch) Batch processing (from different warehouses) only for quality control. Traceability Certification None. Wants to get HACCP certification, and has started making investments Fumigation Yes Labor force 2,500 registered(currently 2,000 working ) Absentee rate 20% (highest in deshelling) Services for workers Canteen Satellite processing activities Peeling done outside plant Food safety practices Workers provided with hairnets, gloves, workers wash hands before entering factory Plan to get certified under BRC Global Standards Food safety audits Not at present Procurement of RCN Direct -through own buyers, from 5-6 units Types of suppliers Associations/forum, brokers Consistent relationships with buyers Yes Services to suppliers Main challenges Labor High absenteeism, turnover ratio Equipment Peeling machine (from Vietnam) does not work properly Working capital Not a constraint 54 Gani Comercial Gani Comercial is a large general trading company based in Nampula. The company trades a wide range of agricultural products, and is also involved in non-agricultural trade. The company has a large network of warehouses throughout Nampula province. Gani reports that they plan to set up a network of extension agents (500 in Angoche) to provide services for cashew producers through a matching grant from African Cashew Initiative (ACI). About 70% of their sales of kernel are to the US, with the remainder sold to South Africa. These extension agents (tratadores) will provide samplings and, fuel for spraying. This service is intended to have two advantages for the firm: i) to increase the productivity of producers and ii) localize the source of RCN, thereby reducing assembly and transport costs. Gani reports that they are interested to get ACA certification (which includes HACCP conditions). The survey team made a rapid visit to the factory in Lumbo, but the operations were closing down for the day, and time did not permit to get detailed information about operations at this facility. Gani Comercial (Cajú Ilha) Sales 1,875 MT of raw kernels (whole and broken), including stock from 2012 sold in 2013 Types of products sold RCN and Kernels Locations US (70%) and South Africa (30%). Brokens are sold in US. Future plans Want to get ACA certification Want to set up network of extension workers (tratadores) who will work with producers Angoche Facility Processing Capacity 4,000-5,000 MT (3,300 MT processed last year) Storage capacity 20,000 MT shelling (manual/machine) 37 machines , capacity 60 kg/hour 306 manual shelling stations, capacity 40 kg/station/day Breakage rate (deshelling) 11-12% machines; 7-9% manual % Wholes in final packaging 74% Processing (batch) Batch processing through cutting Traceability To level of supplying warehouse (5-6 supply the facility) 55 Gani Comercial (Cajú Ilha) Certification None Fumigation No Labor force 700 registered (56% female) Absentee rate 34% (deshellers) Services for workers Canteen (breakfast and lunch), health post, provide food to caretakers of children, sports club, social events for workers, health services to workers Satellite processing activities No Food safety practices Hand washing before entering, Food safety audits No Procurement of RCN From company warehouses Types of suppliers n.a. Consistent relationships with buyers n.a. Services to suppliers Plans to establish network of extension agents (tratadores) to work with producers, and associations. Plans to supply saplings, and pay fuel costs of spraying Main challenges Labor High turnover and absenteeism Equipment Major problem finding qualified personnel to maintain machines Working capital Not a constraint Indo-Africa Trading Indo-Africa Trading is primarily a trader of RCN, the largest RCN trader in Mozambique, but has gotten into processing as well. The company has two operational processing facilities, one in Murrupula and one in Mecua (also in Murrupula District). The plant in Murrupula had just closed operations for the year when the team visited; so detailed information about plant operations was not available. Indo-Africa trades RCN primarily to India and kernel primarily to the US, but also to South Africa. The company employs about 750 workers in the two facilities. 56 Conclusions Cashew Producers Several findings from this baseline survey of cashew farmers in the MozaCajú project areas are worth emphasizing. First, the average number of cultivated trees per household is around 145, with almost 200 trees per farmer in Cabo Delgado, 120 in Nampula, and 100 in Zambezia. Productivity is very low, with average productivity per tree of only about 3 kg/tree, and a median production of only 1.6 kg/tree. Interestingly, the productivity per tree is significantly higher for households in the highest category of sales, at over 4.5 kg/tree compared with less than 2.5 kg/tree for the other sales categories. This may be explained by the fact that a larger proportion of farmers in the highest sales category apply fertilizer and spray their trees. Thus there appears to be significant scope for increasing the productivity of cashew producers within the MozaCajú project area, and smaller farmers appear to have particular potential to catch up with the performance of the larger farmers. Adoption of several improved technologies in general is quite high, particularly avoiding burning, pruning of canopy, and weeding, which are each reported to be practiced by approximately 80 percent of all surveyed farmers. However, other practices are less widespread, such as spraying, intercropping with beans, and mulching, which are reported by only 30-40 percent of farmers, while application of fertilizer is reported by only 10 percent of farmers. A higher proportion of larger producers (in the highest sales category) report adopting spraying, weeding, and use of fertilizer, compared with smaller farmers. Access to support and services is very limited for cashew producers in the project area. Overall access to training is very low. Only about three percent of interviewed farmers reported that they received any agricultural productivity training. Likewise membership in groups is low, with fewer than 20 percent of interviewed farmers reporting participation in groups. Only about 10 percent of farmers report that they have access to any sources of credit to invest in cashew production. The overall situation of cashew producers in the MozaCajú production area is one of low productivity, but with much scope for adoption of key techniques, and provision of training, access to improved inputs and credit. Cashew processors Currently the processors interviewed in the baseline do not face major marketing problems for whole kernels, but several of the firms reported that they had difficulties finding buyers for brokens. However, even though they can presently find buyers for whole kernels, all the companies are aware that the international market for cashews is changing and that they need to make changes in their operations to meet more stringent demands. Since all of the companies interviewed sell the majority of their kernels to US and European markets, they are particularly aware of the growing demands of buyers in these two markets. This perceived need falls squarely within the scope of the MozaCajú project, which has a focus of helping Mozambican processors to meet needs of buyers – traceability, organic, and fair trade. 57 None of the processors indicated that they faced problems in acquiring raw materials during the 2012 harvest. With the exception of Indo-Africa, which had just finished processing prior to the team visit; all the factories had supplies of RCN to stay in operation until the RCN from the 2013 harvest was in stock. The processors in Nametil and Monapo indicated that as 2013 buying was getting started there was some competition with other processors, but they were able to find sufficient quantity of raw material, even though they had to procure from some more distant locations. Without exception, all interviewed processors reported facing major labor problems due to high rates of turnover and absenteeism. These are the major problems that limit the processors’ processing capacities. High turnover is costly, because it takes 1-2 months to train new workers. Currently, official payment of workers in cashew processing plants is based on standardized rates established by ICAJU. However, respondents in the companies noted that there is competition among companies for workers, and that poaching of workers by offering bonuses is commonly practiced. Problems in access to labor point to opportunities for TechnoServe to promote companies to apply shared value strategies – particularly investments and practices – to secure and retain workers. Time constraints did not allow for extensive interviews with workers at all the plants visited. It is recommended that a separate qualitative exercise to interview workers should be undertaken by the project. This study should be organized in a manner that minimizes the perception that the interviews are organized by the companies themselves. If possible the interviews should be undertaken away from the workplace, so that respondents will be freer to give honest answers about any concerns about workplace conditions. In addition, the survey should try to capture individuals that have left employment at the processing factories. Those companies that wish to adopt traceability, organic, and/or fair trade standards will need to forge ongoing relations with suppliers, either at the level of individual farmers or farmer associations. Both OLAM and Gani have reported that they already plan to establish networks to provide more direct support to cashew producers. In addition, several of the processors (Condor, Gani, OLAM) indicated that they would like to concentrate in their immediate geographic area from which they source RCN, to reduce assembly and transport costs. TechnoServe’s shared value approach can point to ways to help companies to establish stronger ties with producers. 58 Annex 1. Producer-Level Project Indicators Province District Gender Household Head Effective area under improved techniques or technologies Weighted N Effective Area Weighted N % Tech / Effective Area Weighted N Cabo Delgado Mueda M 71,209 6,690 72,787 6,905 98.0% 6,690 F 7,337 863 7,337 863 100.0% 863 All 78,546 7,553 80,124 7,769 98.2% 7,553 Nangade M 115,677 9,339 118,409 9,339 98.2% 9,339 F 16,099 1,334 17,369 1,334 95.8% 1,334 All 131,776 10,673 135,779 10,673 97.9% 10,673 Palma M 2,069 385 2,126 385 98.2% 385 F 535 110 630 110 88.3% 110 All 2,603 494 2,755 494 96.0% 494 Muidumbe M 21,843 6,867 22,969 7,235 96.4% 6,867 F 3,259 1,594 3,335 1,594 93.3% 1,594 All 25,101 8,461 26,304 8,829 95.8% 8,461 Mocimboa da Praia M 7,491 2,461 7,505 2,461 98.5% 2,461 F 1,932 542 1,951 542 95.2% 542 All 9,423 3,003 9,456 3,003 97.9% 3,003 Metuge M 5,668 3,926 5,827 3,926 97.7% 3,926 F 1,406 1,309 1,444 1,309 95.8% 1,309 All 7,073 5,235 7,271 5,235 97.2% 5,235 Chiure M 12,992 8,954 14,974 8,954 95.8% 8,954 F 9,751 3,687 9,942 3,687 94.6% 3,687 All 22,743 12,641 24,916 12,641 95.5% 12,641 Macomia M 29,625 8,870 29,977 8,870 98.3% 8,870 F 1,964 1,626 1,964 1,626 100.0% 1,626 All 31,589 10,497 31,941 10,497 98.6% 10,497 Nampula Meconta M 3,807 2,115 4,575 2,161 83.7% 2,115 F 950 1,103 1,182 1,103 90.1% 1,103 All 4,757 3,218 5,757 3,264 85.9% 3,218 Mogovolas M 40,132 16,359 43,873 16,976 86.3% 16,359 F 4,421 4,013 5,706 4,630 92.3% 4,013 All 44,553 20,371 49,579 21,606 87.5% 20,371 Angoche M 68,477 17,993 96,827 17,993 89.3% 17,993 F 8,762 1,687 9,816 1,687 91.7% 1,687 All 77,239 19,680 106,643 19,680 89.5% 19,680 Moma M 31,810 9,392 34,583 9,576 90.7% 9,392 F 7,175 3,499 8,039 3,499 91.4% 3,499 All 38,985 12,890 42,623 13,075 90.9% 12,890 Zambezia Gile M 30,492 11,816 32,772 12,027 94.2% 11,816 F 4,751 2,743 5,516 3,165 94.2% 2,743 All 35,243 14,559 38,288 15,192 94.2% 14,559 Pebane M 69,536 20,001 76,710 20,785 89.0% 19,609 F 16,417 7,059 18,287 7,059 88.9% 7,059 All 85,952 27,060 94,996 27,845 89.0% 26,668 Project M 510,827 125,167 563,914 127,594 92.4% 124,775 F 84,758 31,169 92,519 32,209 92.8% 31,169 All 595,585 156,337 656,433 159,802 92.5% 155,944 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 59 Province District Gender Household Head Number of farmers and others who have applied new techniques and technologies % Farmers Applying New Tech Weighted N Cabo Delgado Mueda M 6,690 96.9% 6,905 F 863 100.0% 863 All 7,553 97.2% 7,769 Nangade M 9,339 100.0% 9,339 F 1,334 100.0% 1,334 All 10,673 100.0% 10,673 Palma M 385 100.0% 385 F 110 100.0% 110 All 494 100.0% 494 Muidumbe M 6,867 94.9% 7,235 F 1,594 100.0% 1,594 All 8,461 95.8% 8,829 Mocimboa da Praia M 2,419 98.3% 2,461 F 542 100.0% 542 All 2,961 98.6% 3,003 Metuge M 3,926 100.0% 3,926 F 1,309 100.0% 1,309 All 5,235 100.0% 5,235 Chiure M 8,954 100.0% 8,954 F 3,687 100.0% 3,687 All 12,641 100.0% 12,641 Macomia M 8,870 98.4% 9,018 F 1,626 100.0% 1,626 All 10,497 98.6% 10,644 Nampula Meconta M 2,161 97.9% 2,207 F 1,103 100.0% 1,103 All 3,264 98.6% 3,310 Mogovolas M 16,667 98.2% 16,976 F 4,630 93.8% 4,938 All 21,297 97.2% 21,914 Angoche M 18,275 100.0% 18,275 F 1,687 100.0% 1,687 All 19,961 100.0% 19,961 Moma M 9,576 98.1% 9,760 F 3,499 100.0% 3,499 All 13,075 98.6% 13,259 Zambezia Gile M 11,816 98.2% 12,027 F 2,743 86.7% 3,165 All 14,559 95.8% 15,192 Pebane M 20,393 96.3% 21,178 F 6,667 94.4% 7,059 All 27,060 95.8% 28,237 Project M 126,338 98.2% 128,645 F 31,394 96.5% 32,517 All 157,732 97.9% 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 60 Province District Gender Household Head Effective area under improved techniques or technologies (w/o burn avoidance) Weighted N % Tech / Effective Area Weighted N Cabo Delgado Mueda M 70,353 6,690 95.4% 6,690 F 7,119 863 92.2% 863 All 77,473 7,553 95.0% 7,553 Nangade M 114,089 9,339 97.4% 9,339 F 16,099 1,334 95.8% 1,334 All 130,188 10,673 97.2% 10,673 Palma M 1,952 385 94.2% 385 F 460 110 79.7% 110 All 2,412 494 91.0% 494 Muidumbe M 21,843 6,867 96.4% 6,867 F 3,259 1,594 93.3% 1,594 All 25,101 8,461 95.8% 8,461 Mocimboa da Praia M 7,491 2,461 98.5% 2,461 F 1,932 542 95.2% 542 All 9,423 3,003 97.9% 3,003 Metuge M 5,668 3,926 97.7% 3,926 F 1,406 1,309 95.8% 1,309 All 7,073 5,235 97.2% 5,235 Chiure M 12,963 8,954 95.6% 8,954 F 9,322 3,687 89.9% 3,687 All 22,285 12,641 93.9% 12,641 Macomia M 29,609 8,870 98.1% 8,870 F 1,964 1,626 100.0% 1,626 All 31,573 10,497 98.4% 10,497 Nampula Meconta M 3,404 2,023 76.7% 2,023 F 816 1,011 84.7% 1,011 All 4,220 3,034 79.4% 3,034 Mogovolas M 37,382 16,050 76.2% 16,050 F 4,091 4,013 88.5% 4,013 All 41,473 20,063 78.7% 20,063 Angoche M 65,331 17,993 86.3% 17,993 F 8,641 1,687 87.5% 1,687 All 73,972 19,680 86.4% 19,680 Moma M 29,680 9,392 84.3% 9,392 F 6,977 3,499 90.1% 3,499 All 36,658 12,890 85.9% 12,890 Zambezia Gile M 29,541 11,816 89.7% 11,816 F 4,373 2,743 89.4% 2,743 All 33,914 14,559 89.7% 14,559 Pebane M 65,635 20,001 83.0% 19,609 F 15,485 7,059 85.4% 7,059 All 81,120 27,060 83.6% 26,668 Project M 494,942 124,767 88.5% 124,375 F 81,944 31,077 89.7% 31,077 All 576,886 155,844 88.8% 155,452 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 61 Province District Gender Household Head Number of farmers and others who have applied new techniques and technologies (w/o burn avoidance) % Farmers Applying New Tech Weighted N Number of individuals receiving short-term agricultural sector productivity or food security training % receiving training Weighted N Cabo Delgado Mueda M 6,690 96.9% 6,905 216 3.1% 6,905 F 863 100.0% 863 0 0.0% 863 All 7,553 97.2% 7,769 216 2.8% 7,769 Nangade M 9,339 100.0% 9,339 445 4.8% 9,339 F 1,334 100.0% 1,334 0 0.0% 1,334 All 10,673 100.0% 10,673 445 4.2% 10,673 Palma M 385 100.0% 385 0 0.0% 385 F 110 100.0% 110 0 0.0% 110 All 494 100.0% 494 0 0.0% 494 Muidumbe M 6,867 94.9% 7,235 368 5.1% 7,235 F 1,594 100.0% 1,594 0 0.0% 1,594 All 8,461 95.8% 8,829 368 4.2% 8,829 Mocimboa da Praia M 2,419 98.3% 2,461 42 1.7% 2,461 F 542 100.0% 542 0 0.0% 542 All 2,961 98.6% 3,003 42 1.4% 3,003 Metuge M 3,926 100.0% 3,926 73 1.9% 3,926 F 1,309 100.0% 1,309 0 0.0% 1,309 All 5,235 100.0% 5,235 73 1.4% 5,235 Chiure M 8,954 100.0% 8,954 0 0.0% 8,954 F 3,687 100.0% 3,687 0 0.0% 3,687 All 12,641 100.0% 12,641 0 0.0% 12,641 Macomia M 8,870 98.4% 9,018 591 6.6% 9,018 F 1,626 100.0% 1,626 0 0.0% 1,626 All 10,497 98.6% 10,644 591 5.6% 10,644 Nampula Meconta M 2,069 93.8% 2,207 46 2.1% 2,207 F 1,011 91.7% 1,103 0 0.0% 1,103 All 3,080 93.1% 3,310 46 1.4% 3,310 Mogovolas M 16,359 96.4% 16,976 926 5.5% 16,976 F 4,630 93.8% 4,938 0 0.0% 4,938 All 20,989 95.8% 21,914 926 4.2% 21,914 Angoche M 18,275 100.0% 18,275 843 4.6% 18,275 F 1,687 100.0% 1,687 0 0.0% 1,687 All 19,961 100.0% 19,961 843 4.2% 19,961 Moma M 9,576 98.1% 9,760 737 7.5% 9,760 F 3,499 100.0% 3,499 184 5.3% 3,499 All 13,075 98.6% 13,259 921 6.9% 13,259 Zambezia Gile M 11,816 98.2% 12,027 0 0.0% 12,027 F 2,743 86.7% 3,165 0 0.0% 3,165 All 14,559 95.8% 15,192 0 0.0% 15,192 Pebane M 20,393 96.3% 21,178 784 3.7% 21,178 F 6,667 94.4% 7,059 0 0.0% 7,059 All 27,060 95.8% 28,237 784 2.8% 28,237 Project M 125,937 97.9% 128,645 5,070 3.9% 128,645 F 31,303 96.3% 32,517 184 0.6% 32,517 All 157,240 97.6% 161,162 5,255 3.3% 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 62 Province District Gender Household Head Effective area under improved techniques or technologies as a result of USDA assistance Weighted N # of farmers and others who have applied new techniques and technologies as a result of USDA assistance Weighted N Cabo Delgado Mueda M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Nangade M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Palma M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Muidumbe M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Mocimboa da Praia M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Metuge M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Chiure M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Macomia M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Nampula Meconta M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Mogovolas M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Angoche M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Moma M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Zambezia Gile M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Pebane M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Project M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 63 Province District Gender Household Head # of ind. receiving short-term ag sector productivity or food security training as a result of USDA assistance Weighte d N Value of agricultura l and rural loans Value of agricultura l and rural loans (per farmer) Weighte d N Value of agricultura l and rural loans provided with USDA assistance Weighte d N Cabo Delgado Mueda M 0 161,162 0 0 6,905 0 161,162 F 0 161,162 0 0 863 0 161,162 All 0 161,162 0 0 7,769 0 161,162 Nangade M 0 161,162 0 0 9,339 0 161,162 F 0 161,162 0 0 1,334 0 161,162 All 0 161,162 0 0 10,673 0 161,162 Palma M 0 161,162 0 0 385 0 161,162 F 0 161,162 0 0 110 0 161,162 All 0 161,162 0 0 494 0 161,162 Muidumbe M 0 161,162 0 0 7,235 0 161,162 F 0 161,162 0 0 1,594 0 161,162 All 0 161,162 0 0 8,829 0 161,162 Mocimboa da Praia M 0 161,162 0 0 2,461 0 161,162 F 0 161,162 0 0 542 0 161,162 All 0 161,162 0 0 3,003 0 161,162 Metuge M 0 161,162 0 0 3,926 0 161,162 F 0 161,162 0 0 1,309 0 161,162 All 0 161,162 0 0 5,235 0 161,162 Chiure M 0 161,162 0 0 8,954 0 161,162 F 0 161,162 0 0 3,687 0 161,162 All 0 161,162 0 0 12,641 0 161,162 Macomia M 0 161,162 0 0 9,018 0 161,162 F 0 161,162 0 0 1,626 0 161,162 All 0 161,162 0 0 10,644 0 161,162 Nampula Meconta M 0 161,162 0 0 2,207 0 161,162 F 0 161,162 0 0 1,103 0 161,162 All 0 161,162 0 0 3,310 0 161,162 Mogovolas M 0 161,162 9,259,638 545 16,976 0 161,162 F 0 161,162 0 0 4,938 0 161,162 All 0 161,162 9,259,638 423 21,914 0 161,162 Angoche M 0 161,162 2,895,818 158 18,275 0 161,162 F 0 161,162 0 0 1,687 0 161,162 All 0 161,162 2,895,818 145 19,961 0 161,162 Moma M 0 161,162 0 0 9,760 0 161,162 F 0 161,162 0 0 3,499 0 161,162 All 0 161,162 0 0 13,259 0 161,162 Zambezia Gile M 0 161,162 0 0 12,027 0 161,162 F 0 161,162 0 0 3,165 0 161,162 All 0 161,162 0 0 15,192 0 161,162 Pebane M 0 161,162 0 0 21,178 0 161,162 F 0 161,162 0 0 7,059 0 161,162 All 0 161,162 0 0 28,237 0 161,162 Project M 0 161,162 12,155,455 94 128,645 0 161,162 F 0 161,162 0 0 32,517 0 161,162 All 0 161,162 12,155,455 75 161,162 0 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 64 Province District Gender Household Head Number of farmers and others who have received training on improved agricultural techniques and technologies as a result of USDA assistance Weighted N Number of jobs attributed to USDA assistance Weighted N Cabo Delgado Mueda M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Nangade M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Palma M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Muidumbe M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Mocimboa da Praia M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Metuge M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Chiure M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Macomia M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Nampula Meconta M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Mogovolas M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Angoche M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Moma M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Zambezia Gile M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Pebane M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Project M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 65 Province District Gender Household Head Number of individuals benefiting directly from USDA-funded interventions (Farmers, processor employees, processor owners) Weighted N Total number of individuals benefiting indirectly from USDA-funded interventions Weighted N Cabo Delgado Mueda M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Nangade M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Palma M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Muidumbe M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Mocimboa da Praia M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Metuge M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Chiure M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Macomia M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Nampula Meconta M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Mogovolas M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Angoche M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Moma M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Zambezia Gile M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Pebane M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Project M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 66 Province District Gender Household Head Baseline in cashew tree productivity (yield per tree); Disaggregated by Gender and District Weighted N Baseline in small holder cashew sales (total USD); Disaggregated by Gender and District Baseline in small holder cashew sales (USD per farmer); Disaggregated by Gender and District Weighted N Cabo Delgado Mueda M 4.04 5,071 2,821,595 450.88 6,258 F 10.73 863 662,846 767.92 863 All 5.01 5,934 3,484,441 489.31 7,121 Nangade M 4.57 6,967 3,855,255 464.41 8,301 F 2.78 1,186 510,437 382.59 1,334 All 4.31 8,153 4,365,692 453.08 9,636 Palma M 2.66 364 67,878 179.72 378 F 2.50 110 13,439 122.31 110 All 2.62 474 81,317 166.78 488 Muidumbe M 2.06 6,990 383,488 59.01 6,499 F 0.64 1,594 29,450 26.69 1,104 All 1.79 8,584 412,938 54.32 7,603 Mocimboa da Praia M 4.50 2,461 254,001 156.15 1,627 F 2.76 542 44,491 213.33 209 All 4.19 3,003 298,492 162.64 1,835 Metuge M 1.55 3,563 46,448 35.49 1,309 F 0.90 1,236 4,169 28.67 145 All 1.38 4,799 50,617 34.81 1,454 Chiure M 1.99 8,076 131,855 34.14 3,863 F 0.61 3,160 40,967 38.89 1,053 All 1.60 11,237 172,822 35.15 4,916 Macomia M 2.18 8,279 443,564 107.15 4,139 F 1.67 1,626 17,199 19.39 887 All 2.09 9,905 460,762 91.67 5,026 Nampula Meconta M 4.06 2,161 121,094 54.88 2,207 F 4.29 1,011 22,113 20.91 1,057 All 4.13 3,172 143,207 43.87 3,264 Mogovolas M 4.53 16,359 795,403 47.72 16,667 F 6.46 4,321 67,955 18.35 3,704 All 4.94 20,680 863,358 42.38 20,371 Angoche M 4.03 15,744 2,112,963 129.58 16,307 F 2.68 1,406 105,149 62.33 1,687 All 3.92 17,150 2,218,112 123.27 17,993 Moma M 4.22 9,023 952,024 99.42 9,576 F 5.05 3,499 168,129 50.72 3,315 All 4.46 12,522 1,120,152 86.90 12,890 Zambezia Gile M 1.74 11,394 429,179 39.12 10,972 F 2.18 3,165 73,499 29.03 2,532 All 1.83 14,559 502,678 37.22 13,504 Pebane M 2.26 18,824 1,032,731 54.86 18,824 F 2.98 6,667 272,406 38.59 7,059 All 2.45 25,491 1,305,137 50.42 25,884 Project M 3.16 115,276 13,447,477 125.76 106,927 F 3.35 30,387 2,032,247 81.10 25,059 All 3.20 145,663 15,479,725 117.28 131,986 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 67 Province District Gender Household Head Number of new trees planted; Disaggregated by Gender, District Number of new trees planted (per farmer); Disaggregated by Gender, District Weighted N Number of germilings procured by farmers; Disaggregated by Source (farmer extension agent vs. nursery) and District Weighted N Cabo Delgado Mueda M 110,594 16.3 6,797 0 161,162 F 42,835 49.6 863 0 161,162 All 153,428 20.0 7,661 0 161,162 Nangade M 203,681 23.7 8,598 0 161,162 F 4,744 4.6 1,038 0 161,162 All 208,424 21.6 9,636 0 161,162 Palma M 5,219 14.3 364 0 161,162 F 1,785 20.0 89 0 161,162 All 7,004 15.5 453 0 161,162 Muidumbe M 55,671 7.7 7,235 0 161,162 F 3,066 2.1 1,471 0 161,162 All 58,737 6.7 8,706 0 161,162 Mocimboa da Praia M 27,529 11.2 2,461 0 161,162 F 5,631 10.4 542 0 161,162 All 33,160 11.0 3,003 0 161,162 Metuge M 15,269 3.9 3,926 0 161,162 F 5,017 3.8 1,309 0 161,162 All 20,285 3.9 5,235 0 161,162 Chiure M 26,336 2.9 8,954 0 161,162 F 2,634 0.7 3,687 0 161,162 All 28,969 2.3 12,641 0 161,162 Macomia M 62,240 6.9 9,018 0 161,162 F 4,879 3.0 1,626 0 161,162 All 67,119 6.3 10,644 0 161,162 Nampula Meconta M 6,942 3.1 2,207 0 161,162 F 1,885 1.7 1,103 0 161,162 All 8,827 2.7 3,310 0 161,162 Mogovolas M 31,791 1.9 16,667 0 161,162 F 1,543 0.3 4,938 0 161,162 All 33,335 1.5 21,606 0 161,162 Angoche M 132,420 7.5 17,712 0 161,162 F 1,406 0.8 1,687 0 161,162 All 133,826 6.9 19,399 0 161,162 Moma M 84,893 8.9 9,576 0 161,162 F 12,154 3.5 3,499 0 161,162 All 97,047 7.4 13,075 0 161,162 Zambezia Gile M 114,785 9.7 11,816 0 161,162 F 20,045 7.3 2,743 0 161,162 All 134,831 9.3 14,559 0 161,162 Pebane M 189,029 9.1 20,785 0 161,162 F 24,315 3.9 6,275 0 161,162 All 213,344 7.9 27,060 0 161,162 Project M 1,066,398 8.5 126,117 0 161,162 F 131,937 4.3 30,871 0 161,162 All 1,198,336 7.6 156,988 0 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 68 Province District Gender Household Head Number of farmers benefitting from procurement of germilings; Disaggregated by Gender and District Weighted N Number of agrodealers created and operational Weighted N Cabo Delgado Mueda M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Nangade M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Palma M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Muidumbe M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Mocimboa da Praia M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Metuge M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Chiure M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Macomia M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Nampula Meconta M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Mogovolas M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Angoche M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Moma M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Zambezia Gile M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Pebane M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Project M 0 161,162 0 161,162 F 0 161,162 0 161,162 All 0 161,162 0 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 69 Province District Gender Household Head Number of (loans, grants, etc) disbursed to (direct beneficiaries) % of farmers receiving loans Weighted N Number of (loans, grants, etc) disbursed to (direct beneficiaries) as a result of USDA assistance Weighted N Cabo Delgado Mueda M 0 0.0% 6,905 0 161,162 F 0 0.0% 863 0 161,162 All 0 0.0% 7,769 0 161,162 Nangade M 0 0.0% 9,339 0 161,162 F 0 0.0% 1,334 0 161,162 All 0 0.0% 10,673 0 161,162 Palma M 0 0.0% 385 0 161,162 F 0 0.0% 110 0 161,162 All 0 0.0% 494 0 161,162 Muidumbe M 0 0.0% 7,235 0 161,162 F 0 0.0% 1,594 0 161,162 All 0 0.0% 8,829 0 161,162 Mocimboa da Praia M 0 0.0% 2,461 0 161,162 F 0 0.0% 542 0 161,162 All 0 0.0% 3,003 0 161,162 Metuge M 0 0.0% 3,926 0 161,162 F 0 0.0% 1,309 0 161,162 All 0 0.0% 5,235 0 161,162 Chiure M 0 0.0% 8,954 0 161,162 F 0 0.0% 3,687 0 161,162 All 0 0.0% 12,641 0 161,162 Macomia M 0 0.0% 9,018 0 161,162 F 0 0.0% 1,626 0 161,162 All 0 0.0% 10,644 0 161,162 Nampula Meconta M 0 0.0% 2,207 0 161,162 F 0 0.0% 1,103 0 161,162 All 0 0.0% 3,310 0 161,162 Mogovolas M 309 1.8% 16,976 0 161,162 F 0 0.0% 4,938 0 161,162 All 309 1.4% 21,914 0 161,162 Angoche M 562 3.1% 18,275 0 161,162 F 0 0.0% 1,687 0 161,162 All 562 2.8% 19,961 0 161,162 Moma M 0 0.0% 9,760 0 161,162 F 0 0.0% 3,499 0 161,162 All 0 0.0% 13,259 0 161,162 Zambezia Gile M 0 0.0% 12,027 0 161,162 F 0 0.0% 3,165 0 161,162 All 0 0.0% 15,192 0 161,162 Pebane M 0 0.0% 21,178 0 161,162 F 0 0.0% 7,059 0 161,162 All 0 0.0% 28,237 0 161,162 Project M 871 0.7% 128,645 0 161,162 F 0 0.0% 32,517 0 161,162 All 871 0.5% 161,162 0 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 70 Province District Gender Household Head Number of farmers benefitting from demonstration plots; Disaggregated by Gender and District Weighted N Number of farmers who have received training in post-harvest handling; Disaggregated by Gender and District % of farmers who have received training in post-harvest handling; Disaggregated by Gender and District Weighted N Cabo Delgado Mueda M 0 161,162 108 1.6% 6,905 F 0 161,162 0 0.0% 863 All 0 161,162 108 1.4% 7,769 Nangade M 0 161,162 148 1.6% 9,339 F 0 161,162 0 0.0% 1,334 All 0 161,162 148 1.4% 10,673 Palma M 0 161,162 0 0.0% 385 F 0 161,162 0 0.0% 110 All 0 161,162 0 0.0% 494 Muidumbe M 0 161,162 0 0.0% 7,235 F 0 161,162 0 0.0% 1,594 All 0 161,162 0 0.0% 8,829 Mocimboa da Praia M 0 161,162 42 1.7% 2,461 F 0 161,162 0 0.0% 542 All 0 161,162 42 1.4% 3,003 Metuge M 0 161,162 73 1.9% 3,926 F 0 161,162 0 0.0% 1,309 All 0 161,162 73 1.4% 5,235 Chiure M 0 161,162 0 0.0% 8,954 F 0 161,162 0 0.0% 3,687 All 0 161,162 0 0.0% 12,641 Macomia M 0 161,162 148 1.6% 9,018 F 0 161,162 0 0.0% 1,626 All 0 161,162 148 1.4% 10,644 Nampula Meconta M 0 161,162 46 2.1% 2,207 F 0 161,162 0 0.0% 1,103 All 0 161,162 46 1.4% 3,310 Mogovolas M 0 161,162 309 1.8% 16,976 F 0 161,162 0 0.0% 4,938 All 0 161,162 309 1.4% 21,914 Angoche M 0 161,162 281 1.5% 18,275 F 0 161,162 0 0.0% 1,687 All 0 161,162 281 1.4% 19,961 Moma M 0 161,162 552 5.7% 9,760 F 0 161,162 184 5.3% 3,499 All 0 161,162 737 5.6% 13,259 Zambezia Gile M 0 161,162 0 0.0% 12,027 F 0 161,162 0 0.0% 3,165 All 0 161,162 0 0.0% 15,192 Pebane M 0 161,162 784 3.7% 21,178 F 0 161,162 0 0.0% 7,059 All 0 161,162 784 2.8% 28,237 Project M 0 161,162 2491 1.9% 128,645 F 0 161,162 184 0.6% 32,517 All 0 161,162 2675 1.7% 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 71 Province District Gender Household Head Number of farmers who have applied improved farm management practices (i.e. governance, administration or financial management) % of farmers who have applied improved farm management practices (i.e. governance, administration or financial management) Weighted N Cabo Delgado Mueda M 2,697 39.1% 6,905 F 216 25.0% 863 All 2,913 37.5% 7,769 Nangade M 4,299 46.0% 9,339 F 296 22.2% 1,334 All 4,595 43.1% 10,673 Palma M 151 39.3% 385 F 27 25.0% 110 All 179 36.1% 494 Muidumbe M 2,452 33.9% 7,235 F 368 23.1% 1,594 All 2,820 31.9% 8,829 Mocimboa da Praia M 167 6.8% 2,461 F 0 0.0% 542 All 167 5.6% 3,003 Metuge M 509 13.0% 3,926 F 0 0.0% 1,309 All 509 9.7% 5,235 Chiure M 702 7.8% 8,954 F 0 0.0% 3,687 All 702 5.6% 12,641 Macomia M 1,331 14.8% 9,018 F 0 0.0% 1,626 All 1,331 12.5% 10,644 Nampula Meconta M 873 39.6% 2,207 F 230 20.8% 1,103 All 1,103 33.3% 3,310 Mogovolas M 7,716 45.5% 16,976 F 1,852 37.5% 4,938 All 9,568 43.7% 21,914 Angoche M 7,029 38.5% 18,275 F 281 16.7% 1,687 All 7,310 36.6% 19,961 Moma M 3,683 37.7% 9,760 F 737 21.1% 3,499 All 4,420 33.3% 13,259 Zambezia Gile M 1,477 12.3% 12,027 F 422 13.3% 3,165 All 1,899 12.5% 15,192 Pebane M 3,922 18.5% 21,178 F 392 5.6% 7,059 All 4,314 15.3% 28,237 Project M 37,009 28.8% 128,645 F 4,821 14.8% 32,517 All 41,830 26.0% 161,162 Note: 161,162 is the total number of HH across the 14 districts Note: Avg. effective area is 286 square meters per cultivated tree Note: MZN/USD exchange rate = 30 72 Annex 2. Producer Level Indicators Calculation Indicator Value Calculation Survey question 1. Effective area under improved techniques or technologies (ha) 595,585 Sum(Max(% of trees in which a practice was applied)) (C4_01 - C4_11), B4A 2. Effective Area (ha) 656,433 Sum(Trees Cultivated / 35) B4A 3. % Tech / Effective Area 92.5% Effective area under improved techniques / Effective area (C4_01 - C4_11), B4A 4. Number of farmers and others who have applied new techniques and technologies 157,732 Sum(Any(applied new practice=yes)) (C2_01 - C2_11) 5. % Farmers Applying New Tech 97.9% Number of farmers applying new practices / Total farmers (C2_01 - C2_11) 6. Effective area under improved techniques or technologies (w/o burn avoidance) 576,886 Sum(Max(% of trees in which a practice was applied)) (C4_01 - C4_10), B4A 7. % Tech / Effective Area 88.8% Effective area under improved techniques / Effective area (C4_01 - C4_10), B4A 8. Number of farmers and others who have applied new techniques and technologies (w/o burn avoidance) 157,240 Sum(Any(applied new practice=yes)) (C2_01 - C2_10) 9. % Farmers Applying New Tech 97.6% Number of farmers applying new practices / Total farmers (C2_01 - C2_10) 10. Number of individuals receiving short-term agricultural sector productivity or food security training 5,255 Sum (Did you receive any training in cashew nut cultivation practices = yes) D4 11. % receiving training 3.3% Number of farmers receiving training / Total farmers D4 73 Indicator Value Calculation Survey question 12. Baseline in cashew tree productivity (yield per tree); Disaggregated by Gender and District 3.2 Quantity nuts produced (kg) / Trees cultivated E1, E2, B4A 13. Baseline in small holder cashew sales (total USD); Disaggregated by Gender and District 15,479,725 Sum((Total quantity nuts sold * 10) + wine sales + juice sales + fruit sales) (E900_01- E900_10), (E10_01- E10_10), E17, E20, E22 14. Baseline in small holder cashew sales (USD per farmer); Disaggregated by Gender and District 117.28 Average[(Total quantity nuts sold * 10) + wine sales + juice sales + fruit sales] (E900_01- E900_10), (E10_01- E10_10), E17, E20, E22 15. Number of new trees planted; Disaggregated by Gender, District 1,198,336 Sum(Number of trees planted in the last 12 months) B13 16. Number of new trees planted (per farmer); Disaggregated by Gender, District 7.6 Average(Number of trees planted in the last 12 months) B13 17. Number of farmers who have received training in post-harvest handling; Disaggregated by Gender and District 2,675 Sum(Any(trained in sorting, storage, or drying=yes)) D5A_05, D5A_12, D5A_13 18. % of farmers who have received training in post-harvest handling; Disaggregated by Gender and District 1.7% Number of farmers receiving PHH training / Total farmers D5A_05, D5A_12, D5A_13 19. Number of farmers who have applied improved farm management practices (i.e. governance, administration or financial management) 41,830 Sum(Any(keep business records, invoices, receipts, household records=yes)) F1, F2, F3 20. % of farmers who have applied improved farm management practices (i.e. governance, administration or financial management) 26.0% Number of farmers applying improved farm mgmt / Total farmers F1, F2, F3 74 Indicator Notes 1. Effective area under improved techniques or technologies The maximum area (%age of trees) that was recorded for any of the practices a farmer indicated that they had applied (Module C) a given practice, multiplied by the effective area. The midpoint of the range given by a respective farmer to the question "What %age of trees did you apply this practice?" was used (e.g. 0%-25% = 12.5%). 2. Effective Area A representative hectare was calculated using the median number of trees cultivated (35) from the sample. 3. % Tech / Effective Area Indicator 2. / Indicator 3. 4. Number of farmers and others who have applied new techniques and technologies A farmer was counted as applying a new technique if they responded yes to having applied any of the practices listed in module C. 5. % Farmers Applying New Tech Indicator 4. / Total farmers in the sample 6. Effective area under improved techniques or technologies (w/o burn avoidance) Same as calculation for Indicator 1., excluding burn avoidance practice. 7. % Tech / Effective Area Indicator 6. / Indicator 7. 8. Number of farmers and others who have applied new techniques and technologies (w/o burn avoidance) Same as calculation for Indicator 4., excluding burn avoidance practice. 9. % Farmers Applying New Tech Indicator 7. / Total farmers in the sample 10. Number of individuals receiving short-term agricultural sector productivity or food security training The total number of farmers responding yes to having received training. 11. % receiving training Indicator 10. / Total farmers in sample 12. Baseline in cashew tree productivity (yield per tree); Disaggregated by Gender and District For each farmer, the reported quantity of nuts produced is converted to kg and divided by the number of trees cultivated. The yield per cultivated tree is an average per farmer. Yields over 60kg per tree were considered outliers and excluded from the calculation. 13. Baseline in small holder cashew sales (total); Disaggregated by Gender and District The sum across all farmers of: total quantity of nut sales converted to kg multiplied by a representative price of 10 per kg (the median and mode reported price in the sample). Included in total sales are the sum of all reported sales of wine, juice, and fruit. Farmers that had greater than 600 MZN in sales per cultivated tree (60 kg) were considered outliers and excluded from the analysis. An exchange rate of 30MZN/USD was used. 75 Indicator Notes 14. Baseline in small holder cashew sales (per farmer); Disaggregated by Gender and District Indicator 15. / Number of farmers reporting sales 15. Number of new trees planted; Disaggregated by Gender, District Sum of all responses to "How many trees did you plant in the last 12 months?". 16. Number of new trees planted (per farmer); Disaggregated by Gender, District Indicator 15 / Farmers planting trees 17. Number of farmers who have received training in post￾harvest handling; Disaggregated by Gender and District Total of all farmers indicating that have received training in sorting, storage, or drying. 18. % of farmers who have received training in post-harvest handling; Disaggregated by Gender and District Indicator 17. / Total farmers in sample 19. Number of farmers who have applied improved farm management practices (i.e. governance, administration or financial management) Total of all farmers responding that they keep production records, receipts, invoices, or records of household goods. 20. % of farmers who have applied improved farm management practices (i.e. governance, administration or financial management) Indicator 19 / Total farmers in sample 76 Annex 3. Processor Level Indicators Indicators Unit EGT Condor Gani Indo-Africa OLAM All firms 1. Value of cashew sold into regional(SADC) and international markets USD 8,540,000 10,980,000 11,437,500 2,000,000 17,568,000 50,525,500 % Traceable % 0 0 0 0 27 9 % Bulk (vs retail) % 100 100 100 100 100 100 % Conventional (vs specialty) % 0 0 0 0 0 0 2. Volume (MT) of processed cashew kernel sold into regional (SADC)markets MT 140 0 563 32 288 1,023 % Traceable % 0 0 0 0 0 0 3. Volume (MT) of processed cashew kernel sold into international markets (Non-SADC) MT 1,260 1,800 1,313 272 2,592 7,237 % Traceable % 0 0 0 0 30 11(avg.) 4. Number of new sales relationships with regional/international consumer goods companies as a result of USDA assistance # 0 0 0 0 0 0 % Traceable % n.a. n.a. n.a. n.a. n.a. n.a. % Bulk (vs retail) % n.a. n.a. n.a. n.a. n.a. n.a. % Conventional (vs specialty) % n.a. n.a. n.a. n.a. n.a. n.a. 5. Total cost of wages per year (Value of wages from jobs resulting from USDA assistance USD 600,000 1,700,000 1,850,000 750,000 4,800,000 9,700,000 male 120,000 578,000 740,000 300,000 1,152,000 2,890,000 female 480,000 1,122,000 1,110,000 450,000 3,648,000 6,810,000 6. Number of firms that have taken food safety (GFSI)audits # 1 0 0 0 0 1 (20% firms) 7. Number of firms passing food safety audits # 1 0 0 0 0 1 (20% firms) 8. Number of processing firms that have applied new technologies and/or management practices as a result of USDA assistance # 0 0 0 0 0 0 9. Number of processor representatives trained in post-harvest processing # 0 0 0 0 0 0 10. Number of processors pursuing exports under international certifications # 1 1 0 0 0 2 (40% firms) Organic 1a 0 0 0 0 1 (20% firms) Fair Trade 0 1 0 0 0 1 (20% firms) 77 Indicators Unit EGT Condor Gani Indo-Africa OLAM All firms 11. Number of processors participating in international marketing and branding # 0 0 0 0 0 0 12. Number of industry stakeholders trained in certifications # 0 0 0 0 0 0 13. Number of firms for which traceability audits are conducted. # 0 0 0 0 0 0 14. Number of shared value investments undertaken # 0 0 0 0 0 0 15. Percentage of introductions made between retailers and processors that resulted in a sale. % 0 0 0 0 0 0 16. Number of shared value models identified and tested # 0 0 0 0 0 0 17. Number of (loans, grants, etc) disbursed to (direct beneficiaries) as a result of USDA # 0 0 0 0 0 0 18. Total number of current buyers (main buyers) # 5 4 2 3 5 3.8 (avg./firm) 19. Total number of employees # 600 1,700 1,850 750 4,800 9,700 % female % 80% 66% 60% 60% 76% 70% Notes: Value of exports computed on basis of USD 6.1/kg (based on average mix of quality of kernels and brokens) Wages estimated based on minimum wage for cashew workers of 2,500 MTS per month, equal to USD 1,000 per year. a In process, but have not yet received organic certification 78 Annex 4. Producer Questionnaire Nos gostaríamos de entrevistar um membro do agregado familiar. O/A Sr(a) tem direito a não participar nesta entrevista. A sua participação é inteiramente voluntária. No entanto, vale a pena indicar que, caso da Sr(a). participar na entrevista, toda a informação recolhida será completamente confidencial - em nenhuma circunstância o seu nome será associado a nenhuma resposta. Na campanha passada, o seu agregado familiar vendeu pelo menos 1 saco de 50 kg de castanha de cajú? 1-Sim 0-Não PARE E PROCURE UM OUTRO AGREGADO FAMILIAR Seria possível conversar com o membro do agregado responsável pela produção da castanha de cajú? 1-Sim 0-Não PARE E PROCURE UM OUTRO AGREGADO FAMILIAR PESQUISA AO PRODUTORES DE CASTANHA DE CAJÚ Identificação ID.1 Data da entrevista Dia ____ / Mês ____ Ano________ ID.2 Província 1=Cabo Delgado, 2=Nampula, 3=Zambezia ID.3 Distrito ID.4 Posto Administrativo ID.5 Comunidade ID.6 ID Produtor (Número)________ ID.7 Código do inquiridor (Código)_________ ID.8 Código do digitador 1 (Código) ________ ID.9 Código do digitador 2 (Código)_________ A. DADOS DEMOGRÁFICOS DO AGREGADO Pergunta Códigos de Respostas (marque as respostas apropriadas) Salte A1 Qual é o sexo do produtor? 1=masculino 2=feminino A2 Qual é a sua idade? (em anos compeltos) Anos __________________ A.3 Qual é o seu actual estado civil? 1 = casado ou Coabitação 2 = separado/divorciado 3 = viúvo(a) 4 = solteiro(a), nunca casado A.4 Qual é o seu nível de alfabetização? 1 = não sabe ler ou escrever 2 =só sabe ler 3 =sabe ler e escrever A.5 Quantos membros vivem no seu agregado?a ______________________ 79 a Agregado: todas as pessoas que vivem na mesma quintal ou normalmente passam as refeições juntas. B. CULTIVO DA CASTANHA DE CAJÚ Pergunta Códigos de Respostas (marque as respostas apropriadas) Salte B.1 Há quanto tempo você cultiva castanha de cajú (# de anos)? ___________________ (999=não sabe) B.2 Qual é a área total de terra em que você cultiva castanha de cajú? (em hectares) ___________________ (999=não sabe) B.3a Quantos cajúeiros vivos você possui? ___________________ (999=não sabe) Se o entrevistado responder com um número → B.4a B.3b Se o respondente não consegue dar o número certo, regista o intervalo 1 = 0-50 2 = 51-100 3 = 101-200 4 = 201-500 5=mais de 500 B.4a Quantos cajúeiros você explora agora? _______________ (999=não sabe) Se o entrevistado responder com um número → B.5 B.4b Se o respondente não consegue dar o número certo, regista o intervalo 1 = 0-50 2 = 51-100 3 = 101-200 4 = 201-500 5 = mais de 500 B.5 Será que as árvores estão dispersas ou em plantações concentradas? 1 = dispersas 2 =plantação concentrada 9 = outro (especificar) _____________ B.6 Como conseguiu as suas árvores? 1 = herança 2 = compra 3 = oferta dum familiar 4 = Aluguei 5 = outro (especificar) __________________ ___________________ (999=não sabe) B.7 Há quanto tempo você é dono de pelo menos algumas árvores de castanha de cajú (# de anos)? ___________________ (999=não sabe) B.8a Quantas destas árvores deram frutos na última colheita? ___________________ (999=não sabe) Se o entrevistado responder com um número → B.9a B.8b Se o respondente não consegue dar o número certo, regista o intervalo 1 = 0-50 2 = 51-100 3 = 101-200 4 = 201-500 5=mais de 500 Qual é o número TOTAL das suas árvores que: # de árvores B.9a São muito novas para produzir castanha? (menos de 9 anos de idade) ___________________ (999=não sabe) Se o entrevistado responder com um número → B.10a B.9b Se o respondente não consegue dar o número certo, regista o intervalo 1 = 0-50 2 = 51-100 3 = 101-200 4 = 201-500 5=mais de 500 80 Pergunta Códigos de Respostas (marque as respostas apropriadas) Salte B.10a Estão na sua idade pico de produção de castanha? (9-25 anos de idade) ___________________ (999=não sabe) B.10b Se o respondente não consegue dar o número certo, regista o intervalo 1 = 0-50 2 = 51-100 3 = 101-200 4 = 201-500 5=mais de 500 B.11a Estão em idade de declínio da produção de castanha? (25 anos ou mais velhas) ___________________ (999=não sabe) Se o entrevistado responder com um número → B.12 B.11b Se o respondente não consegue dar o número certo, regista o intervalo 1 = 0-50 2 = 51-100 3 = 101-200 4 = 201-500 5=mais de 500 B.12a São muito velhas para produzir castanha? ___________________ (999=não sabe) Se o entrevistado responder com um número → B.13 B.12b Se o respondente não consegue dar o número certo, regista o intervalo 1 = 0-50 2 = 51-100 3 = 101-200 4 = 201-500 5=mais de 500 B.13 Nos últimos 12 meses, quantos novos cajúeiros você plantou? ___________________ (999=não sabe) Mais do que 0 → B.15 B.14 Porque é que você não plantou nos últimos 12 meses? 0 = não tenho acesso a mudas/germilings 1 = não dá dinheiro 2 = não tem mercado 3 = requere muita mao-de-obra 9 = outro (especificar) _____________ Passe para B17 B.15 Que tipo de material de plantação foi utilizado? 1=sementes 2=enxertos 3=cortes locais B.16 Qual foi a fonte deste material de plantio? 1 = viveiro próprio de cajúeiros 2 = produtores vizinhos 3 = comerciantes 4 = organizações não governamentais (ONG) 9 = outro (especificar) ________________ B.17 Existe um viveiro de cajúeiros na sua comunidade? 0 = não 1 = sim 2 = não sabe B.18 Será que você perdeu alguma parte da sua produção na colheita mais recente? 0 = não 1 = sim 2 = não sabe 0 ou 2 → B.20 B.19 Quais foram as causas da perda? 1 = deterioração (apodrecimento) 2 = roubo 9 = outro (especificar) ________________ 81 B.20 Quais são as principais pragas/ doenças que afectam os seus cajúeiros? Indique todas que forem apropriadas 0 = nenhuma 1 = Antracnose (lesões de cor laranja a castanho ou vermelhas) 2 = Bolor 3 = Mancha foliar 4 = Insecto do Coco 5 = Besouro do cajú 9 = outro (especificar) ________________ B.21 Será que você utilize algum produto químico (pesticidas, fungicidas, adubos) na cultura de cajúeiros? 0= não 1 =sim 2=não sabe B.22 Beneficiou de serviços de pulveracação nos cajúeiros? 0= não 1=sim 2=não sabe B.23 Será que você pretende plantar cajúeiros no próximo ano? 0= não 1=sim 2=não sabe 1→ B.25 B.24 Porque você não pretende plantar árvores no próximo ano? 1=falta de dinheiro 2=demanda fraca/ preços baixos 3=produzo tudo o que quero/ consigo 9 = outro(especificar) _______________ B.25 Será que você utiliza mão-de-obra contratada na sua cultura de cajúeiros ? 0= não 1=sim 2=não sabe 0→ B.28 B.26 Quantos trabalhadores você contratou durante a última colheita? ___________________ (999=não sabe) B.27 Como você pagou ao(s) trabalhador(es) ? 1 = dinheiro 2 = troca de produtos de castanha de cajú 3 = troca de outros produtos 9 = outro (especificar) B. 28 Como se faz a colheita de cajú? 1=tira a fruta da árvore 2=deixa a fruta cair no chão e recolhe 3=outro (especficar) _____________________ B.29 Qual é a superfície que se usa para secar a castanha? 1= Chão duro 2=lona 3=sacos 4=estrutura de caniço/bambu/pau 5=outro (especificar) _______________ B.30 Por quanto tempo você seca a produção de castanha de cajú? 1 = 1-3 dias 2 = 4-5 dias 9 = mais de 5 dias 82 B.31 Como você armazena a sua produção de castanha de cajú? 1 = sacos 2= amontoar ao ar livre 3= caixas 9 = outro (especificar) _______________ B.32 No local onde você armazena castanha tem circulação de ar (ventilação)? 0= não 1=sim 2=não sabe B.33 Quais são os três problemas mais críticos que você enfrenta na produção de castanha? (Entrevistador, se o produtor disser “precos baixos” peça para falar de outros problemas para além de preços baixos. Ordene os em níveis de prioridade, 1 = problema mais sério) 1. ___________________________ 2. ___________________________ 3. ___________________________ B.34 Você precisa de material ou equipamento para a produção e/ou processamento de castanha? 0= não 1=sim 2=não sabe 0,2 → C.1 B.35 Que tipo de material e/ou equipamento voce precisa? Registe apenas os 3 mais importantes 1. ___________________________ 2. ___________________________ 3. ___________________________ C. PRÁTICAS DE CULTIVO DE CASTANHA DE CAJÚ Prática (entrevistador – faça as perguntas especificamente para cada prática) Você está familiarizado com está prática? Você aplica esta prática em algum dos seus cajúeiros? Há quantos anos é que você tem aplicado esta prática? Qual é a percentagem de todos os seus cajueiros, aproximadamente, é que você aplica esta prática? Você aplica esta prática em qualquer outra cultura sua? 0=não; 1=sim 0=não; 1=sim, 999= não sabe 999= não sabe 1 = 25% ou menos 2 = 26 – 50% 3 = 51 – 75% 4 =76 – 99% 5 = 100% 0=não; 1=sim; 0→próxima prática 0,999→próxima prática C.1 Cobertura morta (mulching) C.2 Consociação com leguminosas C.3 Consociação com outras culturas C.4 Poda (copa) C.5 Matéria orgânica/ fertilizante orgânico C.6 Adubos/Fertilizante inorgânico C.7 Plantio de material enxertado C.8 Sacha na produção de cajúeiros C.9 Pulverização de árvores (pela Incajú e outros) C.10 Pó amarelo (enxofre) para controlar fungos C.11 Evitar queimadas 83 D. FORMAÇÃO NO CULTIVO DA CASTANHA DE CAJÚ Pergunta Código de Resposta (marque as respostas apropriadas) Salte D.1 Será que você tem acesso ao serviço de extensão ? 0= não 1=sim 2=não sabe 0 ou 2 → D.4 D.2 Será que o extensionista tem conhecimento do cultivo de castanha de cajú ? 0= não 1=sim 2=não sabe D.3 Será que você está satisfeito com a qualidade dos serviços de extensão que você recebe? 1= muito insatisfeito 2 = insatisfeito 3= satisfeito 4= muito satisfeito D.4 Será que você recebeu alguma formação em práticas de cultivo de castanha de cajú? 0 = não 1 = sim 2= não sabe 0 ou 2 → E.1 D.5 Você teve formação em relação a que tipos de práticas (Entrevistador, não faça perguntas sobre práticas específicas, registe somente as práticas mencionadas pelo entrevistado). Após uma prática ter sido descrita, pergunte novamente ao entrevistado ‘existem outras práticas em que tenhas sido formado?’ Pergunta Quem deu a formação? Será que você praticou o que foi aprendido durante a formação? Porque você NÃO prática o que foi ensinado na formação? Até que ponto a formação foi útil? Códigos das respostas Marque ‘1’ para todas as práticas mencionadas pelo entrevistado e ‘0’ para todas aquelas que não foram mencionadas 0= não 1= sim 1=empresa 2= SDAE e ou SPA 3= ONG 4= não sabe 5= Incajú 9 = outro (especifique) 0= não 1= sim 1= não pode comprar os materiais/ insumos 2= não acha que vai aumentar os rendimentos 3= não recebeu formação suficiente 4= esqueceu como fazer a prática 5= muito trabalho 9= Outro (especifique) 0= nãp foi útil 1= foi útil de algumaforma 2= muito útil Salte 0→Próxima prática 1 → D.5.E Prática D.5.A D.5.B D.5.C D.5.D D.5.E 1 Poda de cajúeiros (umbrella canopy) 2 Espaçamento apropriado entre cajúeiros 3 Sacha na produção de cajúeiros 4 Método apropriado de pulverização de cajúeiros 84 E. PRODUÇÃO E VENDA DA CASTANHA DE CAJÚ Pergunta Códigos de Respostas (circle appropriate answers) Skip E.1 Qual é a quantidade de castanha de cajú bruta (CCB) que as suas árvores produziram na última colheita? _______________ (999=não sabe) E.2 Qual é a Unidade de medição? 1 = kg 2 = saco 50 kg 3 =saco 100 kg 4 =lata (20 litros) 9 = Outro (especificar)________________ E.3 Nos últimas cinco campanhas, como variou a sua produção? 0=diminuiu 1=manteve-se 2=aumentou 0 → E.5 1 → E.6 2 → E.4 E.4 Quais são os motivos do aumento? (permitidas respostas múltiplas) 1= aumento do número de árvores produtoras 2=melhor gestão das árvores 3=uso de melhores/ mais insumos 4=disponibilidade de mais mão-de-obra 5= mais rentável produzir 6=obteve crédito para investimento 9= outro (especificar)____________________ Depois de registar a resposta, avance para E.6 5 Método apropriado de secagem de castanha 6 Consociação entre o cajúeiro e outras culturas 7 Plantio e cuidado de mudas de cajúeiro 8 Enxerto de ramos de alta qualidade em mudas de cajúeiros 9 Práticas agrícolas orgânicas ou de Comércio Justo 10 Tempo apropriado para a colheita da castanha 11 Selecção das melhores castanhas 12 Armazenamento apropriado da castanha 13 Produção e utilização de fertilizante orgânico 14 Produção e utilização de pesticidas orgânico 15 Evitar queimadas 16 Cobertura morta/mulching 17 Outro (especificar): __________ 85 Pergunta Códigos de Respostas (circle appropriate answers) Skip E.5 Quais são os motivos da diminuição (permitifdas respostas múltiplas) 1=doença das árvores 2= pragas 3=árvores muito velhas 4=falta de mão-de-obra para cuidar das árvores 5=não é rentável produzir 6=alterração dos padrões meteorológicos 7 = erosão 9 = outro (especificar)______________ E.6 Qual é a quantidade de castanha de cajú bruta (CCB) que você vendeu na última colheita? _______________ (999= não sabe) 0 ou 999→ F.1 E.7 Qual é a Unidade de medição 1 = kg 2 = saco 50 kg 3 =saco 100 kg 4 =lata (20 litros) 9 = outro (especificar)________________ E.8 Quantas vezes você vendeu a castanha de cajú durante a última campanha? _______________ (999= não sabe) E9. Marketing (Preencha a primeira coluna com a quantidade vendia e o resto das colunas com as opções colocadas juntamente com os títulos). Quantidade vendida Preco # venda Quantidade vendida Unidades de medida Preço unitário (Mt) Unidades de medida Tipo de comprador Número 1=kg 2= saco 50 kg 3=saco 100 kg 4=lata 20 litros 5=balde de 10 litros 6=outro (especificar) ________________ Número 1=kg 2= saco 50 kg 3=saco 100 kg 4=lata 20 litros 5=balde de 10 litros 6=outro (especificar) _______________ 1=fabrica 2=grupo/associação/cooperativa 3=vendedor ambulante 9 = outro (especificar) E.9 E.10 E.11 E.12 E.13 1 2 3 4 5 86 Pergunta Códigos de Repostas (marque as respostas apropriadas) Salte E.14 Você está satisfeito com o preço que recebe para castanha com casca (RCN)? 0= não 1=sim E.15 Você produz vinho de cajú? 0= não 1=sim 2=não sabe 0 ou 999 → E.17 E.16 Quantos litros de vinho de cajú você produziu na última época? Litros _________________ E.17 Quanto dinheiro (MT) você fez da venda de vinho de cajú, na última época ? MZN________________ E.18 Você produz sumo a partir do cajú? 0= não 1=sim 2=não sabe 0 ou 999 → E.20 E.19 Quantos litros de sumo você produziu na última época? lt _________________ E.20 Quanto dinheiro (MT) você fez da venda de sumo de cajú na última época ? MZN________________ E.21 Você vendeu cajú? 0= não 1=sim 2=não sabe 0 ou 999 → E.22 E.22 Quanto dinheiro (MT) você fez da venda de cajú na última época ? MZN________________ E.23 Será que você já enfrentou uma situação em que compradores de castanha prometeram comprar a castanha mas não apareceram ? 0 = não 1=sim 2=não sabe E.24 Qual é o factor mais importante que você considera ao escolher os compradores da sua castanha ? 1 = oferta do melhor preço 2 = confiança (pode-se confiar para fazer compras) 3 = oferece insumos e outros serviços 4 = oferece crédito (paga antes da entrega) 5 = tenho apenas um comprador 9= outro (especificar) ___________________ E.25 Será que algum comprador já lhe adiantou insumos em troca da garantia de fornecimento de castanha de cajú bruta (CCB) 0 = não 1=sim 87 F. PRÁTICAS DE GESTÃO AGRÍCOLA Pergunta Códigos de Resposta (marquee as respostas apropriadas) Salte F.1 Será que você arquiva registos de produção? 0= não 1=sim 2=não sabe F.2 Será que você arquiva registos de receitas e despesas? 0= não 1=sim 2=não sabe F.3 Será que você guarda registos dos bens do seu agregado familiar? 0= não 1=sim 2=não sabe F.4 Já ouviu falar de “produção organica”? 0= não 1=sim 2=não sabe 0 ou 2 → G.1 F.5 Será que você sabe dos requisitos para se alcançar os padrões de “produção organica”? 0= não 1=sim 2=não sabe 0 ou 2 → G.1 F.6 Será que você segue os padrões de “produção orgânica”? 0= não 1=sim 2=não sabe G. ASSOCIAÇÕES DE PRODUTORES Pergunta Códigos de Respostas (marquee as respostas apropriadas) Salte G.1 Será que existe algum grupo de produtores na sua área? 0= não 1=sim 2=não sabe 0 ou 2 → H.1 G.2 Você é membro de algum grupo de produtores de castanha de cajú? 0= não 1= sim 0 → G.6 G.3 A que grupo você pertence? 1=grupo 2=associação 3=cooperativa Outro (especificar) ___________ G.4 Quais são os motivos pelos quais você se juntou ao grupo? 1= obter melhores preços 2= acesso a crédito 3= acesso a insumos 4= acesso a armazenamento 9=outro (especificar)________________ 88 G.5 Você acha que o seu grupo tem capacides suficientes para procurar compradores? 0= não 1=sim 2=não sabe responda a pergunta e passe para a secção a seguir→ H.1 G.6 Porque você não é membro da associação? 1 = não tenho tempo 2 = não acho que seja eficiente 3 = é muito caro ser membro 9= outro (especificar)________________ H. ACESSO A CRÉDITO PARA CAJÚ Pergunta Códigos de Respostas (marque as respostas apropriadas) Salte H.1 Existe alguma organização (formal e/ou informal) que providencia crédito aos AFs na comunidade? 0= Não 1=sim 2=não sabe 0,2 → H.3 H.2 Que tipo de organizações? 1. Agiotas 2. Grupos rotativos de poupança 3. Grupos de poupança e crédito 4. ONGs 5. Bancos 9. Outro (especificar) ________________ H.3 Existe crédito disponível para o cultivo de castanha? 0= não 1=sim 2=não sabe 0,2 → I.1 H.4 Você tem acesso a crédito para o cultivo de cajú ? 0= não 1=sim 2=não sabe 0 ou 2→ I.1 H.5 Você recebeu crédito no ano passado para o cultivo de cajúeiros ? 0= não 1=sim 2=não sabe 0 ou 2→ I.1 H.6 Qual foi a fonte do crédito? 1 = banco 2 = AKF Grupos de Poupança Comunitários 3 = outras ONG grupos de poupança 4 = familiares/ amigos 5 = comerciantes/ negociantes 9 = outro (especificar)________________ H.7 Qual é o valor total de crédito que você recebeu para o cultivo de cajú ? MZN _______________________ 89 I. PRINCIPAIS PROBLEMAS SOCIAIS NA COMUNIDADE Pergunta A B C I1 Na sua opinião, quais são os 3 principais problemas, em ordem de prioridade, que a sua aldeia /áreas enfrentam (Não leia as opções abaixo) |___||___| |___||___| |___||___| Código para Pergunta I1 00. Nenhum 10. Pobre liderança da aldeia/corrupção 01. Problemas com a educação 11. Roubo/crime 02. Problemas com serviços de saúde 12. Alterações climáticas 03. Problemas com electricidade 13. Dominação econômica por imigrantes 04. Problemas com água 14. Problemas de vias de acesso 05. A falta de acesso ao capital/insumos 15. Destruição de culturas por animais selvagens 06. Desemprego / subemprego 16. Problemas com lixo 07. Sistema de Transporte debilitado 17. Falta de compradores 08. Irresponsabilidade dos homens 98. Outro: _____________________ 09. Gravidez precoce 90 Annex 5. Selected Communities by District and Province Province District Admin Posts Community Cabo Delgado Mueda N'gapa Lunango Cabo Delgado Mueda N'gapa Nonge Cabo Delgado Mueda N'gapa Nastengue Cabo Delgado Mueda Mbuo Nangada Cabo Delgado Nangade M'tambo Lijungo Cabo Delgado Nangade M'tambo Mualela Cabo Delgado Nangade Nangade Sede Lukuamba Cabo Delgado Nangade Nangade Sede Unidade Cabo Delgado Palma Pundanhar Chidololo Cabo Delgado Palma Pundanhar Pundanhar Cabo Delgado Palma Pundanhar Chicuedo Cabo Delgado Palma Pundanhar Nhica do Rovuma Cabo Delgado Muidumbe Chitunda Litapata Cabo Delgado Muidumbe Chitunda Chitunda Cabo Delgado Muidumbe Muidumbe Sede Mandela Cabo Delgado Muidumbe Muidumbe Sede Namacande Cabo Delgado Mocímboa de Praia Diaca Panjele Cabo Delgado Mocímboa de Praia Diaca Chitolo Cabo Delgado Mocímboa de Praia Diaca Ntotwe Cabo Delgado Mocímboa de Praia Diaca N'nango Cabo Delgado Metuge Metuge Sede Pulo Cabo Delgado Metuge Metuge Sede Messanja/ Ntessa Cabo Delgado Metuge Metuge Sede Taratara Cabo Delgado Metuge Metuge Sede Bandar Cabo Delgado Chiúre Chiúre Sede Mpeule Cabo Delgado Chiúre Chiúre Sede Nanihuta Cabo Delgado Chiúre Chiúre Sede Namania/Maningane Cabo Delgado Chiúre Chiúre Sede Milamba Cabo Delgado Macomia Chai Litandacua Cabo Delgado Macomia Sede Nova Vida Cabo Delgado Macomia Sede Xinavane Cabo Delgado Macomia Macojo Cogolo Nampula Meconta Meconta Sede Nivaltene Nampula Meconta Meconta Sede Namiruto Nampula Meconta Meconta Sede Nemarra Nampula Meconta Meconta Sede Minhar Nampula Mogovolas Nametil Sede Namuito 91 Nampula Mogovolas Nametil Sede Murezene 'A,B,C' Nampula Mogovolas Nametil Sede Mucutanala 'B,A,C' Nampula Mogovolas Nanhupo Rio Maileliha Nampula Angoche Boila Namitória Nacopa Nampula Angoche Boila Namitória Muerauera Nampula Angoche Boila Namitória Muitiua Nampula Angoche Boila Namitória Muahivire Nampula Moma Chalaua Naiuire Nampula Moma Chalaua Murioze Nampula Moma Chalaua Kuline Nampula Moma Chalaua Mavuco Zambézia Gile Gilé Sede Muirela Zambézia Gile Gilé Sede Naholoco Zambézia Gile Gilé Sede Malema 2 Zambézia Gile Gilé Sede Nanepa Zambézia Pebane Pebane Sede Muromone Zambézia Pebane Mualama Alto Maganha Zambézia Pebane Mualama Mugome Zambézia Pebane Naburi Txalalane 92 Annex 6. Processor Topical Outline 1. Sales i. Who are your major buyers, what are their requirements? ii. What are the most desirable grades? iii. Do you primarily ship FCL or mixed grades? iv. Do you sell RCN or CNSL or any by-product v. Any specialty market focus (fair trade, organic or traceable) 2. Processing i. Organization of warehouse (sections) identification of stocks origin? ii. % manual vs. mechanized processing by activity iii. Brokens/whole ratio iv. Kernels/RCN ratio v. HACCP: Certified?, where in process, Food safety standards like HACCO, ACA seal or else vi. Packaging strategies and options vii. Wage costs (total or per ton) Individual average and cost/Mt viii. Traceability documentation In processing, batch process, production losses etc. etc. 3. Procurement procedures i. Broker or direct? Or cooperatives/ associations/ forums/CAN ii. Documentation on procurement iii. What limits buying? (Limited by working capital, physical processing capacity, limited availability of product, other) iv. Do you have consistent relationships with sellers? v. Payment terms (on delivery, pre-payment, etc) vi. Payment premium on quality and volumes, or criteria to give premium to seller vii. Exclusive sourcing? (yes/no) viii. How do you track nuts? ix. Level of traceability x. What kind of screening process do you follow? 4. Challenges i. Sourcing raw material ii. Working capital iii. Processing capacities iv. Equipment needs v. Meeting needs of buyers vi. Financing investments vii. Food safety standards