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Determinants of Value Addition Choices among Cassava Farmer- Processors in Benue State, Nigeria

Ugah, E S, Ashiko, F TG and, Atagher, M M

Abstract

The study analyzed the determinants of value-addition choices among cassava farmer-processors in Benue State, Nigeria. A three-stage sampling procedure was used to select 223 respondents for the study. A well-structured questionnaire was used to obtain primary data. Data collected were analyzed using descriptive statistics (mean, frequency and percentage), ANOVA and Logistic regression. The results showed that the major products of the value-adders were cassava flakes (garri), cassava paste (akpu/fufu) and dried cassava (kpor/alibo). Results of the Logistic regression of factors influencing choice of value-added product showed that processing income (p < 0.05) cost of processing (p < 0.01) frequency of processing (p < 0.10), and access to extension services (p < 0.05) significantly influenced the choice of value-added products. The Likelihood Ratio (LR) Chi-Square of 165.07 suggests that the model fits significantly. The P-value was also found to be significant (p-value = 0.0000), confirming that the modelled variables determine farmer-processor’s choice of cassava paste processing in Benue State, Nigeria. The pseudo R2 of 0.5562 implied that the independent variables accounted for 55.62% variation in the dependent variable. Major challenges in the business of cassava processing were inadequate funding (83%), Fluctuation in prices of processed cassava products (74%), inadequate modern processing equipment (69.1%), High marketing cost (59.6%), unpredictable climate (58.7%) and limited machinery capacity (46.6%) were the most important factors militating against cassava processing in the study area The study, therefore, recommends that Governments should develop and implement policies aimed at increasing access to affordable financing options for cassava farmer-processors as this will enable farmers to obtain improved or modern processing equipment to increase their processing efficiency and income.

Keywords

Value-additionChoiceFarmer-processorsValue-added productslogistic

References

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Table 1: Distribution of Cassava Farmer-Processors according to their Socio-economic Characteristics (n=223) Variables Frequency of Percentage (%) Mean Farmer-Processors Gender Male 111 49.8 Female 112 50.2 Age 39.4 ? 20 3 1.3 21 – 35 82 36.8 36 – 50 115 51.6 51 & above 23 10.3 Membership of Cooperative Member 72 32.3 Non Member 151 67.7 Processing Experience ? 10 158 70.9 11 – 20 47 21.1 21 – 30 12 5.4 31 & above 6 2.7 10.4 Years in Education ? 6 47 21.1 7 – 12 97 43.5 13 & above 79 35.4 11.4 Household Size ? 4 53 23.8 5 – 12 148 66.4 13 – 20 15 6.7 21 & above 7 3.1 7.97 Access to Extension Service Access 36 16.1 No Access 187 83.9 Access to Credit Access 59 26.5 No Access 164 73.5 Non-Processing Income Source Available 140 62.8 Not Available 83 37.2 Annual Processing Income (N ‘000) ? 50 14 6.3 51 – 150 58 26.0 151 – 250 53 23.8 251 & above 98 56.1 403,293.27 Source: Computed from field survey data, 2023 Table 2. Distribution of Respondents based on Forms of Value-added Cassava Products Produced Forms of Processed Cassava Frequency of Percentage (%) Cassava Processors Cassava Paste (Akpu/Fufu) 98 43.9 Cassava Flakes (Garri) 90 40.4 Dried cassava (kpor/alibo) 56 24.1 Starch 2 0.9 Charcoal 1 0.4 Note: *Multiple responses were obtained Source: Computed from field survey data, 2023 Table 3: Logistic Result of Factors Influencing Cassava Farmer-Processor’s Choice of Cassava Value added products Variables Coefficient Standard Z – value P>|z| Marginal Error Effect Age 0.005 0.024 0.20 0.840 0.000 Gender 0.012 0.502 0.02 0.98 0.001 Household Size 0.012 0.071 0.17 0.865 0.001 Educational status 0.021 0.034 0.62 0.536 0.002 Processing Experience -0.046 0.042 -1.08 0.282 0.004 Mem. of Cooperative 0.288 0.491 0.59 0.558 0.027 Access to Ext. Service -1.801 0.808 -2.23 0.026** 1.169 Frequency of Processing 0.124 0.075 1.65 0.098* 0.011 Processing Income -0.000 6.84 -2.20 0.028** 1.41 Cost of processing 0.000 0.000 6.54 0.000*** 0.000 Off Processing Income -2.18 2.57 -0.85 0.395 2.05 Amount of Credit Rec. 5.50 6.73 0.82 0.414 1.19 Constant -1.190 1.180 -1.01 0.314 *significant at 10% **significant at 5% *** significant at 1% Likelihood Ratio Chi2 (13) = 165.07 Prob > chi 2 = 0.0000 Pseudo R2 = 0.556 Source: Computed from field survey data, 2023 Table 4: Distribution of Respondents on Challenges faced in Cassava Value Addition Challenges Frequency of Percentage (%) Cassava Processors Inadequate Capital 185 83 Inadequate Modern Processing Equipment 151 68.1 Fluctuation in Prices of Processed Products 165 74 Lack of Technical know-how 64 28.7 Lack of marketing facilities 94 42.2 Limited Machinery Capacity 104 46.6 Unpredictable Climate 131 58.7 High marketing cost 133 59.6 Stressful and Time-consuming Nature of 14 6.3 Processing Note: *Multiple responses were obtained Source: Computed from field survey data, 2023