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Dr. Otitoju, M. A._2023 AGRODEP Annual Conference

  2. #2023 AGRODEP CONFERENCE Introduction Nigeria, which accounts for over 21% of the market, produces the most cassava worldwide (FAO, 2013). According to the International Institute of Tropical Agriculture (IITA), Benue and Kogi states in northern Nigeria are the highest producers of cassava. Smallholder farmers produce the majority of the country's cassava for subsistence or small-scale processing, just a little amount is produced for use in textile, pastry, cuisine, ethanol, animal feeds, and other industries (Knipscheer et al., 2007).  Cassava value chain ranks among the most significant in Nigeria's agricultural industry, but it has challenges with respect to processing capacity, post-harvest spoilage, storage, equipment, and market accessibility.
  3. #2023 AGRODEP CONFERENCE Introduction  The International Fund for Agricultural Development (IFAD) has been directed by the Federal Government of Nigeria (FGN), through the Country Programme Evaluation (CPE), to concentrate its intervention on the agricultural sector, with a focus on improving productivity and access to markets, in order to boost the incomes and food security of the country's underprivileged rural households.  The Agricultural Transformation Agenda (ATA), which outlines a commodities value chain approach, was the impetus for the establishment of the Value Chain Development Programme (VCDP), which is closely aligned with changing government strategy and policy (IFAD, 2012). Six states in Nigeria are home to the VCDP, which focused on cassava and rice, including (Anambra, Benue, Ebonyi, Niger, Ogun, and Taraba).  Participation in the vaue chain will guide in formulating appropriate programmes that will help in ensuring values are addded to cassava.
  4. #2023 AGRODEP CONFERENCE The thrust of the study The objectives of the study are: i. identify areas of participation in the cassava value chain among the respondents in the study area ii.identify the factors responsible for the participation of rural households in the operations along the cassava value chain in the study area. iii. examine the constraints responsible for their level of participation in the cassava value chain.
  5. #2023 AGRODEP CONFERENCE Methodology The study was conducted in Kogi State, Nigeria. Kogi State is a non-participating State in the FGN/IFAD Value Chain Development Programme (VCDP). Sampling Technique: The multistage sampling technique was used to select a total of 289 rural cassava farming households for this study • Data Collection instrument: Data were collected using a well structured questionnaire.
  6. #2023 AGRODEP CONFERENCE Methodology Data Analysis: Objectives (i) was achieved using descriptive statistics such as mean, percentages, and frequency distribution. Objective (ii) was realized using a multinomial logit model. The equation using a four-category response (value 1 if production, value 2 if processing, value 3 if it is marketing, and value 4 if distribution) as in the model for this study. Objective (iii) was achieved using factor analysis using principal component analysis as the extraction method.
  7. #2023 AGRODEP CONFERENCE Results: Socio-economic characteristics of rural households Socio-economic variable Mean distribution Age 48.32 years Gender Frequency %Distribution Male 227 79.1 Female 60 20.9 Marital Status Single 226 78.7 Married 61 21.3 Level of Education No Formal Education 71 24.7 Formal Education 216 75.3 Awareness of VCDP Yes 203 70.7 No 84 29.3 Extension Visits Yes 219 76.3 No 68 23.7 Total 287 100
  8. #2023 AGRODEP CONFERENCE Results: Areas of Participation in the cassava value chain Areas of Participation in the cassava value chain Frequency Percentage % No participation 45 15.7 Production 138 48.0 Processing 41 14.3 Marketing 63 22.0 Total 287 100
  9. #2023 AGRODEP CONFERENCE Results:Factors Responsible for the Participation of Rural Households in the Operations Along the CSV Production Processing Marketing Distribution Variables Parameters Coefficient Coefficient Coefficient Coefficient Age (X1) β1 -0.0922 (-2.36)** -0.0543 (-1.78)* 0.0502 (-1.48) -0.057 (-1.56) Sex (X2) β2 -0.793 (-0.74) -1.824(-2.18)*** -1.9105 (-2.07)** -1.595 (-1.80)* Years of schooling (X3) β3 -0.00963(-0.11) -0.0489 (-0.58) -0.0324 (-0.36) 0.000243 (-0.001) Farming experience (X4) β4 0.252 (2.95)*** 0.1564 (2.08)** 0.1417(1.83) 0.1911 (2.43)** Cassava farming experience (X5) β5 -0.331 (-3.21)*** -0.278 (-2.94)*** -0.233 (-2.36)** -0.272 (2.86)*** Employed people (X6) β6 0.0786 (0.45) 0.1629 (0.99) 0.1033(0.60) 0.0920 (0.55) People in the household (X7) β7 -0.287 (-0.46) 0.469 (1.27) 0.587 (1.53) 0.3811 (0.99) Farm Distance (X8) β8 0.1015 (0.61) 0.00694 (0.05) 0.0597 (0.39) -0.165 (-0.98) Annual Income (X9) β9 -1.1610 (-1.24) -1.0614 (-1.52) -1.521 (-1.91)* -1.80 (-2.32)** Membership of Association (X10) β10 4.12e-06 (0.72) 5.18e-06 (0.92) 4.47e-06 (0.76) 3.78e-06 (-0.61) Access to credit (X11) β11 -1.224 (-0.89) -0.627(-0.51) -0.686(-0.56) -0.7095(-0.55) Extension visit (X12) β12 -0.9026(-0.67) -2.024 (-1.54) -1.0293(-0.81) -1.534 (-1.19) Access to radio (X13) β13 1.782(1.23) 0.362(0.13) -0.453 (-0.37) 0.534 (0.44) Access to Electricity (X14) β14 15.381 (5.70)*** 14.208 (5.37)*** 14.430 (5.41)*** 14.5067 (5.47)*** Literacy Ratio(X15) β15 0.779 (1.25) 0.815 (1.31) 0.8432 (1.35) 1.0204 (1.64) Dependency Ratio(X16) β16 0.6103 (1.86)* 0.7732 (2.42)** 0.700046 (2.17)** 0.6065 (1.90)* Constant β0 0.7214 (0.32) 3.496 (1.87)* 2.1154 (0.97) 3.076 (1.50) Log Pseudo likelihood= -300.66817, Number of observations = 286, Wald chi (64) = 980.61, Prob. > chi2= 0.0000, Pseudo R2= 0.2227
  10. #2023 AGRODEP CONFERENCE Factors Responsible for the Participation of Rural Households in the Operations Along the Cassava Value Chain in Kogi, State, Nigeria The result of the multinomial logit regression model analysis for the factors responsible for the participation of rural households in the operations along the cassava value chain in Kogi, State, Nigeria revealed that cassava farming experience and income negatively influenced the rural household’s participation in production, processing, and marketing as opposed to the distribution of cassava production in the study area Farming experience, access to electricity and dependency ratio positively influence their participation in the cassava production.
  11. Constraints to Rural Households of Participation in Cassava Value Chain Operations in the Study Area • The Kaiser criterion (1960) was used for selecting the number of underlying factors or principal components explaining the data. • In this study, the number was decided by leaving out components with corresponding Eigenvalues. • Variables that have factor loading of less than 0.50 were not used while variables that loaded in more than one constraint were also discarded in line with Madukwe (2004). • After rotation, the first factor accounted for 13.2% of the variance, the second factor accounted for 12.2% of the variance, the third factor accounted for 11.5% of the variance and the fourth factor accounted for 10.9% of the variance. • The true factors that were retained explained 47.8% of the variance in the 15 constraining factors or variable components. Constraint Variables Factor 1 Factor 2 Factor 3 Factor 4 Communalities Illiteracy of the household head 0.702 0.531 Lack of adequate extension programme directed towards the Cassava value chain (CVC) 0.718 0.608 Poor access to information by the rural household in CVC 0.670 0.572 Insufficient knowledge of credit source to cassava Value chain operations 0.633 0.538 Poor agricultural extension service delivery 0.745 0.575 Insufficient funds/ finance 0.580 0.379 Inadequate government policies to encourage rural 0.626households in policy-making decision 0.676 0.525 Lack of access to and awareness about NGOs programmes for value chain operation 0.626 0.406 High cost of fertilizers and other inputs 0.662 0.569 Non-availability of hired labour 0.696 0.518 The religious belief of the household heads about CVC 0.871 0.787 Lack of adequate access to supporting institutional facilities e.g cooperatives 0.723 0.568 High cost of improved value chain operations materials 0.528 0.361 High cost of farmland 0.610 0.487 The unwillingness of the farmers to take risks involved in input supply, production, processing, and marketing in CVC 0.761 0.648 Percentage (%) of total variance 13.2 12.2 11.5 10.9
  12. #2023 AGRODEP CONFERENCE Constraints to Rural Households of Participation in Cassava Value Chain Operations in the Study Area • Using the varimax-rotated principal component factor analysis the constraints to rural household participation in the cassava value chain in the study area are: Factor 1: Literacy, extension, information, and credit constraints Factor 2: Poor agricultural extension, Finance, public policies, and NGOs awareness constraints Factor 3: High cost of inputs, hired labour, and religious beliefs constraints Factor 4: Risk aversion in cassava value chain operations constraints.
  13. #2023 AGRODEP CONFERENCE Recommendations • The study recommends that the Government and other stakeholders in cassava value chain should: encourage literacy in rural households through formal and informal agricultural training centers ensure that electricity/power supply is provided for enhancement of particpation in cassava value chain. encourage investment in cassava value chain operations, and improved technological infrastructure in rural areas.