University of Abuja, Nigeria
RURAL HOUSEHOLD PARTICIPATION IN CASSAVA
VALUE CHAIN IN KOGI STATE, NIGERIA
Dr. Moradeyo A. Otitoju

#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.

#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.

#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.

#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.

#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.

#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

#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

#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

#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.

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

#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.

#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.

THANK YOU