Determinants of Food Security Status among Irrigated Vegetable Farmers in Northern Agricultural Zone of Bauchi State, Nigeria

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Available Online at www.aextj.com
Agricultural Extension Journal 2018; 2(3):176-183
ISSN 2521 – 0408
RESEARCH ARTICLE
Determinants of Food Security Status among Irrigated Vegetable Farmers in
Northern Agricultural Zone of Bauchi State, Nigeria
A. A. Bose
Department of Agricultural Economics and Extension, Abubakar Tafawa Balewa University, Bauchi, Nigeria
Received: 05-07-2018; Revised: 30-07-2018; Accepted: 25-08-2018
ABSTRACT
The study examined factors influencing food security status of irrigated vegetable farmers and price
trend of vegetables in Northern Agricultural Zone of Bauchi State, Nigeria. Multistage sampling
technique was adopted where 360 framers were randomly selected for the study. Data were collected
using structured questionnaire and analyzed using descriptive statistics as well as binary logistic model.
The result reveals that average quantity produced per hectare of tomato, sweat pepper, and onion was
about 227 baskets (6810 kg), 185 bags (7400 kg), and 168 bags (18480 kg), respectively. The net income
was N187,245.00 ($520.00), N145,114.00 ($403.00), and N330,761.00 ($919.00) per hectare, for the
respective vegetable crops. The result on binary logistic model indicates that the quantity of vegetable
produced was found to be positively related with farmers food security status and statistically significant
at P = 0.001. Monthly income had a positive odds ratio (2.214) and statistically significant at P = 0.000.
The result also reveals that age was significant (P = 0.014) and positively related with a food security
status of the farmers with the odds ratio of 0.943. The pseudo R2
was found to be 0.481, implying that
about 48% of variation in the dependent variable is explained by independent factors included in the
model. The result on price trend analysis indicates that seasonal variations occur in vegetable prices, for
several reasons such as demand and supply factors. Thus, the study recommends that farmers should
be provided with adequate information concerning prices, supply, and demand, especially at the local
level. Farmers should be encouraged to adopt improved technologies and new farming practices to boost
output. In addition, farmers should be encouraged to diversify the source of income to have more funds
to purchase other foodstuffs that they could not producing.
Key words: Determinants, farmers, food security, irrigated vegetable, Nigeria, price trend
INTRODUCTION
Food security means provision and access to
nutritionally sufficient and culturally accepted
food by each member of the household for healthy
life obtained through socially acceptable ways.
Food insecurity, on the other hand, is the uncertain
or limited access to nutritionally adequate and safe
food.[1]
Food availability is a problem for everyone
and, especially, for the developing world. Nigeria
still suffers from poverty and food insufficiency.[2]
In the recent time, there have been a lot of concerns
Address for correspondence:
A. A. Bose,
E-mail: abdullahi.bose@yahoo.com
expressed over the looming danger of food crisis
in many nations, including Nigeria. However, food
availability is a function of the combination of
domestic food stock, commercial food imports, as
well as the underlying determinants of each of these
factors. The determinants of food security differ at
different levels, i.e., from global to regional and
national to household and individual level because
food security is deemed to be a multidimensional
phenomenon encompassing climate change, civil
conflicts, natural disasters, and social norms.[1]
Irrigation has been identified to be a key part
in optimizing agricultural production for self-
sufficiencyinfoodproductionandpovertyreduction
in most developing countries in the world.[3]
The
long dry season experienced by farmers in the most
parts of Northeast Nigeria form part of the reasons

Bose: Determinants of food security status among irrigated vegetable farmers in Northern agricultural zone of bauchi state, Nigeria
AEXTJ/Jul-Sep-2018/Vol 2/Issue 3 177
why farmers seem to be shifting toward irrigation
schemes. According to Mani et al.,[4]
vegetable
production is an integral part of the Nigerian
agricultural sector. Vegetables are produced in
different agro-ecological zones, particularly by
small-scale farmers. Thus, its production has been
on-going for decades, providing employment and
income for the increasing population.[5]
Vegetable
crops give 5–10 times more yield per unit area
than cereals, and they are quick growing and short
duration. The short duration nature of vegetables
offers scope for raising two or more crops a year
and for fitting effectively in different cropping
system. In addition, most of the vegetable farmers
under current agricultural sector were characterized
by smallness of farm size, 0.25–1.00 hectares.
[6]
Furthermore, there is a need to understand the
pattern of price variations, price trends, monthly
seasonal indices, and their deviations to establish
policiesthathelpstabilizefoodprices.Itisexpected
that rural populace in various communities may
benefit from the outcome of the study toward
irrigated vegetable production as a source of
income and a means of attaining food security.
Objectives of the study
The study has the following specific objectives:
1. Assess the quantity of vegetable produced per
hectare in the study area;
2. Evaluate the profit level of irrigated vegetable
production in the area;
3. Examine the factors influencing food security
status of irrigated vegetable farmers; and
4. Examine the price trend of vegetable crops in
the study area.
Conceptual framework
Logit regression model
Different researchers employed different
methods for the analysis of binary data, but
many of them adopted logistic regression
technique including.[1,7,8]
Since the dependent
variable food security is qualitative in nature
means dichotomous, it can only take two values
either the presence of something or absence, so
by pursuing the conventional method of binary
response, it will either take the value of one or zero.
This value of 1 means that farmer is food secure
and zero means otherwise because this measure
of food security in binary manner yields results
which have more policy implications.[9]
Logistic
regression technique can be used to model the
relationship between the dichotomous dependent
variable and set of independent variables that are
hypothesized to affect the outcome. The logistic
regression model characterizing the status of
farmer food security is given by Oyebanjo et al.,[8]
2013, and Abdullah et al.[1]
1 1 2 2
1
    
 
=+ + + + 
 
i
i i i i i
i
P
Ln o X X n Xn
P (1)
This [Pi
/(1–Pi
)] is simply the odds ratio in favor of
food security (Fi
), i.e., the ratio of the probability
that the farmer is food secure to the probability
that it is not food secure. The subscript “i” shows
the ith
observation in the data. βo is the intercept
of the model, while X1, X2, X3 … Xn are the
explanatory variables. It is important to note that
the estimated coefficients do not directly affect
the change in corresponding explanatory variables
on the probability of the outcome. Rather,
the coefficients reflect the effect of individual
explanatory variables on its log of odds. The
positive coefficient shows that the odds ratio will
increase as the explanatory variables increases,
and conversely, the odds ratio will decrease as the
explanatory variables decreases.
METHODOLOGY
The study was conducted in Misau, Jama’are,
and Itas-Gadau Local Government Areas (LGAs)
in Northern Agricultural Zone of Bauchi State,
Nigeria. It is located between latitudes 90
31’ and
120
30’North and longitudes 80
50’ and 110
East.
The study area has two main seasonal climates
which comprise wet and dry seasons. April is
the hottest month of the year and December is
the coldest month, with temperatures averaging
22.4°C. The area received an average of
600–900 mm rainfall per year, which commences
lately on April and ends by September. In general,
the relief is between 300 and 900 m above the sea
level and the vegetation is typically of Northern
Guinea Savanna and Sudan Savannah types.[10]
It has arable land with rich, fertile soils which
is good for the cultivation of a wide variety of
food crops, including vegetables. The common
vegetable crops grown include tomatoes, onion,
cabbage, pepper, okra, fluted pumpkin, amaranths,
and garden egg.

Sampling techniques and sample size
Multistage sampling technique was used for
this study. The first stage involves a purposive
selection of three LGAs which comprise Misau,
Jama’are, and Itas-Gadau LGAs in the Zone.
The selection of the LGAs was due to the large
production of vegetables in the areas. In the second
stage, three villages were purposively selected
from each LGA. In the final stage, 60 irrigated
vegetables farmers were randomly selected in
each community comprising of Misau, Jama’are,
and Itas communities. In addition, 30 irrigated
vegetable farmers were randomly selected in each
village which comprises Zindi, DabigiSabon-
Gari, Digiza, Melen-Dige, and Gulmo villages.
This gives a total sample of 360 farmers for this
study. The list of registered vegetable farmers was
used as a sampling frame. The sample size was
determined using a model adopted by Titus et al.[11]
and Bose et al.[12]
: It is specified as follows:
2
1 ( )
=
+
irvf
N
n
N e (2)
Where
nirvf
= Sample size of the irrigated vegetable
farmers in each village
N = Total number of the registered farmers in each
village
e2
= Error term (0.052
).
Method of data collection
Primary and Secondary data were used in this
study. The primary data were collected with the
aid of structured questionnaires. The information
collected are those on vegetable production and
food security status of the farmers in the study area.
Secondary data were obtained from the Bauchi
State Agricultural Development Programme
(BSADP). It consists of the average monthly
retailed price in naira (N) per kilogram of tomato,
sweat pepper, and onion from sampled markets in
rural areas of Bauchi State. The secondary data
were for 10 years (2008–2017).
Method of data analysis
The data generated will be subjected to a statistical
tool of analysis such as descriptive and inferential
statistics (logit regression model) and farm budget
model. Descriptive statistics such as frequency,
mean, percentages, and graphs were used in
analyzing objective one and four. Farm budget
model was used in analyzing objective two. Logit
regression model was used to analyze factors
influencing food security status of the vegetable
producers (objective three). Logit model was
used to analyze the relationship between the food
security status and its determinants. The data were
analyzed using IBM SPSS 22. Explicitly, this
model is specified as follows:
Fi
=β0
+β1
X1
+β2
X2
+β3
X3
+β4
X4
+β5
X5
+β6
X6
+β7
X7
+β8
X8
+β9
X9
+μi
(3)
Where
Fi
= 1 if household head is food secure, 0 otherwise
X1
= Quantity of vegetable produced (kg)
X2
= Monthly income (₦)
X3
= Age (years)
X4
= Sex (male =1 and female = 0)
X5
= Level of education (years)
X6
= Farm size (hectares)
X7
= Farming experience (years)
X8
= Household size (number of individuals)
X9
= Membership of cooperative (member =1, 0 =
otherwise)
βo
= Vector of parameters
μi
= Random error.
Farm budgeting model
Farm budget model will be used to evaluate the
costs and benefits of vegetable production, where
total costs and returns will be estimated. The
total cost incurred during the production period
is obtained by multiplying the various input
resources by their unit market prices, while returns
(revenue) refer to the sum of outputs multiplied by
their unit price which is also known as the gross
income (GI).[13]
The model is specified as follows:
NFI=GI-TC (4)
Where
NFI = Net farm income (₦)
GI = Gross income of vegetable production
TC= Total costs (variable + fixed costs) of
vegetable production
D
−
=
P S
N (5)
Where
D = Depreciation of fixed assets
P = Price of the assets

S = Salvage value
N = Number of years (lifespan of asset)
RESULTS AND DISCUSSION
Quantity of vegetable produced
The result in Table 1 shows the average quantity of
irrigated vegetable produced in the area. The result
reveals that tomato was produced in a large quantity
of about 227 baskets (6810 kg) per hectare with an
average market price of ₦1,585.00 per basket. The
average quantity of sweat pepper and hot pepper
produced was 185 bags (7400 kg) and 145 bags
(5800 kg) per hectare with an average market price
of N2,550.00 and N3,235.00, respectively. The
quantityofonionproducedwas168bags(18480 kg)
per hectare with an average price of N4,500.00 per
bag. This implies that farmers obtained a substantial
output in the area. The market price of the products
was favorable as confirmed by the farmers during
data collection session.
Profitability analysis
The result in Table 2 reveals that the most
prominent variable cost is the labor with
constituted about 36.2%, 45.3%, and 46.2% of the
total cost for production of tomato, sweat pepper,
and onion, respectively. This implies that most of
the farmers used hired labor in irrigated vegetable
production and this type labor is expensive. This
was followed by the cost of transportation with
covered about 13.8%, 10.9% and 9.7% of the
total cost for the respective vegetables. This may
be attributed to the fact that most of the farmers
convey their produce to market individually
instead to transport their vegetables collectively.
Hence,groupmarketingmayhelptheminreducing
transportation fare. This finding is in line with
Ala and Bello[14]
who reported that labor cost and
transportation cost were prominent variable cost
in crop production. The result also shows that net
income was N187,245.00 ($520.00), N145,114.00
($403.00), and N330,761.00 ($919.00) for the
respective vegetable crops. The Return per Naira
Invested was 0.92, 0.65, and 1.03 for tomato,
sweat pepper, and onion, respectively. This
implies that a farmer acquired a return of ₦0.92,
Table 1: Average quantity of vegetable produced per
hectare
Vegetable crops quantity produced market price
Tomato1
227 baskets 1.585.00
Sweat pepper2
185 bags 2.550.00
Hot pepper3
145 bags 3,235.00
Onion4
168 bags 4,500.00
Okra5
245 baskets 1,200.00
Lettuce6
155 baskets 1,000.00
Weight: 1=30 kg/basket, 2=40 kg/bag, 3=40 kg/bag, 4=110 kg/bag, 5=20 kg/basket,
6=8 kg/basket. Currency exchange rate (2018)$1.00=N 360.0. Source: Field survey,2018
Table 2: Cost and returns of some vegetable produced (N/kg) in the study area
Variables Tomato sweat pepper onion
Amount (n) (%) TC amount (n) % TC amount (n) % TC
Seeds/seedlings 12.700 (6.3) 10.250 (4.6) 13.350 (4.2)
Fertilizer 21.550 (10.6) 23.600 (10.5) 29.800 (9.3)
Pesticides 9.640 (4.8) 13.333 (5.9) 15.500 (4.8)
Herbicides 10.520 (5.2) 10.200 (4.5) 17.600 (5.5)
Labor 73.360 (36.2) 102.133 (45.3) 147.550 (46.2)
Empty bags/baskets 27.000 (13.3) 19.500 (8.7) 36.000 (11.3)
Transportation 28.000 (13.8) 24.650 (10.9) 31.114 (9.7)
Other cost 5.750 (2.8) 6.200 (2.8) 10.700 (3.3)
Total variable cost 188.520 209.866 301.614
Depreciation of farm equipment 14.350 (7.1) 15.420 (6.8) 18.050 (5.6)
Total fixed cost 14.350 15.420 18.050
TC 202.870 225.286 319.664
Gross income (sales of produce) 390.115 370.900 650.425
Net income 187.245 145.114 330.761
RNI 0.92 0.65 1.03
Currency exchange rate (2018)$1.00 = N 360.0 Source: Field survey, 2018. RNI: Return per naira invested, TC: Total costs

₦0.65 and ₦1.03 for tomato, sweat pepper and
onion, respectively in every naira invested. Thus,
irrigated vegetable production is very profitable
and worth undertaking in the area. This finding
is in agreement with Ayodele[15]
that each rural
woman farmer on average earned $1,994.00
(N279,160.00) a year, but with the improved
yields, the income has increased to $3,376.00 (N
72,640.00) from the sale of indigenous vegetables.
Factors influencing food security status of the
irrigated vegetable farmers
Nine independent variables were included, of
which seven variables are found to be significant
determinant factors of farmers’food security status
in the study area. In line with prior expectation,
the quantity of vegetable produce was found to
be positively related with farmers food security
status and statistically significant at P = 0.001. The
positiverelationshipimpliesthatoddsratioinfavor
of being food secured increases with an increase
in the quantity of output and vice versa. Hence, as
the quantity of vegetable produced increases by
one kilogram, the odds ratio in favor of being food
secure increases by a factor of 2.030, assuming
that other factors are held constant. This results
are in line with Agbola[16]
who reported that crop
output had a significant influence on food security
status of farmers in Nigeria. In the same direction,
monthly income had positive odds ratio (2.214)
and statistically significant (P = 0.000), implying
that the odds ratio of being food secure increases
by a factor of 2.214. This could be attributed by
the fact that farmers’ monthly income obtained
from sales of vegetables and from non-agricultural
sources was used in purchasing other food items,
which in turn help them to attain food security.
Age is an important factor in determining
household food security status. The result
reveals that age was significant (P = 0.014) and
positively related with food security status of
the farmers with odds ratio of 0.943. Thus, the
positive coefficient is contrary to expectation
and this could be as a result of additional income
obtained by adults in the household. This finding
is in agreement with Oyebanjo et al.[8]
who
reported that age had a positive relationship and
significant influence on food security status of
farmers in Ogun State, Nigeria. Furthermore,
the result shows that the odds ratio of sex being
food secure increases by a factor of 0.958 if the
farmer is a male, keeping other variables constant.
It is statistically significant at P 0.05. This is
in line with the general view that male has better
physical endurance and capacity in farm activity
unlike female counterpart. This may be because
irrigated vegetable production demands higher
physical effort and takes more time, whereas
females have additional responsibilities inside
their home besides farming activities. This finding
is in conformity with Teklay et al.[17]
who observed
that odds ratio for sex was positive and significant
(P 0.05) influence on the food security status of
household.
Education was found positively significant
(P = 0.002) with odds ratio of 0.993 implying that
farmers being food secure increases by a factor of
0.993 if the farmer had acquired formal education.
Thus, education had a positive influence on food
security status. The more the educated household
head is the more food secure the household will
be and vice versa. This is because individuals who
have access to formal education are less hesitant
to adopt improved technologies and farming
practices. It also enables them to read instructions
on sprayers, fertilizer, herbicide, and pesticide
packages, among others for efficient production.
This results are in line with Abdullah et al.[1]
that education had significant (odds ratio = 0.60,
P = 0.005) influence on food security status of
household head.
In addition, farm size had positive and statistical
influence on food security of the farmers. The
odds ratio was found to be 1.141 and significant
at P = 005 as shown in Table 3. This implies that,
as farmer increases his farm by one unit, food
security status increases by a factor of 1.141 other
variables kept constant. This findings conform
to Agbola[15]
who observed that farm size had
positive significant influence of food security
status of farmers.
In respect of household size, the result reveals a
significant (P = 0.043) influence with a positive
odds ratio of 1.118. The positive relationship
implies that the odds ratio in favor of being food
secure increases with an increase in household size
and vice versa. Thus, family size increases by one
more adult, the odds ratio in favor of being food
secure increases by a factor of 1.118, assuming that
other factors are held constant.A similar result was
obtained by Teklay et al.[17]
that family size had a
significant (odds ratio = 2.304, P = 0.000) influence
on food security status of household. Other
explanatory variables that influence food security

status of the farmers are farming experience and
membership of cooperative societies, though they
are insignificant, implying that increase in the
odds ratio of these variables increases the food
security of the irrigated vegetable farmers in the
study area.
The log-likelihood ratio test robustly rejects
the hypothesis that all slope coefficients are
simultaneously equal to zero, and thus, the model
correctly predicted the observations as shown
in Table 3. The overall predictive power of the
model reveals that the independent variables had
a significant impact in explaining the food security
status of the farmers as justifying by the value of
pseudo R2
of 0.481. This implies that about 48%
of variation in the dependent variable is explained
by independent factors included in the model. Chi-
square test was found to be 96.85 with a degree of
freedomof8andstatisticallysignificantatP=0.001.
Price trend analysis of tomato, sweat pepper,
and onion
The results on rural price trend are presented in
Figures 1-3 for tomato, sweat pepper, and onion,
respectively. The seasons of the year were divided
into four seasons as adopted by BSADP[18]
and Bose
et al.,[12]
namely early dry (November–January),
late dry (February–April), early rainy (May–July),
and late rainy seasons (August–October).As shown
in Figure 1, in all the seasons, the prices of tomato
vary between the seasons of the year throughout the
period of the study, where increase and decrease in
pricewereobserved.Thehighestpricewasrecorded
in the early rainy season, especially in year 2016.
This is not surprising because, in 2016, there were
high prices of food commodities in Nigeria due to
low supply. The lowest price was observed in 2008
in all the seasons. Seasonal variations occur in
tomato prices, for several reasons such as demand
and supply factors. In most of the time, at the early
rainy season, the tomato products were scarce
because at that time irrigated tomato was very
scarce in the market and that of the rainy season was
yet to be available. Thus, low supply was observed
which in turn leads to high prices. This finding is
in line with Mani et al.[4]
who reported that high
price variation of fresh tomato in the market is
common, especially between harvest and lean
periods. Similarly, the result is in agreement with
Table 3: Binary logistic results on factors influencing food security status of vegetable farmers
Variable Coefficient SE Odds ratio Wald (Z) P value
Constant −1.674 1.407 0.188 1.414 0.006
Quantity of vegetable produced (kg) (X1) 1.026 0.103 2.030* 0.102 0.001
Monthly income (N) (X2) 2.130 0.410 2.214*** 1.004 0.000
Age (Years) (X3) 1.580 0.040 0.943* 2.140 0.014
Sex (male=1 and female=0) (X4) 0.346 0.117 0.958* 1.003 0.031
Level of education (years) (X5) 0.007 0.037 0.993** 0.033 0.002
Farm size (hectares) (X6) 0.132 0.235 1.141** 0.317 0.005
Farming experience (years) (X7) 0.042 0.047 1.043NS
0.811 0.231
Household size (number of individuals) (X8) 0.112 0.055 1.118* 4.077 0.043
Membership of cooperative (member=1 and 0 = otherwise) (X9) −0.524 0.731 0.592NS
0.514 0.473
Pseudo R2
=0.481 χ2
=97.38 (8), P0.001
***Implies P0.001, ** implies P 0.01, * implies P0.05, NS implies not significant. Source: Field Survey, 2018
Figure 1: Rural price trend of tomato (N/kg) in Bauchi
State
Figure 2: Rural price trend of sweat pepper (N/kg) from
2008 to 2017 in Bauchi State

the findings of Akpan et al.[19]
who ascertain that
marketing of fresh tomato and pineapple in Akwa
Ibom State is generally not promising in terms of
better prices at the rural levels. However, a general
rising pattern of prices was observed throughout
the seasons.
In Figure 2, the results reveal that the price of
sweat pepper had a similar trend with that of
tomato where price fluctuated in all the seasons.
The highest prices were recorded in an early rainy
season. This was not surprising because at that
period there was a high demand of vegetables
for household consumption, especially during
festivities. In early dry and late rainy seasons
also, exorbitant prices were recorded in 2013 and
2016, respectively. This also may be attributed
to high demand of the product at those periods.
In general, prices move closely range with some
kind of interwoven movement in increasing
and decreasing within the seasons of the years
(between the harvest and the lean periods). Hence,
price fluctuates throughout the seasons.
In Figure 3, the highest price of onion was recorded
in early dry season in 2016 and lowest price was
recorded in late rainy season 2008. Moreover,
exorbitant price was recorded in late dry season
in 2014 and 2015. In addition to this, high price of
onion was observed in late rainy season in 2016.
It can be noted that the prices were increasing and
decreasing within all the seasons over the years.
The seasonal pattern was as the result of storage
needed to bridge a discontinuous flow of supply
with a continuous demand for the commodity over
an annual cycle. Thus, seasonal price variation is
common in all the vegetable crops under review
in the study area. It could be noted that there are
price swings in production and marketing periods
of fresh vegetables and that changes in price in the
market were influenced by time variable.
CONCLUSION AND
RECOMMENDATIONS
Based on the findings of this study, it can be
concluded that farmers obtained a substantial
output of about 227 baskets (6810 kg) of tomato,
185 bags (7400 kg) of sweat pepper, and 168 bags
(18480 kg) of onion per hectare. The net incomes
were N187,245.00 ($520.00), N145,114.00
($403.00), and N330,761.00 ($919.00) per hectare
for tomato, sweat pepper, and onion, respectively.
This indicates that vegetable production is very
profitable and worth undertaking in the area.
Seasonal price variation is common in all the
vegetable crops under the study in the area. The
pseudo R2
recorded was 0.481, implying that about
48% of variation in the dependent variable was
explained by independent factors that influence the
food security status of the farmers. The significant
independent variables influencing food security
status of the vegetable farmers were quantity of
vegetable produced, monthly income, age, sex,
education, and household size in the study area.
To minimize the problem of price fluctuations
at all levels of vegetable marketing, the study
recommends that farmers should be provided with
adequate information concerning prices, supply,
and demand, especially at the local level. This will
enable farmers to assess alternative opportunities
of marketing their crops and thereby minimize
the problem of low prices caused by seasonal
glut in the area. The study further recommends
that since the quantity of vegetable produced has
high influence on food security, farmers should be
encouraged to adopt improved technologies and
new farming practices to boast output. Similarly,
monthly income has significant influence on food
security; therefore, farmers should be encouraged
to diversify source of income to purchase other
foodstuffs that they could not producing in their
farms.
ACKNOWLEDGMENT
The author would like to express the profound
gratitude to Tertiary Education Trust Fund
(TETFund)forsponsoringthisresearchworkunder
Institution Based Research (IBR). In addition, the
author would like to appreciate the Management
of Abubakar Tafawa Balewa University, Bauchi,
Nigeria, for giving me the opportunity to conduct
this research project.
Figure 3: Rural price trend of onion (N/kg) from 2008 to
2017 in Bauchi State

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