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Available Online at www.aextj.com
Agricultural Extension Journal 2018; 2(3):176-183
ISSN 2521 ā€“ 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 (6810Ā kg), 185 bags (7400Ā kg), and 168 bags (18480Ā 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.,Ā 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 5ā€“10Ā 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, 0.25ā€“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
ļ¢ ļ¢ ļ¢ ļ¢ ļ­
ļ£® ļ£¹
=+ + + +ļ£Æ ļ£ŗ
ļ£° ļ£»
i
i i i i i
i
P
Ln o X X n Xn
P (1)
This [Pi
/(1ā€“Pi
)] is simply the odds ratio in favor of
food security (Fi
), i.e.,Ā the ratio of the probability
that the farmer is food secure to the probability
that it is not food secure. The subscript ā€œiā€ shows
the ith
observation in the data. Ī²o is the intercept
of the model, while X1, X2, X3 ā€¦ 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, Jamaā€™are,
and Itas-Gadau Local Government Areas (LGAs)
in Northern Agricultural Zone of Bauchi State,
Nigeria. It is located between latitudes 90
31ā€™ and
120
Ā 30ā€™North and longitudes 80
Ā 50ā€™ 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
22.4Ā°C. The area received an average of
600ā€“900Ā mm rainfall per year, which commences
lately on April and ends by September. In general,
the relief is between 300 and 900Ā 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.
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 3 178
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,
Jamaā€™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, Jamaā€™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 etĀ 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 10Ā years (2008ā€“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
=Ī²0
+Ī²1
X1
+Ī²2
X2
+Ī²3
X3
+Ī²4
X4
+Ī²5
X5
+Ī²6
X6
+Ī²7
X7
+Ī²8
X8
+Ī²9
X9
+Ī¼i
(3)
Where
Fi
= 1 if household head is food secure, 0 otherwise
X1
= Quantity of vegetable produced (kg)
X2
= Monthly income (ā‚¦)
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)
Ī²o
= Vector of parameters
Ī¼i
= 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 (ā‚¦)
GI = Gross income of vegetable production
TC= Total costs (variable + fixed costs) of
vegetable production
D
āˆ’
=
P S
N  (5)
Where
D = Depreciation of fixed assets
P = Price of the assets
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 3 179
S = Salvage value
N = Number of years (lifespan of asset)
RESULTS AND DISCUSSION
Quantity of vegetable produced
The result in TableĀ 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 (6810Ā kg) per hectare with an
average market price of ā‚¦1,585.00 per basket. The
average quantity of sweat pepper and hot pepper
produced was 185 bags (7400Ā kg) and 145 bags
(5800Ā kg) per hectare with an average market price
of N2,550.00 and N3,235.00, respectively. The
quantityofonionproducedwas168bags(18480Ā 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 TableĀ 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 ā‚¦0.92,
TableĀ 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 rateĀ (2018)$1.00=N 360.0. Source:Ā Field survey,2018
TableĀ 2: Cost and returns of some vegetable producedĀ (N/kg) in the study area
Variables Tomato sweat pepper onion
AmountĀ (n)Ā (%) TC amountĀ (n) % TC amountĀ (n) % TC
Seeds/seedlings 12.700Ā (6.3) 10.250Ā (4.6) 13.350Ā (4.2)
Fertilizer 21.550Ā (10.6) 23.600Ā (10.5) 29.800Ā (9.3)
Pesticides 9.640Ā (4.8) 13.333Ā (5.9) 15.500Ā (4.8)
Herbicides 10.520Ā (5.2) 10.200Ā (4.5) 17.600Ā (5.5)
Labor 73.360Ā (36.2) 102.133Ā (45.3) 147.550Ā (46.2)
Empty bags/baskets 27.000Ā (13.3) 19.500Ā (8.7) 36.000Ā (11.3)
Transportation 28.000Ā (13.8) 24.650Ā (10.9) 31.114Ā (9.7)
Other cost 5.750Ā (2.8) 6.200Ā (2.8) 10.700Ā (3.3)
Total variable cost 188.520 209.866 301.614
Depreciation of farm equipment 14.350Ā (7.1) 15.420Ā (6.8) 18.050Ā (5.6)
Total fixed cost 14.350 15.420 18.050
TC 202.870 225.286 319.664
Gross incomeĀ (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 rateĀ (2018)$1.00Ā =Ā N 360.0 Source: Field survey, 2018. RNI: Return per naira invested, TC: Total costs
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 3 180
ā‚¦0.65 and ā‚¦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 farmersā€™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 farmersā€™ 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 TableĀ 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.AĀ 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
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 3 181
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 TableĀ 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
FiguresĀ 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 (Novemberā€“January),
late dry (Februaryā€“April), early rainy (Mayā€“July),
and late rainy seasons (Augustā€“October).As shown
in FigureĀ 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
TableĀ 3: Binary logistic results on factors influencing food security status of vegetable farmers
Variable Coefficient SE Odds ratio WaldĀ (Z) P value
Constant āˆ’1.674 1.407 0.188 1.414 0.006
Quantity of vegetable producedĀ (kg)Ā (X1) 1.026 0.103 2.030* 0.102 0.001
Monthly incomeĀ (N)Ā (X2) 2.130 0.410 2.214*** 1.004 0.000
AgeĀ (Years)Ā (X3) 1.580 0.040 0.943* 2.140 0.014
SexĀ (male=1 and female=0)Ā (X4) 0.346 0.117 0.958* 1.003 0.031
Level of educationĀ (years)Ā (X5) 0.007 0.037 0.993** 0.033 0.002
Farm sizeĀ (hectares)Ā (X6) 0.132 0.235 1.141** 0.317 0.005
Farming experienceĀ (years)Ā (X7) 0.042 0.047 1.043NS
0.811 0.231
Household sizeĀ (number of individuals)Ā (X8) 0.112 0.055 1.118* 4.077 0.043
Membership of cooperativeĀ (member=1 and 0Ā =Ā otherwise)Ā (X9) āˆ’0.524 0.731 0.592NS
0.514 0.473
Pseudo R2
=0.481 Ļ‡2
=97.38Ā (8), P0.001
***Implies P0.001, ** implies PĀ 0.01, * implies P0.05, NS implies not significant. Source: Field Survey, 2018
FigureĀ 1: Rural price trend of tomato (N/kg) in Bauchi
State
FigureĀ 2: Rural price trend of sweat pepper (N/kg) from
2008 to 2017 in Bauchi State
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 3 182
the findings of Akpan etĀ 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 FigureĀ 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 FigureĀ 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 (6810Ā kg) of tomato,
185 bags (7400Ā kg) of sweat pepper, and 168 bags
(18480Ā 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
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 3 183
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Determinants of Food Security Status among Irrigated Vegetable Farmers in Northern Agricultural Zone of Bauchi State, Nigeria

  • 1. Ā© 2018, AEXTJ. All Rights Reserved 176 Available Online at www.aextj.com Agricultural Extension Journal 2018; 2(3):176-183 ISSN 2521 ā€“ 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 (6810Ā kg), 185 bags (7400Ā kg), and 168 bags (18480Ā 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.,Ā 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
  • 2. 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 5ā€“10Ā 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, 0.25ā€“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 ļ¢ ļ¢ ļ¢ ļ¢ ļ­ ļ£® ļ£¹ =+ + + +ļ£Æ ļ£ŗ ļ£° ļ£» i i i i i i i P Ln o X X n Xn P (1) This [Pi /(1ā€“Pi )] is simply the odds ratio in favor of food security (Fi ), i.e.,Ā the ratio of the probability that the farmer is food secure to the probability that it is not food secure. The subscript ā€œiā€ shows the ith observation in the data. Ī²o is the intercept of the model, while X1, X2, X3 ā€¦ 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, Jamaā€™are, and Itas-Gadau Local Government Areas (LGAs) in Northern Agricultural Zone of Bauchi State, Nigeria. It is located between latitudes 90 31ā€™ and 120 Ā 30ā€™North and longitudes 80 Ā 50ā€™ 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 22.4Ā°C. The area received an average of 600ā€“900Ā mm rainfall per year, which commences lately on April and ends by September. In general, the relief is between 300 and 900Ā 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.
  • 3. 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 3 178 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, Jamaā€™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, Jamaā€™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 etĀ 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 10Ā years (2008ā€“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 =Ī²0 +Ī²1 X1 +Ī²2 X2 +Ī²3 X3 +Ī²4 X4 +Ī²5 X5 +Ī²6 X6 +Ī²7 X7 +Ī²8 X8 +Ī²9 X9 +Ī¼i (3) Where Fi = 1 if household head is food secure, 0 otherwise X1 = Quantity of vegetable produced (kg) X2 = Monthly income (ā‚¦) 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) Ī²o = Vector of parameters Ī¼i = 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 (ā‚¦) GI = Gross income of vegetable production TC= Total costs (variable + fixed costs) of vegetable production D āˆ’ = P S N (5) Where D = Depreciation of fixed assets P = Price of the assets
  • 4. 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 3 179 S = Salvage value N = Number of years (lifespan of asset) RESULTS AND DISCUSSION Quantity of vegetable produced The result in TableĀ 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 (6810Ā kg) per hectare with an average market price of ā‚¦1,585.00 per basket. The average quantity of sweat pepper and hot pepper produced was 185 bags (7400Ā kg) and 145 bags (5800Ā kg) per hectare with an average market price of N2,550.00 and N3,235.00, respectively. The quantityofonionproducedwas168bags(18480Ā 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 TableĀ 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 ā‚¦0.92, TableĀ 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 rateĀ (2018)$1.00=N 360.0. Source:Ā Field survey,2018 TableĀ 2: Cost and returns of some vegetable producedĀ (N/kg) in the study area Variables Tomato sweat pepper onion AmountĀ (n)Ā (%) TC amountĀ (n) % TC amountĀ (n) % TC Seeds/seedlings 12.700Ā (6.3) 10.250Ā (4.6) 13.350Ā (4.2) Fertilizer 21.550Ā (10.6) 23.600Ā (10.5) 29.800Ā (9.3) Pesticides 9.640Ā (4.8) 13.333Ā (5.9) 15.500Ā (4.8) Herbicides 10.520Ā (5.2) 10.200Ā (4.5) 17.600Ā (5.5) Labor 73.360Ā (36.2) 102.133Ā (45.3) 147.550Ā (46.2) Empty bags/baskets 27.000Ā (13.3) 19.500Ā (8.7) 36.000Ā (11.3) Transportation 28.000Ā (13.8) 24.650Ā (10.9) 31.114Ā (9.7) Other cost 5.750Ā (2.8) 6.200Ā (2.8) 10.700Ā (3.3) Total variable cost 188.520 209.866 301.614 Depreciation of farm equipment 14.350Ā (7.1) 15.420Ā (6.8) 18.050Ā (5.6) Total fixed cost 14.350 15.420 18.050 TC 202.870 225.286 319.664 Gross incomeĀ (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 rateĀ (2018)$1.00Ā =Ā N 360.0 Source: Field survey, 2018. RNI: Return per naira invested, TC: Total costs
  • 5. 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 3 180 ā‚¦0.65 and ā‚¦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 farmersā€™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 farmersā€™ 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 TableĀ 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.AĀ 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
  • 6. 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 3 181 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 TableĀ 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 FiguresĀ 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 (Novemberā€“January), late dry (Februaryā€“April), early rainy (Mayā€“July), and late rainy seasons (Augustā€“October).As shown in FigureĀ 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 TableĀ 3: Binary logistic results on factors influencing food security status of vegetable farmers Variable Coefficient SE Odds ratio WaldĀ (Z) P value Constant āˆ’1.674 1.407 0.188 1.414 0.006 Quantity of vegetable producedĀ (kg)Ā (X1) 1.026 0.103 2.030* 0.102 0.001 Monthly incomeĀ (N)Ā (X2) 2.130 0.410 2.214*** 1.004 0.000 AgeĀ (Years)Ā (X3) 1.580 0.040 0.943* 2.140 0.014 SexĀ (male=1 and female=0)Ā (X4) 0.346 0.117 0.958* 1.003 0.031 Level of educationĀ (years)Ā (X5) 0.007 0.037 0.993** 0.033 0.002 Farm sizeĀ (hectares)Ā (X6) 0.132 0.235 1.141** 0.317 0.005 Farming experienceĀ (years)Ā (X7) 0.042 0.047 1.043NS 0.811 0.231 Household sizeĀ (number of individuals)Ā (X8) 0.112 0.055 1.118* 4.077 0.043 Membership of cooperativeĀ (member=1 and 0Ā =Ā otherwise)Ā (X9) āˆ’0.524 0.731 0.592NS 0.514 0.473 Pseudo R2 =0.481 Ļ‡2 =97.38Ā (8), P0.001 ***Implies P0.001, ** implies PĀ 0.01, * implies P0.05, NS implies not significant. Source: Field Survey, 2018 FigureĀ 1: Rural price trend of tomato (N/kg) in Bauchi State FigureĀ 2: Rural price trend of sweat pepper (N/kg) from 2008 to 2017 in Bauchi State
  • 7. 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 3 182 the findings of Akpan etĀ 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 FigureĀ 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 FigureĀ 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 (6810Ā kg) of tomato, 185 bags (7400Ā kg) of sweat pepper, and 168 bags (18480Ā 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
  • 8. 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 3 183 REFERENCES 1. Abdullah DZ, Tariq S, Sajjad A, Waqar A, Izhar U, Aasir I. Factors affecting household food security in rural northern hinterland of Pakistan. JĀ Saudi Soc Agric Sci 2017;301-10. Available from: http://www.ac.els- cdn.com/S1658077X16301709. [Last accessed on 2018Ā AprĀ 10]. 2. Food and Agriculture Organization. Food Insecurity Indicators. Food and Agriculture Organization; 2014. Available from: http://www.fao.org/economic/ess/ess- fs/fsdata. [Last accessed on 2018Ā JunĀ 17]. 3. Hassan A, Ahmad ME, Adewumi MO, Falola A. Irrigation and income poverty reduction: An assessment study of river basin development authorityā€™s irrigation scheme in dadinkowa, Gombe State, Nigeria. Dutse J Agric Food Secur 2017;4:56-64. 4. Mani JR, Hudu MI, Ali A. Price Variation of Tomatoes and Ginger in Giwa Market, Kaduna State, Nigeria; 2018. Available from: https://www.dx.doi.org/10.4314/ jae.v22i1.9. [Last accessed on 2018Ā AugĀ 05]. 5. Busari AO, Idris-Adeniyi KM, Oyekale JO. Economic analysis of vegetable production by rural women in iwo zone of Osun State, Nigeria. Green J Agric Sci 2012;3:6-11. 6. Echeme II, Nwachukwu CC. An investigation on the impact of Fadama II project implementation in Imo State. Am J Sci Ind Res 2010;1:532-8. 7. Arene CJ, Anyaeji C. Determinants of food security among households in Nsukka metropolis of Enugu state, Nigeria. Pak J Soc Sci 2010;30:9-16. 8. Oyebanjo O, Ambali OI, Akerele EO. Determinants of food security status and incidence of food insecurity among rural farming households in Ijebu division of OgunState, Nigeria. JĀ Agric Sci Environ 2013;2:351-7. Available from: http://www.journal.unaab.edu.ng/ index.php/JAgSE/article/view/1214/1110. [Last accessed on Mar 25]. 9. Coleman-Jensen A, Nord M, Andrews M, Carlson S. Statistical Supplement to Household Food Security in the United States in 2010: AP-057. USDA, Economic Research Service; 2011.Available from: http://www.ers. usda.gov/publications/ap-administrative-publication/ ap-057.aspx. [Last accessed on 2018Ā JulĀ 22]. 10. Bauchi State Information. Bauchi State of Nigeria. Nigeria Galleria; 2016. Available from: http://www. Nigeria galleria. com/Nigeria/States_Nigeria/Bauchi_ State.html. [Last accessed on 2018Ā JulĀ 20]. 11. Titus OG, Olise MC, Eze GA. Research Methods in Business Management Sciences. Nigeria: Iyke Ventures Production Enugu; 2008. p.Ā 258. 12. Bose AA, Mohammed I, Haruna U. Price Trends and determinants of market supply in cross-border cattle trade between Nigeria and Niger republic. Dutse J Agric Food Secur 2016;3:13-24. 13. Olukosi JO, Erhabor PO. Introduction to Farm management Economics, Principles and Application. Nigeria: Agitab Publishers Zaria; 2005. p.Ā 114. 14. Ala L, Bello FA. Reducing the incidence household food insecurity via crop production among farmers in Patigi local government area, Kwara state. Niger J Farm Manag 2011;12:23-9. 15. Ayodele V, Makaleka MB, Chaminuka P, NchabelengĀ LM. Potential Role of Indigenous Vegetable Production in Household Food Security: AĀ Case Study in Limpopo Province of South Africa; 2011. http://www.actahort. org/members/showpdf? Book nrarn r=911_52. [Last accessed on 2018Ā AugĀ 17]. 16. Agbola PO. Factors influencing food insecurity among smallscalefarmersinNigeria.AfrJAgricRes2014;9:1-7. Available from: http://www.academicjournals.org/ AJAR. [Last accessed on 2018Ā AugĀ 20]. 17. Teklay N, Aynalem S, Nega AR. Determinants and coping strategies of household food insecurity evidence from agro pastoralists ofAfar Region (Zone Two)Addis Ababa. JĀ Poverty Invest Dev 2015;12:1-11. 18. BSADP. Report for the Monthly Technology Review Meeting for the Month of November, 2012. Bauchi State, Nigeria: Bauchi State Agricultural Development Programme; 2012. 19. Akpan SB, Patrick IV, Edet GE, John DE. Analysis of price transmission of fresh tomato and pineapple in the rural and urban markets of AkwaIbom sate, Nigeria. Am J Agric For 2014;2:66-78.