Analysis of Resource Use Efficiency in Tomato (Solanum lycopersicum) Production in Kogi State, Nigeria

Full text

_____________________________________________________________________________________________________
*Corresponding author: E-mail: drsjibitoye@yahoo.com;
Asian Journal of Agricultural Extension,
Economics & Sociology
6(4): 220-229, 2015; Article no.AJAEES.2015.080
ISSN: 2320-7027
SCIENCEDOMAIN international
www.sciencedomain.org
Analysis of Resource Use Efficiency in Tomato
(Solanum lycopersicum) Production in Kogi State,
Nigeria
S. J. Ibitoye
1*
, U. M. Shaibu
1
and B. Omole
1
1
Department of Agricultural Economics and Extension, Kogi State University, Anyigba, Nigeria.
Authors’ contributions
This work was carried out in collaboration between all authors. Author SJI design the study, wrote the
proposal, performed the data analyses and wrote the first and final draft of the manuscript. Authors
UMS and BO managed the literature searches and participated in data collection and processing.
All authors read and approved the final manuscript.
Article Information
DOI: 10.9734/AJAEES/2015/18112
Editor(s):
(1)
Jamal Alrusheidat, Assistant and Consultant to Director General for Extension Education, Director of Extension Education
Department, National Centre for Agricultural Research and Extension (NCARE), Amman, Jordan.
Reviewers:
(1)
Anonymous, Graduate School of Yamagata University, Japan.
(2)
Guillermo R. Pratta, Department of Biology, National University of Rosario, Argentina.
(3)
HAB. TAKÁCS-GYÖRGY Katalin, Károly Róbert College, Hungary.
Complete Peer review History:
http://www.sciencedomain.org/review-history.php?iid=1060&id=25&aid=9398
Received 4
th
April 2015
Accepted 24
th
April 2015
Published 25
th
May 2015
ABSTRACT
The study was on resource use efficiency among tomato farmers in Kogi State, Nigeria. The data
were collected from 240 tomato farmers through purposive sampling in 2014. Questionnaire design
was the instrument used for data collection. Data collected were analysed through the use of simple
descriptive statistics, OLS regression analysis and efficiency ratio. The result of the study showed
that majority of tomato farmers in the State were married males with an average family size of 7
members. Farmers’ educational status, farming experience, contact with extension workers, and
farm size were positively related and significant at 1% in influencing the output of tomato produced
in the State. Resources such as pesticide, labour, years spent in school, quantity of seed and farm
size were positively and significantly related to tomato output in Kogi State. Quantity of pesticide,
seed and fertilizer were over utilized while labour and farm size were underutilized. It is
recommended that government should implement policies that will facilitate the efficient utilization of
agricultural resources among tomato farmers in Kogi State.
Original Research Article

Ibitoye et al.; AJAEES, 6(4): 220-229, 2015; Article no.AJAEES.2015.080
221
Keywords: Tomato; farmers; resources; efficiency; production.
1. INTRODUCTION
Tomato (Solanum lycopersicum) is one of the
most popular and widely grown fruit in the world
including Africa [1,2]. It is native to South
America [3], but was introduced into West Africa
by Portuguese traders and freed slaves from
West Indies [4]. It is the second most important
vegetable worldwide, in terms of the amount of
vitamins and minerals it contributes to the diet
[5]. Genetic evidence shows that the progenitors
of tomatoes were herbaceous green plants with
small green fruit and a centre of diversity in the
high lands of Peru [6]. Tomato is the edible, often
red fruit/berry of the Nightshade (Solanum
lycopersicum) commonly known as a tomato
plant.
According to a press release by the Central Bank
of Nigeria in 2013 [7], an annual total area of one
million hectares is reportedly used for tomato
cultivation in Nigeria while it makes up about 18
percent of the average daily consumption of
vegetables in homes. Nigeria is ranked second
largest producer of tomato in Africa and
fourteenth largest in the world, producing 1.51
million metric tonnes of tomato annually valued
at N87 billion at an average of 25-30 tonnes per
hectare under rainfed production, Central Bank
of Nigeria [7].
Tomato is grown and eaten all over the world. It
is used in diverse ways, including raw in salads,
and processed into tomato soup. Unripe green
tomatoes can also be breaded and fried. Tomato
juice is sold as a drink. The fruit is preserved by
drying, often in the sun, and sold either in bags,
baskets or in jars with oil. Tomato is rich in
vitamins [8], minerals and lycopene, an excellent
antioxidant [2] that helps to reduce the risk of
prostate and breast cancer [9].
Tomato production requires a high level of
management, large labour and capital inputs and
close attention to detail. Tomato production is
subject to the variations that occur in weather,
which may result in severe crop damage and
losses [10]. Labour requirements for production,
harvesting, grading, packaging and transporting
are very intense. Erdogan [11] confirms that
tomato production is labour intensive and bulk of
production is mostly supported by small family
farm.
Major tomato producers in Kogi State are small
scale farmers who could hardly produce enough
to meet the demand of consumers. Tomato
produced in the State is done mostly during the
dry season, that is, October to May. The period
between July to September is severe tomato
scarce period because of high incidence of pests
and disease associated with growing tomato;
general crop management and shifting of tomato
producers to production of grain crops [12].
These critical supply elements drive high
demand for fresh tomatoes, causes inflation of
fresh tomato price, opens market for unhygienic
sun-dried tomato as well as clearance for
imported fresh tomatoes from neighbouring
States.
The failure of tomato farms to meet demand in
Kogi State has raised concern over the ability of
these farms to increase tomato output. In view of
the growing demand for tomato in Kogi State,
improving the efficiency of resource use would
be the key to increased tomato production in the
State. Thus, for the State to thrive in tomato
production, it needs to achieve a high level of
efficiency which is essential for competitiveness
and profitability. It is against this background that
this study intends to carry out the technical
efficiency of resource use among tomato farmers
as well as the factors influencing the output of
tomato in Kogi State, Nigeria.
2. MATERIALS AND METHODS
This study was carried out in Kogi State, Nigeria
which is located in the central region of Nigeria. It
is popularly called the Confluence State due to
the fact that the confluence of River Niger and
River Benue is at it’s headquarter in Lokoja.
Lokoja, the State headquarter is the first
administrative capital of modern day-Nigeria. The
State lies between latitude 6
0
30
’
N and 8
0
48
’
N
and
longitude 5
0
23
’
E and 7
0
48
’
E. Kogi State has a
population of about 3,278,487 people [13]. The
State has land area of about 30,354.74 square
kilometers. Out of this total area, the State has 2
Million hectares of cultivable land but only about
0.5 Million hectares are under cultivation, (Kogi
State Economic Empowerment and Development
Strategy (KOSEEDS), [14]).
A purposive sampling technique was used to
select eight Local Government Areas (LGAs)
from the four agricultural zones. The eight LGAs
selected were: Kabba-Bunu, Ijumu, Bassa,

Ibitoye et al.; AJAEES, 6(4): 220-229, 2015; Article no.AJAEES.2015.080
222
Omala, Ankpa, Lokoja, Ajaokuta and Olamaboro.
These LGAs were purposively selected based on
their level of involvement in tomato production.
The survey was carried out in 2014. Two
communities from each of the LGAs were
randomly selected to give a total of sixteen
communities used for the study. Fifteen tomato
farmers were randomly selected from each of the
sixteen communities to give a total of 240
respondents used for the study. Structured
questionnaire was administered to the selected
tomato farmers from the selected communities.
The study used descriptive statistics, multiple
regression analysis and efficiency ratio to
analyse the data. The Multiple Regression and
Efficiency Ratio models were specified as
follows:
2.1 Multiple Regression Analysis
For this study, three functional forms were tested
on the primary data collected, but the Cobb-
Douglas function was chosen based on the R
2
,
value of the estimated coefficients, number of
significant variables and conformity with the a
priori expectation. The Cobb-Douglas production
function investigated in this study is expressed
mathematically as;
Y=f (X
s
)
Y=f (X
1,
X
2,
X
3,
X
4,
X
5,
X
6,
X
7,
e
i
)
LnY=b
0
+b
1
LnX
1
+b
2
LnX
2
+b
3
LnX
3
+b
4
LnX
4
+b
5
L
nX
5
+b
6
LnX
6
+b
7
LnX
7
+e
i
Where:
Y= Output (kg), β
0
= Intercept (kg), β= Marginal
effect of X
S
on Y, X
1
= Sex (1 = Females, 0 =
Males), X
2
= Age of Respondents (years), X
3=
Farming experience (years), X
4
= Educational
status (years), X
5
= Household size (number), X
6
=
Access to extension (Number of contacts), X
7
=
Farm size (hectares) and e
i
= Error term.
It is expected that the value of each of the
variables, that is, b
1
– b
7
will be positively related
to the output of tomato in the area. By
implication, the higher the quantity of these
variables, the higher the output of tomato.
2.2 Efficiency Ratio
Efficiency ratio was used to determine the
efficiency of resources used in tomato
production. The estimated coefficients of the
relevant independent variables were used to
compute the Marginal Value Products (MVP) and
their corresponding Marginal Factor Costs
(MFC). The equation is
r = MVP
MFC
Where r = efficiency ratio
MVP = Marginal Value Product of variable input
MFC = Marginal Factor Cost
The value of MVP was computed using the
regression coefficient of each input and the price
of the output was expressed as stated below:
MVP
x
= b
i
× P
y
Where
P
y
= price per unit of output
b
i
= regression coefficient of input i (i = 1, 2, .....n)
MVP
xi
= Marginal Value Product of input
xi
The prevailing market price of inputs was used
as the Marginal Factor Cost (MFC) [15].
The values of the ratios are interpreted thus:
i. If r < 1, means that the resource in
question was over-utilized-therefore, if the
quantity of such input is increased, profit
will increase.
ii. If r > 1, means that the resource was
under-utilized. If the quantity of such input
is decreased, profit will increase.
iii. If r = 1, it means that the resource was
being efficiently utilized.
3. RESULTS AND DISCUSSION
3.1 Socio-Economic Characteristics of
Tomato Farmers in Kogi State
The distribution of respondents according to age
revealed that majority (82.5%) were in the age
range of 41-60 years. 9.6% of the respondents
were above 60 years of age while 7.9% were
within the age range of 21-40 years (Table 1).
The mean age was 51 years. This implies
increased productivity and technical efficiency
among tomato farmers in the area since majority
of the farmers are still in their active and
productive age. This agrees with the findings of
[16] who found that tomato production was
dominated by adults who were between the age
range of 40-60 years of age and attributed it to
labour requirement in tomato production.
Majority (72.1%) of the respondents were male
while 27.9% were female. This implies that
tomato production in the study area was

Ibitoye et al.; AJAEES, 6(4): 220-229, 2015; Article no.AJAEES.2015.080
223
dominated by men. 27.9% involvement of
females in tomato production indicated that
women were also in the business but to a smaller
extent. This is in line with studies by [16] and [17]
who reported that males dominated tomato
production in Adamawa and Niger States
respectively.
Distribution of respondents according to marital
status revealed that majority (76.7%) of the
respondents was married, 11.7% were single,
7.1% were widowed, and 4.6% of the
respondents were divorced. This implies that
apart from been a major source of income to the
family, majority of the tomato farmers produce
tomato most likely to cater for their family needs.
The table further revealed that half (50%) of the
respondents had no formal education. 28.3% of
the respondents attended primary school. 15.4%
attended secondary school at both junior and
senior secondary level, while 6.3% of the
respondents attended tertiary institutions. This
implies that about half (50%) of the sampled
farmers do not know how to read and write while
another 50% can read and write. The low level of
education of the farmers could affect their
adoption of appropriate technology. This agrees
with the findings of [18] and [19] who reported
relatively high level of illiteracy among small
scale farmers in Rivers and Ogun States
respectively.
Result on major occupation of the respondents
showed that most (61.7%) of the tomato farmers
were into full-time farming on an average farm
size of 1.3 hectares. 19.5% combined civil
service work with tomato production, while 11.7%
and 7.1% of the respondents combined tomato
production with artisan and trading respectively.
This implies that the agricultural sector serves as
source of employment and income to many
households in the area. This finding is consistent
with [20] who posited that the agricultural sector
of Nigeria economy contributes significantly to
rural employment, food security, provision of
industrial and raw materials.
About 73.3% of the respondents had above 30
years of tomato farming experience. 13.8% had
21-30 years of experience, 8.7% had 1-10 years
of tomato farming experience, while 4.2% of the
sampled respondents had between 11-20 years
of farming experience. The average farming
experience was 37 years. The high level of
experience among tomato farmers in the area
may increase their level of efficiency, because
the more experienced a farmer is, the more
efficient he is supposed to become and vice
versa. The finding supports the findings of [21],
who reported a positive and significant
relationship between farming experience and
technical efficiency among Fadama farmers in
Adamawa State.
About 95.8% of tomato farmers in the area
cultivated tomato on an area of 3 hectares and
below. Only 4.2% of the respondents had a farm
land of above 3 hectares for tomato production.
The mean farm size was 1.5 hectares. This
implies that tomato production in the study area
is still at the subsistence level. The small area of
farm land may also be attributed to the
perishable nature of tomato. This confirms the
result of separate studies carried out by [22] and
[23] who reported that the average number of
hectares cultivated per farmer was found to be
about 1.5 hectares.
Household size of most respondents ranged from
7-12 members (37.5 percent), above 12
members (32.5 percent) and to those with less
than 6 members (30 percent). The mean
household size was about 7 members per
household. It is expected that members of the
household will serve as source of labour on the
farm. The range of household size is lower when
compared with what is obtainable in the Northern
part of the country, which recorded an average
size of 13 members per household [24]. The
average household size of 7 is the same with the
national average of 7 and slightly lower than the
findings of [25] who found a higher level of labour
availability with an average of 8 members per
household. Orebiyi et al. [26] have also reported
that large family size may mean more family
expenses and fewer funds for agricultural
activities. The mean household size also could
characterize moderate dependency ratio in
Nigeria (Udo, 1999 in [27]).
About 51.3% of tomato farmers in the study area
had annual income of N 50 000 - N 100 000 from
tomato production, 22.5% of the respondents
had below N 50 000, 13.3% had above N 150
000 annually from tomato production, while
12.9% of the sampled respondents had between
N 100 000 – N 150 000 from tomato production.
The average income of the respondents from
tomato production was N 74 590. This implies
that tomato production in the study area is still at
the subsistence level. Mikloda [28] associated
low income with poverty. Also, according to [29],
over 90% of the country’s food supply comes
from the agricultural population who are
smallholder farmers.

Ibitoye et al.; AJAEES, 6(4): 220-229, 2015; Article no.AJAEES.2015.080
224
Table 1. Distribution of respondents according to socio-economic characteristics
Socio-economic indicators Frequency
Percentage Mean/Mode
A. Age (years)
20-40
41-60
Above 60
Total
19
198
23
240
7.9
82.5
9.6
100
51 years
B. Sex
Male
Female
Total
173
67
240
72.1
27.9
100
Male
C. Marital status
Single
Married
Widowed
Divorced
Total
28
184
17
11
240
11.7
76.6
7.1
4.6
100
Married
D. Educational status
No formal education
Primary education
Secondary education
Tertiary education
Total
120
68
37
15
240
50.0
28.3
15.4
6.3
100
No formal education
E. Major occupation
Farming
Civil service
Trading
Artisan
Total
148
47
17
28
240
61.7
19.5
7.1
11.7
100
Farming
F. Farming experience (years)
1-10
11-20
21-30
Above 30
Total
21
10
33
176
240
8.7
4.2
13.8
73.3
100
31 years
G. Farm size (hectares)
Less than 1
1-1-2.0
2.1-3.0
Above 3
Total
96
121
13
10
240
40.0
50.4
5.4
4.2
1.3 hectares
H. Family size (Number)
1-6
7-12
Above 12
Total
72
90
78
240
30.0
37.5
32.5
100
7 members
I. Level of Income (Naira)
Below 50 000
50 000 – 100 000
100 001 – 150 000
Above 150 000
Total
54
123
31
32
240
22.5
51.3
12.9
13.3
100
89, 000
Source: Field survey, 2014

Ibitoye et al.; AJAEES, 6(4): 220-229, 2015; Article no.AJAEES.2015.080
225
3.2 Effect of Socio-Economic Characteris-
tics on Tomato Output in Kogi State
The regression analysis on the effect of socio-
economic variables on the output of tomato in the
study area is presented in Table 2.
Ordinary Least Square (OLS) estimation
technique was used to determine the effect of
socio-economic characteristics on tomato output
in the study area. Three functional forms such as
linear, semi-log and double-log were fitted into
the model.
After some econometric considerations such as
number of significant variables, F – ratio and R
2
value, the double-log functional form was
selected as the lead equation.
The regression result indicated an R
2
value of
0.740 meaning that 74 percent of the variability in
the model was explained while the remaining 26
percent could be attributed to error terms and
omitted variables. The F-ratio was 132.38 at 1
percent significance which means that the
independent variables jointly explained the
dependent variable.
Table 2 indicated that years spent in school,
extension contact, and farm size were significant
socio-economic variables influencing the output
of tomato production in the study area. Number
of years spent in school (X
4
) was found to be
positively related to the output of tomato and
significant at 1 percent. This implies that an
increase in the number of years spent in school
increases the output of tomato. The higher the
level of education, the more enlightened a farmer
becomes in adopting new innovation with its
multiplier effect on increased output. Education is
believed to increase the ability to perceive,
interpret and react to new events and improves
farmers’ managerial skills. This agrees with [30]
who reported that formal education has helped
farmers to obtain useful information from
bulletins, agricultural newsletters and other print
media sources of information. Sani et al. [31]
underscore the importance of the individual
farmer to know how to seek for and apply
information on improved farm practices.
The coefficient of extension contact (X
6
) was
found to be positive and significant at 1 percent.
This implies that an increase in extension contact
increases the output from tomato production.
Otunaiya and Akinleye [32] confirmed that
contact with extension workers will increase the
likelihood that a farmer will adopt improved
maize technologies and this will lead to
increased maize output. Also, [17] found a
positive relationship between extension contact
and the output of irrigated tomato in Niger State.
Table 2. Regression results for effect of socio-economic variables on tomato output
Variables Linear Semi-Log Double-Log
Constant
Sex
Age
Farming Experience
Years Spent in School
Household size
No. of Extension contacts
Farm size
F-value
R
2
8.075
(0.025)
279.587
(2.314)
*
0.269
(0.50)
4.204
(0.861)
26.266
(3.63)
**
5.380
(0.267)
171.511
(1.350)
1537.874
(22.418)
**
74.505
**
0.692
7.076
(35.242)
**
-0.048
(-0.629)
0.004
(1.055)
0.003
(1.133)
-0.0196
(-4.01)
**
-0.016
(-1.226)
-0.037
(-0.467)
0.288
(6.868)
**
68.105
**
0.57
7.623
(24.656)
**
0.0056
(1.41)
-0.070
(-0.863)
0.021
(0.596)
0.089
(3.657)
**
0.001
(0.026)
2.952
(69.12)
**
0.851
(25.492)
**
132.38
**
0.740
Source: Computed from field survey, 2014
Note: Figures in parentheses are t–values.
*
and
**
denote 5 and 1 percent level of significance respectively

Ibitoye et al.; AJAEES, 6(4): 220-229, 2015; Article no.AJAEES.2015.080
226
The regression result also shows that the
coefficient of farm size (X
7
) was positive and
significant at 1 percent. This implies that a unit
increase in the hectares of farm land for tomato
will lead to an increase in the output of tomato,
ceteris paribus. This corroborates [17] who
reported a positive relationship between farm
size and irrigated tomato output at 1 percent
level of significance.
Furthermore, the coefficient of sex, farming
experience, and household size were positive.
However, the relationships were statistically not
significant at the levels tested in this study. This
implies that an increase in these socio-economic
variables will lead to increased tomato output.
The result on farmers’ age shows a negative
relationship with a coefficient of -0.070. This
implies that the older a farmer, the less energetic
he becomes in carrying out farming operations
leading to decreased tomato output.
3.3 Effects of Resources Used on Tomato
Output
The effect of resources used on tomato output in
Kogi State is presented in Table 3.
The efficiency indictor in Table 4 revealed that
pesticide, quantity of seed, and kg of fertilizer
has ratios that are less than unity. This means
that these variable inputs in tomato production
were over-utilized and increase in the supply of
these resources will increase tomato output. The
finding of this study on seed corroborates with
[17] who reported an efficiency ratio of -19.3 for
quantity of seed used in irrigated tomato
production in Niger State. Also, [33] found an
over-utilization of fertilizer, pesticide, and seed
with efficiency ratio of 0.08, -0.04, and 0.16
respectively for tomato production in Benue
State.
Table 4 also shows that inputs such as labour
and farm size have an efficiency ratio of 1.2 and
15.2 respectively. This means that these inputs
were under-utilized in tomato production in the
area and a decrease in the supply of these
resources will increase the output of tomato
produced in the State. The result on farm size
agrees with [33] who found an efficiency ratio of
1.24 for farm size. The finding on labour agrees
with [17] who reported an efficiency ratio of 9.584
for labour. All the inputs were not utilized to
optimum economic advantage. A resource is said
to be optimally allocated if there is no significant
difference between the MVP and MFC, that is, if
the ratio of MVP to MFC = 1.
Table 3. Linear regression for the estimation of resource use efficiency in tomato production
Variables
Coefficients
Std. error
t-value
p-value
Pesticide
Labour
Quantity of seed
Years in school
Farm size
Fertilizer
Farming experience
Household size
F value = 65.471
Prob >F = 0.000
R
2
= 0.694
Adjusted R
2
= 0.683
64.580
123.652
55.934
19.999
1519.891
0.974
7.005
11.398
37.893
44.964
39.478
11.088
86.621
1.193
4.786
20.316
1.704
2.745
1.852
1.804
17.546
0.816
1.464
0.561
0.090
*
0.003
**
0.068
*
0.073
*
0.000
***
0.415
0.145
0.575
Source: Computed from field survey, 2014.
Table 4. Estimated resource use efficiency in tomato production in Kogi State
Farm inputs
Coefficient
P
y
MVP
MFC
r= MVP/MFC
Remarks
Pesticide
Labour
Seed
Farm size
Fertilizer
64.580
123.652
55.932
1519.891
0.974
5
5
5
5
5
322.9
618.26
279.66
7599.46
4.87
1850
500
925
500
100
0.2
1.2
0.3
15.2
0.05
Over-utilized
Underutilized
Over-utilized
Underutilized
Over-utilized
Source: Computed from field survey, 2014

Ibitoye et al.; AJAEES, 6(4): 220-229, 2015; Article no.AJAEES.2015.080
227
4. CONCLUSION
The study analysed resource use efficiency in
tomato production in Kogi State, Nigeria. The
OLS regression result revealed that pesticide,
labour, years spent in school, quantity of seed
and farm size were positively and significantly
related to tomato output in Kogi State. The
efficiency ratio result showed that quantity of
pesticide, seed and fertilizer were over utilized
while labour and farm size were underutilized.
The study further showed that all the inputs were
not utilized to optimum economic advantage. The
profit level of farmers can be increased if these
resources are efficiently allocated and utilized.
Also, farmers’ educational experience, contact
with extension workers, and farm size increased
tomato output in the State.
5. RECOMMENDATIONS
Based on the findings the following
recommendations were made:
1. Prices of inputs such as fertilizer, seed and
pesticide should be subsidized by
government. This will enable farmers
increase the use of these resources as
they were over-utilized in tomato
production in the study area.
2. There should be extension services that
will facilitate the efficient utilization of
agricultural resources among tomato
farmers in Kogi State. This will enhance
the output of tomato produced in the area
and achievement of optimum resource
allocation.
3. Educational status had positive
relationship with tomato farmers’ output.
Therefore, policies that will enable the
farmers to improve on their education and
grant them increased access to credit
should be vigorously pursued for
increasing the farmers’ efficiency and
income.
4. Tomato farmers in the area should be
encouraged to form cooperative societies
so as to enable them obtain loans from
commercial banks, agricultural banks, and
other financial institutions. This will enable
them purchase the needed inputs that will
increase tomato output in the area.
COMPETING INTERESTS
Authors have declared that no competing
interests exist.
REFERENCES
1. Agrios GN. Plant pathology. New York,
Academic Press, USA; 2003.
2. Osemwegi OO, Oghenekaro AO, Owolo
LO. Effect of pulverized Ganoderma spp.,
on Sclerotium rolfsii Sacc and Post-harvest
tomato fruit preservation. Journal of
Applied Science and Research. 2010;6:
1794-1800.
3. Nonneoke IL. Vegetable production. New
York, Van Nostrand Reinhold. 1989;657.
4. Jones JB. Tomato plant culture. Boca
Raton, CRC Press, LLC. FL. 1999;1-3.
5. Enrique CB, Eduardo RW. Tomato fruit
quality conservation during postharvest by
application of potassium bicarbonate and
its effect on Botrytis cinerea. Cien. Inv.
Agr. 2006;33:67-172.
6. Smith AF. The tomato on America: Ilorin,
University of Ilorin press; 1994.
7. Central Bank of Nigeria, (CBN): Daily Trust
Newspaper, Tuesday, January 28, 2014.
Category: Agriculture Published on
Thursday, 29 August 2013 06:00 Written
by Vincent A. Yusuf.
8. John D, Suthin RT, Usha RS,
Udhayakumar R. Role of defense enzymes
activity in tomato as induced by
Trichoderma virens against Fusarum wilt
caused by Fusarium oxysporum F. Sp
Lycopersici. Journal of Biopesticide. 2010;
3:158-162.
9. Giovannucci E. Tomatoes, tomato-based
products lycopene, and cancer: review of
the epidemiologic literature. J. Natl Cancer
Inst. 1999;17(91):317-331.
10. Ogunniyi LT, Oladejo JA. Technical
efficiency of tomato production in Oyo
State, Nigeria. Agricultural Science
Research Journal. 2011;1(4):84–91.
11. Erdogan G. The econometric analysis of
tomato production with contracting in
Turkey. Journal of Applied Science.
2007;7(14):56-77.
12. Haruna U, Sani MH, Danwanka HA, Adejo
E. Economic analysis of fresh tomato
marketers in Bauchi metropolis of Bauchi
State, Nigeria. Nigerian Journal of
Agriculture, Food and Environment. 2012;
8(3):1-8.
13. National Population Commission (NPC).
The 2006 Population Census. Official
Gazette. Abuja. 2007;94(24).
14. Kogi State Economic Empowerment and
Development Strategy (KOSEEDS).
Towards Poverty Alleviation Wealth

Ibitoye et al.; AJAEES, 6(4): 220-229, 2015; Article no.AJAEES.2015.080
228
Creation. Lokoja, Kogi State Ministry of
Budget and Planning. 2004;17.
15. Gani M, Mohammed S, Baba BA. Analysis
of resource use efficiency in rice
production in the Lake Chad Area of Borna
State, Nigeria. Journal of Sustainable
Development in Agriculture and
Environment. Paraclet publishers 2007;
3(2):31-37.
16. Usman J, Bakar UM. Profitability of small
scale dry season tomato (Lycopersicon
esculentum Mill.) production in Adamawa
States, Nigeria. Journals of Science and
Technology. 2013;3(6):25-39.
17. Ojo MA, Ibrahim OA, Mohammad US.
Profitability and production function of
small scale irrigated tomato production in
Niger State, Nigeria. Continental Journal of
Agricultural Economics. 2009;3:16-22.
18. Olayemi FF, Adegbola JA, Bamishaiyi EI,
Awagu EF. Assessment of post harvest
losses of some selected crops in eight
Local Government Areas of Rivers State,
Nigeria. Asian Journal of Rural
Development. 2011;2(3):123-135.
19. Babalola DA, Makinde YO, Omonona BT,
Oyekanmi MO. Determinants of
postharvest losses in tomato production: a
case study of imeko – Afon local
government area Ogun State. Acta
SATECH. 2010;3:14-18.
20. Daramola AG. Competitiveness of Nigeria
agriculture in global economy: Any
dividends of democracy? Inaugural
Lecture Series 36, Federal University of
Technology, Akure; 2004.
21. Maurice DC. Resource production in
cereals crop production among fadama
farmers of Adamawa State Nigeria. M.Sc.
Thesis, Department of Agricultural
Economics and Extension, Federal
University of Technology, Yola, Nigeria;
2004.
22. Ibitoye SJ, Orebiyi JS, Shaibu UM.
Economic effect of inorganic pesticide use
on fadama ii rice farming in Ibaji Local
Government Area, Kogi State, Nigeria. Int’l
Journal of Agric. And Rural Dev. 2012;
15(2):1063–1070.
23. Agwu AE, Anyanwu AC. Sociocultural and
environmental constraints in implementing
the NALDA Programme in South eastern
Nigeria: A case study of Abia and Enugu
States. Journal of Agriculture, Technology
and Education. 1996;1(2):68-72.
24. Salisu SA. Individual pump ownership and
associated service providers in Fadama
irrigation in Northern Nigeria. In Hilmy S,
Charles, L (Eds) private irrigationin Sub-
Saharan Africa. Regional seminar on
private sector participation and Irrigation
Expansion in Sub-Saharan Africa 22-26
October, Accra, Ghana; 2001.
25. Korie OC, Ejike OU, Orebiyi JS,
Osugiri II,
Saliu OJ, Otitolaiye JO. Evaluation of the
traditional method of palm oil processing in
Isu L.G.A of Imo State, Nigeria.
International Journal of Agricultural
Economics, Management and
Development. 2013;3:102-111.
26. Orebiyi JS, Eze CC, Henry-Ukoha A,
Akubude FC, Ibitoye SJ. Demand for
institutional credit from NACRDB by small
scale farmers in Imo State, Nigeria.
International Journal of Agricultural
Science, Research and Technology. 2011;
1(2):83-87.
27. Emodi AI. Analysis of rice (oryza spp)
innovation system in Southeast Nigeria.
Ph.D Thesis, Department of Agricultural
Extension, University of Nigeria, Nsukka;
2010.
28. Mikloda PI. The effect of agricultural credit
guarantee scheme on household income
and consumption in Adamawa State,
Nigeria. A Ph.D Thesis, University of
Maiduguri, Nigeria; 2006.
29. Amalu UC. Poverty alleviation and
agriculture in sub-saharan Africa: The
Nigerian experience. Journal of food,
Agriculture and Environment; 2005;3(2):
230-236.
30. Adejoh SO, Onuche U, Edoka MH.
Evaluating the factors influencing the
adoption of selected soil management
technology by yam farmers Olamaboro
LGA of Kogi State, North Central Nigeria.
International Journal of Agricultural
Economics. Management. & Development.
2010;1(1):1-5.
31. Sani A, Abubakar BZ, Yakubu,DH, Atala
TK, Abubakar L. Socio-economic factors
influencing adoption of dual-purpose
cowpea production technologies in Bichi
Local Government Area of Kano State,
Nigeria. Asian Journal of Agricultural
Extension, Economics & Sociology. 2014;
3(4):257-274.
32. Otunaiya AO, Akinleye SO. Adoption of
improved maize production technologies in

Ibitoye et al.; AJAEES, 6(4): 220-229, 2015; Article no.AJAEES.2015.080
229
Yewa North LGA of Ogun State, Nigeria.
Proceedings of 10
th
Annual National
conference of Nigeria Association of
Agricultural Economists (NAAE) held at
university of Abuja. 2008;395-403.
33. Orefi A, Mimidoo A, Peter TT. Can small-
scale tomato farmers flourish in Benue
State, Nigeria? Journal of Agricultural
Science. 2011;2(2):77-82.
_________________________________________________________________________________
© 2015 Ibitoye et al.; This is an Open Access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
Peer-review history:
The peer review history for this paper can be accessed here:
http://www.sciencedomain.org/review-history.php?iid=1060&id=25&aid=9398