Analysis of Profitability of Fish Farming in Ogun State



© Kamla-Raj 2010 J Hum Ecol, 31(3): 179-184 (2010)
Analysis of Profitability of Fish Farming in Ogun State, Nigeria
S. A. Adewuyi,* B. B. Phillip**, I. A. Ayinde*and D. Akerele*
*Department of Agric Economics & Farm Management, University of Agriculture,
Abeokuta, Ogun State, Nigeria
** Research and Development Centre, University of Agriculture, Abeokuta,
Ogun State, Nigeria

KEYWORDS : Profitability. Fish Farming. Gross Margin. Elasticities
ABSTRACT  This study was conducted in Ogun state, Nigeria and made use of both primary and secondary data.

The
main instrument for collecting the primary data was structured questionnaire.
The descriptive analysis showed that
a large proportion (68%) of the fish farmer had formal (tertiary) education and financed their fish production through
personal savings. Equally evident from the result is that an average total cost of N394,380 was incurred per annum
by fish farmers while gross revenue of N 715030.30 was realized with a gross margin of N 574314 and a profit of N
320650. The rate of return on investment of 0.55 implies that for every one naira invested in Fish production by
farmers, a return of N1.55 and a profit of N0.55 were obtained. The multiple regression result revealed that fish
output was significantly determined by pond size, labour used, cost of feeds, cost of lime and cost of fingerlings. The
coefficient of determination, R2
 value of 0.462 indicates that 46.2% of the variation in the value of fish output was
explained by pond size, quantity of labour used, cost of feed, cost of lime and cost of fingerlings The degree of
responsiveness of the value of fish output to changes in the independent variables shows that a percent increase in the
values of pond size, labour, feeds, fertilizer, lime, fixed input and fingerlings will lead to 0.029%, 0.057%, 0.005%,
0.534%,0.007% , 0.79% and 0.001% in the value of fish produced respectively. The study concluded that fish
production in the study area is economically rewarding and profitable. It is capable of creating employment, augmenting
income and improving the standard of living of the people. Therefore, it recommended government participation in
fish farming to boost the quantity of fish available for consumption.

1. INTRODUCTION

The Nigerian fishing industry comprises of
three major sub sectors namely the artisanal,
industrial and aquaculture. The awareness on the
potential of aquaculture to contribute to domestic
fish production has continued to increase in the
country. This stems from the need to meet the
much needed fish for domestic production and
export. Fish species which are commonly cultured
include Tilapia spp, Heterobranchus bodorsalis,
Clarias gariepinus, Mugie spp, Chrysichthys
nigrodigitatus, Heterotis niloticus, Ophiocephalus
obscure, Cyprinus carpio and Megalo
spp. Fish culture is done in enclosures such as
tanks.The aquaculture sub sector contributes
between 0.5% and 1% to Nigeria’s domestic fish
production.
The rapid increase in population of the world
has resulted in a huge increase in the demand for
animal protein (which is essentially higher in
quality than plant protein). The average protein
intake in Nigeria which is about 19.38/output/ day
is low and far below FAO requirement of 65g/
output/day. The nutritional requirement is
particularly crucial in a developing country such
as Nigeria where malnutrition and starvation are
the major problems faced by million of rural
dwellers .The low protein intake is an indication
of shortage of high quality protein food in the
diet of Nigerians. The consumption has been
estimated to be 1.56267metric tones Tabor (1990).
Although fishing started over 40 years ago,
aquaculture has not significantly contributed to
domestic fish production. Equally estimated was
the possible creation of 30000 jobs and generation
of revenue of US$160 million per annum by the
aquaculture industry.
Fish has been recognized to contribute 55%
to the protein intake in Nigeria. However, local
fish production has been below consumption with
imports accounting for aboutUS$48.8m in 2002
(Central Bank of Nigeria 2004).Despite the
increase in the major sources of animal protein
such as livestock and poultry industries, the
problem of protein deficiency still continues
unabated. The protein deficiency in diet is equally
associated with the inability of fish farming
industry to supply the required quantity of fish.
The situation causes poor health, low efficiency,
low productivity and poor standard of living and
decline in the contribution of fishery industry’s180 S. A. ADEWUYI, B. B. PHILLIP, I. A. AYINDE AND D. AKERELE
contribution to the Gross Domestic Product
(GDP).The industry now contributes only2.0%
of the GDP and accounts for 0.2% of the total
global fish production. Nigeria is one of the
largest importers of fish with a per capita
consumption of 7.52kg and a total consumption
of 1.2million metric tones with imports making up
about 2/3 of the total consumption. This indicates
the large deficit in fish supply in Nigeria Olopade
and Olaokun (2005). It is therefore expedient to
examine the profitability of fish farming in the
study area to identify possible areas that require
improvement. The development of the fish
industry will increase local production of fish and
save much of the foreign exchange being used
for fish importation. Specifically, it has a special
role of ensuring food security, alleviating poverty
and provision of animal protein.
The study will therefore describe the socioeconomic
status of fish farmers, determine the
profitability of fish farming and examine the
determinants of fish output in the study area.
1.1 Research Hypothesis
H0
: There is no significant relationship
between the quantity of fish produced and the
educational level of fish farmers.
H1
: There is a significant relationship between
the quantity of fish produced and the educational
level of fish farmers.
2. RESEARCH METHODOLGY
This study was conducted in Ogun state, Nigeria
and made use of both primary and secondary data.
The main instrument for collecting the primary data
was structured questionnaire. Information were
collected on input and output in fish farming and
socio-economic characteristics of fish farmers
through personal interview. The primary data were
supplemented with secondary data from journals,
books and publications from National Bureau of
Statistics, Central Bank of Nigeria and Nigeria
Institute for oceanography and marine Research
(NIOMR). A total sample of 82 fish farmers were
selected randomly from the list of fish farmers with
the assistance of extension agents from Ogun state
Agricultural Development Programme (OGADEP)
for the study.
Data analysis was done using the descriptive
statistics, budgetary technique and multiple
regression technique.
2.1 Budgetary Technique
The budgetary technique involves the cost
and return analysis. It was used to determine the
profitability of fish farming in the study area.
2.1.1.Model Specification
Π = TR- TC………………………..Equation 1
TR= PQ………………………...…. Equation 2
Where
Π = Total Profit (N)
TR=Total revenue (N)
TC= total Cost (N)
P= Unit price of output (N)
Q= Total quantity of output (N)
2.1.2 The Regression Model
The multiple regression model was employed
to determine the influence of socioeconomic
factors on the fish output level. The model is
specified as follows
Q=f(X1
, X2
, X3
, X4
, X5
, X6
, X7
, e) ....Equation 3
Q is the value of fish output in naira
X1 represents the pond size measured in
square metres
X2
 is the quantity of labour used in fish
production in mandays
X3 is the cost of feeds measured in naira
X4
 represents the cost of fertilizer in naira
X5 stands for the cost of lime in naira
X6
 represents the cost of fixed inputs in naira
X7
 is the cost of fingerlings measured in naira
e= Error term
Following Olayemi (1998) the relationship
between the endogenous variable and each of
the exogenous variables were examined using
linear, exponential, logarithm and quadratic
functional forms. Based on the value of the
coefficient of determination (R2
), statistical
significance and economic theory that support
fish production, the lead was chosen
3. RESULTS AND DISCUSSION
 3.1 Descriptive Analysis
 Evidence from the descriptive analysis of
socio economic characteristics of respondents
in the study area in table 1 shows that male fish
farmers constituted about 87.7% as compared to
the female farmers that represent 12.3%. This ANALYSIS OF PROFITABILITY OF FISH FARMING IN OGUN STATE, NIGERIA 181
indicates the dominance of men in fish production

in the study area.



The fish farmers whose age fall
between 31 – 40 years constituted the majority.
On the whole, 96.3% fall into the economically
active group of 20 – 50 years. The result of the
marital status shows that majority 63.7% of the
fish farmers were married. It is also evident that
most of the respondents (71.9%) were part time
fish farmers. A large proportion (68%) of them
fish farmer had formal (tertiary) education and
finances their fish production through personal
savings. The farmers can therefore be said to be
literate since only small proportion of them had
no formal education. The result compares favourably
with Aromolaran (2000) .The distribution of
the household size indicates that the household
size ranged from 2 to 13 while the average fish
pond size was found to be 355m2
. The study also
revealed poor extension visits to fish farmers who
mostly operated on part-time basis. Also 74
(90.3%) of them obtained their fingerlings from
farm gate while 84.2% purchased the feeds and
10.5% used household wastes. The descriptive
analysis also indicates that most fish farmers
(53.7%) fed their fish twice daily to achieve high
yield while majority of them (57%) had no formal
training on fish farming. The most common
breeds of fingerlings utilized by fish farmers were
Claris, Heteroclarias and Tilapia.
3.2 Profitability Analysis
The study examines the profitability of fish
production in the study area. To determine the
profit level, attempts were made to estimate the
cost and return from fish farming. The input used,
cost, yield or output data generated from the
farmers were used to undertake the cost and return
analysis for assessing the profitability of fish
Table 1: Socio economic characteristics of fish
farmers
Frequency Percentage (%)
Education
Primary 3 3.7
Secondary 68 82.9
Tertiary 1 1 13.4
Total 82 100.0
Age
10-20 3 3.7
21-30 21 25.6
31-40 41 50.0
41-50 13 15.9
>50 4 4.8
Total 82 100.0
Marital Status
Married 58 63.7
Single 2 4 25.3
Total 82 100.0
Sex
Male 71 86.6
Female 11 13.4
Total 82 100.0
Household Size
1-4person 33 40.7
5-8 29 35.4
>8 1 1.2
No response 19 23.2
Total 82 100.0
Total 108 100.0
Farming Experience (Years)
<5 51="" 62.2="" p="" yrs="">5-10yrs 25 30.1
11-15 yrs 3 3.8
>15yrs 3 3.8
Total 82 100.0
Times of Feeding
1 time 10 12.2
2 times 44 53.7
3 times 24 29.3
4 times 2 2.4
5 times 2 2.4
Total 82 100.0
Contact with Extension Workers
0 time 64 78.0
1 time 5 6.1
2 times 8 9.8
3 times 4 4.9
5 times 1 1.2
Total 82 100.0
Training on Fish Farming
Formal training 25 30.5
No formal training 57 69.5
Total 82 100.0
Mode of Farming
Par time 59 71.9
Full time 23 28.1
Total 82 100.0
Sources of Finance
Personal savings 68 82.9
Friends 1 1.2
Relatives 2 2.4
Cooperatives 9 11.0
Bank loans 2 2.4
Total 82 100.0
Sources of Feeds
Purchase 68 83.9
Households waste 7 8.5
Others 7 8.5
Total 82 100.0
Farming Experience (Years)
<5 50="" 61.7="" p="">5-10 25 30.8
11-15 3 3.7
>15 3 3.7
Total 82 100.0
Source: Field survey data 2007.
Frequency Percentage (%)
Table 1: contd...182 S. A. ADEWUYI, B. B. PHILLIP, I. A. AYINDE AND D. AKERELE
production in the study area. The cost and return
analysis is presented in the table 2. The result
reveals that the cost of fingerlings accounted for
the largest proportion (12.4%) of the total cost of
fish production. This is followed by cost of feeds
(11.7%).The lime cost and labour cost accounted
for 3.2% and4.9% of the total cost respectively.
This clearly shows that large amount of money is
spent by fish farmers in the study area for the
purchase of fingerlings and feeds. The fixed cost
of production consists of cost of fixed assets such
as pump, vehicles, aerators and pond which
accounted for 61.6% of total production cost.
consistent with the finding of Ashaolu et al. (2005)
from their studies on profitability on fish farming.
The rate of return per capital invested (RORCI) is
the ratio of profit to total cost of production .It
indicates what is earned by the business by
capital outlay Awotide and Adejobi (2007). The
result revealed that the RORCI of 80% is greater
than the prevailing bank lending rate, 20%
implying that fish farming in the study area is
profitable. If a farmer takes loan from the bank to
finance fish farming, he will be 60k better off on
every one naira spent after paying back the loan
at the prevailing interest rate.
3.3 Multiple Regression Result
The regression analysis was carried out to
examine the determinants of factors effecting fish
output in the study area. Based on the econometric
and statistical criterion, the double logarithm
was chosen as the lead equation and the
results as presented in the table 3. The multiple
regression result revealed that fish output is
significantly determined by pond size, labour
used, cost of feeds, cost of lime and cost of
fingerlings. The coefficients are in line with the a
priori expectation. Hence, the more the amount
expended on labour, lime and feeds, the more the
amount that will be realized from fish farms in the
study area. The result is consistent with the
finding of Yusuf et al. (2002). The result equally
suggests the need for fish farmers to purchase
more of these inputs to increase their revenue
from fish production. Similarly, policies that will
ensure availability of these inputs to fish farmers
at affordable price should be put in place. The
positive relationship between value of fish and
pond size indicates that with increase in the size
of fish pond, more fish will be produced. This is
not surprising because all things being equal the
Table 2: Average cost and return of fish production
Item (Annual) Amount (#) % of total cost
Fertiliser 13695.72 3.4
Feeds 46450.77 11.7
Lime 12742.34 3.2
Fingerlings 48898.57 12.4
Labour 19519.13 4.9
Total variable cost 140716.3
Fixed inputs 243287
Total cost 394380
Total returns 715030.30
Profit 320650
ROI 0.55
ROIC 0.81
Source: Computed from Field survey data 2007
Table 3 The regression result of the determinants of fish output in the study area
 Variable Coefficient Beta T Significant
Constant 6.238 - 4.882 .000*
Pond size 0.195 .204 2.234 .029**
Labour 0.363 .174 1.934 0.57
Feed 0.266 .263 2.888 0.005*
Fertilizer 0.0266 .056 0.625 0.534
Lime 0.06121 0.248 2.780 0.007*
Fixedinput 0.140 0.163 1.783 0.79
Fingerling 1.481E-05 0.316 3.33 0.001*
R2
 = 0.462; F stat = 9.074
*variable significant @1% ** Variable significant @5%
Source: Computd from Field survey data 2007.
 Equally evident from the result an average
total cost of N394380 was incurred per annum by
the respondents while gross revenue of N
715,030.30 was realized thereby returning gross
margin of N 574,314 and a profit of N 320650. The
rate of return on investment of 0.55 implies that
for every one naira invested in rice production
by farmers, a return of N1.55 and a profit of N0.55
were obtained.
The implication of this is that there is a
considerable level of profitability in fish farming
in the studys findings area. This result isANALYSIS OF PROFITABILITY OF FISH FARMING IN OGUN STATE, NIGERIA 183
quantity of fish produced is directly proportional
to the pond size.
Based on the significance of labour used at
5%, the null hypothesis that the fish output is
not affected by the quantity of labour used is
rejected and the alternative is accepted. The
coefficient of determination, R2
 values of 0.462
indicates that 46.2% of the variation in the value
of fish output is explained by pond size, quantity
of labour used, cost of feed, cost of lime and cost
of fingerlings. Also, 53.8% of the variation in the
value of fish is determined by other factors not
considered.
Table 4 shows that the regression coefficient,
standard error, F ratio and the level at which the tratio
was significant for each of the independent
variables. The performance of the analysis of
variance in table 4 shows that F ratio of 9.074 was
significant at 0.01 alpha level. This provided the
evidence that a combination of pond size, cost of
labour, cost of feeds, lime, fertilizer, fixed inputs
and cost of fingerlings had joint impact on the
fish output in the study area. The beta weight
ranged from 0.056 to 0.316. The result implies that
out of seven independent variables considered,
fingerling is the most important input. It has the
highest value of 0.316. This is followed by the
quantity of lime while fertilizer is the least. This is
not surprising because irrespective of the efforts
and management practices, the output from a fish
farm will be determined by the quantity and
quality of fingerlings used.
3.4 Elasticity of Production and Return to
Scale
The magnitude of elasticity of production is
one of the economic concepts of measuring
efficiency in resource-use (Oludimu 1987). The
total sum of elasticities of production of the
significant variables, 0.834 as shown in table 5
was less than unity. This suggests that fish
production in the study area had a decreasing
return. The implication is that each additional unit
of the inputs will results in a small increase in the
Source of variation Sum of square Df Mean square F-ratio Sig.
Due to regression 41.060 7 5.866 9.074 0.000
Due to Residual 47.837 74 0.646
Total 88.897 81
Source: Computed from Field survey data 2007.
*Significant at 1%
Table 4: Analysis of variance.
Independent variables Elasticities of production
Pond size* 0.195
Labour* 0.363
Feed* 0.266
Fertilizer 0.0266
Lime* 0.06121
Fixed input 0.140
Fingerling* 1.481E-05
Source: Computed from field survey data 2007.
*Significant Variable@5% .
Table 5: Elasticity of production and return to scale
of fish farmers
value of fish output than the preceding unit. This
shows that production occurred among fish
farmers in the study in stage 2, a rational stage of
production. In stage 2, the sum of elasticities of
production is greater than zero but less than one
The implication is that the more the inputs used,
the higher will be the value of fish even though at
a decreasing rate. This finding is consistent with
that of Olagunju et al. (2007) in their study on
economic viability of cat fish production in Oyo
state, Nigeria. The degree of responsiveness of
the value of fish output to changes in the
independent variables shows that a percent
increase in the values of pond size, labour, feeds,
fertilizer, lime, fixed input and fingerlings will
lead to 0.029%, 0.057%, 0.005%, 0.534%,0.007% ,
0.79% and 0.001% in the value of fish produced
respectively. With the production result, increase
in the utilization of labour and feeds is likely to
boost the fish output substantially.
4. CONCLUSION AND RECOMMENDATIONS
 Based on the value of benefit indicators, it
can be concluded that fish production in the study
area is economically rewarding and profitable. It
is capable of creating employment, augmenting
income and improving the standard of living of
the people.
Based on the findings of the study, the
following policy recommendations are made:
Adequate training programme on fish
production should be organized for fish farmers184 S. A. ADEWUYI, B. B. PHILLIP, I. A. AYINDE AND D. AKERELE
in the study area for the dissemination of research
findings to fill the gap created by poor contact
with extension agents.
The ownership structure revealed that most
of the fish farms were owned by individuals who
had little access to finance. Therefore, government
participation in fish farming should be
encouraged in the area to boost the quantity of
fish available for consumption.
Fish farming in the area is male dominated.
Females need to be encouraged to participate in
fish farming in the area as a means of augmenting
their income and improve their standard of living.
Fish farmers should be organized into
formidable groups such as cooperative to enjoin
economies of scale in the purchase of inputs and
sale of output. The formation of the cooperative
should also be done towards ensuring labour
availability.

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