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Effect of Production Gap on Farm Income of Young Catfish Producers in Oyo State, Nigeria

Victoria Adeyemi Tanimonure^* Oyedoyin Leah Oyedibu and Olabisi Damilola Omodara

Department of Agricultural Economics, Obafemi Awolowo University, Ile-Ife, Nigeria

*Corresponding author: Victoria Adeyemi Tanimonure, Department of Agricultural Economics, Obafemi Awolowo University, Ile-Ife, Nigeria. Ph: +2348034822176, E-mail: vicofgodng@yahoo.com

Citation: Tanimonure VA, Oyedibu OL, Omodara OD (2019) Effect of Production Gap on Farm Income of Young Catfish Producers in Oyo State, Nigeria. J Aquat Res Mar Sci 2019: 178-181.

Received Date: 26 May, 2019; Accepted Date: 03 July, 2019; Published Date: 12 July, 2019

Abstract

The study examined the effect of production gap in catfish enterprise in Oyo State, Nigeria. Two Local Government Areas (LGAs) were purposely selected based on the high concentration of Catfish producers. A simple random sampling technique was then used to select 80 farmers from the list of registered catfish producers in the LGAs. Data collected were analyzed using descriptive statistics, budgetary and multiple regression analyses. The findings revealed that Catfish enterprise in the study area is dominated by male, who were married with mean age of 36.65 years and 5.57 years of production experience, average household size of 5 members with high (15.4) years of formal education. A wide production gap was observed among farmers averaged 0.23kg and 93% of the respondents produced below the expected average weight of 0.99kg. The enterprise was profitable, on every ₦1 invested, there was a return of ₦1.81. Also, the effect of production gap on net income was found to be significant and negative. Other variables that affected net income were age and years of experience. While years of experience had positive effect on net income, age had negative effect on it. It was concluded that many farmers are producing below the expected output. Therefore, young fish farmers need target training on best management practices in catfish production to bridge the gap between the expected average and actual average output in Catfish production.

Keywords: Agribusiness; Catfish Enterprise; Farmers’ Socio-Economics; Youth Empowerment

Introduction

Increasing human population and undernourished or starving people, especially in the developing countries like Nigeria, has made the need for food production generally and more specifically, protein rich foods a global issue [1]. In light of the foregoing, fish farming is increasingly becoming a vibrant, dynamic, and fastest growing sub-sector of the Nigerian economy. Fish farming or pisciculture is the act of rearing fish commercially in conditions where all the basic means of production can be controlled for profit maximization and/or cost minimization. It involves building earthen, concrete or tarpauling pond under a controlled management system.

The importance of Catfish production in Nigeria cannot be overemphasized. Aside the support for nutritional wellbeing and significance in improving human life, fish also provides important services including feedstock for the industrial sector and a more effective way to utilize natural resources [2]. Furthermore, fish contributes to rural development, increases export opportunities, and conserves biological diversity of Nigeria [1,3].

Like every other developing country, fish protein is an essential component of the food basket of Nigerians [2]. An average Nigerian consumes about 11kg of fish annually which is significantly lower than the global average of 21kg and some other sub-Sahara Africa countries such as Côte d’Ivoire (13.5kg) and Ghana (26.0kg) [4,5].  Statistics has shown that out of the 2.7 million metric tonnes annual total fish demand in Nigeria, only 30% is met from domestic production resulting into an annual spending of ₦125 billion (US$347m) on fish import [5,6]. However, in the last two years, domestic supply of fish has grown by 71% risen to 1.2 million metric tons; demand stand at 3.3 million metric tons and fish import bill declined significantly due to import ban on fish [7]. Congruently, young Nigerians show more interest in the fishery industry and agribusiness gain ground among the young elites [8]. Score card reports from FMARD [8], shows that Nigerian youths’ participation in agribusiness has risen tremendously in recent time due to the provision of incentive drives and more conducive business environments. Some of these incentives came from government provisions for credit facilities, group training, technical supports, insurance packages and farm inputs via youth targeted schemes such as the Nigerian Incentive-based Risk-Sharing for Agricultural Lending (NIRSAL), Anchor Borrower Scheme (ABS), and Growth Enhancement Scheme (GES) to boost sustainable productivity growth in the sector [8].

Similarly, as part of the efforts to enhance the performance of the fishery industry, Oyo State government and research institutes such as International Institute of Tropical Agriculture (IITA) enunciated several programmes to improve on the income level of youths and stimulate youths’ interest in agricultural production in the State. For instance, in 2011, IITA established the IITA Youth Agripreneurs (IYA) to encourage and improve the perceptions of more youths about agriculture [9]. This group of enterprising young Nigerians are gathered form diverse disciplinary backgrounds. Similarly, in 2015, Oyo State initiated integrated farming scheme for agricultural graduates and set up a micro credit scheme to assist youths engaged in agricultural production under Oyo State Youth Empowerment in Agriculture Programme popularly called YEAP [10]. The schemes according to literature has increased youth involvement in agriculture especially fish farming, however, the output gain is still below expectation [9].

Statement of the Research Problem

Despite the potential opportunities in fish farming and the increasing efforts from governments to boost productivity growth in the fishery industry, there still exist steady decline in output especially since the start of the 2017 as the segment generated ₦135 billion in the third quarter of 2017, compared with ₦138 billion and ₦171 in the second and first quarter of 2017 (Report Cited by Allafrica, [7]). This can be attributed to output weight differentials among fish farmers. Data from experimental studies has established that under intensive management system, table size weight of catfish can attain as high as 2.0kg and average table size weight of 0.99kg within a 6-month production cycle period [11]. Meanwhile, experimental studies reported an average of 1.5kg table size weight in catfish production across the southwestern States [12]. It is thus apparent that there is mismatch between experimental (demonstration field) and on-field (farmer’s field) table size weights which results into production gap [13,14].  Aside the environmental factors, empirical findings have further revealed that less than 50% of fish farmers in Oyo state are technically inefficient resulting from poor feed protein content (feed quality), feeding rate, stocking density, poor timeliness in the delivery of fingerlings supplies and management practices [15,16,17]. These are possible factors that can result into production gap in catfish production.

In general, a lot of literature exists on catfish, while some focus on the production of catfish [18,19,20,21], others focus on efficiency in production [15,17, 22,23], and some others on profitability of catfish production [18,21]. There are literatures that related catfish production to the welfare of producers [24] but literature that establishes gap in the production of catfish and the attendant effect of the gap on the profitability of the business are rather scarce, hence, this study. With the increasing participation of young people in catfish farming in Oyo state, it is therefore imperative to determine production gap in catfish yield among young catfish producers so as to determine possible effect of production gap on the net income of young catfish producers in Oyo State. The result from the study would be able to make necessary recommendations that could bridge the production gap in the study area.   

The main objective of this study is to investigate whether production gap affect net income in Catfish production in the study area or not. The specific objectives are to

1. describe the socio-economic characteristics of the young catfish producers
2. assess the production gap, and estimate costs and returns to catfish production
3. analyze the effect of production gap on net income in catfish production
4. identify technical constraints contributing to production gap in the study area

Materials and Methods

The study was carried out in Oyo State. Oyo State is located in the south-west geographical zone of Nigeria. The state is located between Latitude 8⁰ 00¹ 00¹¹ N and Longitude 4⁰ 00¹ 00¹¹ E, covering approximately an area of 28,454 square kilometers of land mass and ranked 14^th largest State in terms of size in Nigeria. The State is bounded in the south by Ogun State, in the north by Kwara State, in the west it is partly bounded by Ogun State and partly by the Republic of Benin. While in the east by Osun State. Oyo State has an equatorial climate with notable dry and wet seasons with relatively high humidity. In terms of vegetation distribution, Oyo State has a thick forest in the south and guinea savannah in the north, which give way to grassland interspersed with trees in the north. Oyo State is one of the dominant fish farming States in Nigeria due to its favorable climate.  A two-stage sampling technique was used to sample the respondents for the study. At the first stage, Ido and Lagelu Local Government Areas were purposively selected based on the high concentration of registered young catfish farmers in the area. The second stage involved a simple random sampling of 80 farmers from the list of registered catfish farmers got from Oyo State Agricultural Development Programme (OYSADEP), Ibadan. Primary data were collected through the use of structured questionnaire and personal interviews. Arrays of information were collected on the socio-economic characteristics of the young fish farmers, the inputs and output of catfish production, pond size, method of catfish farming among others in 2017/2018 production year. The data collected were analyzed with Stata package version 12 using descriptive statistics, budgetary analysis and multiple regression analysis model.  The descriptive statistics presented the socio-economic characteristics of the farmers such as farmer’s age, gender distribution, level of education, farm size, and income level, production gap among others

Estimation of Production Gap

Production gap is generally calculated as the percentage deviation from estimated production, that is the difference between the expected and the actual average body weight for catfish reared for the period of six months’ production cycle [11]. This gap can be positive or negative, depending on the actual market weight of realized output in a production cycle. Meanwhile, the expected average body weight for catfish reared for the period of six months’ production cycle is 0.99kg [11]. To estimate the production gap, the difference between actual production and estimated production were obtained. The gap was determined using this simple calculation;

Production gap = AAS - EAS…………………………………. (i)

where;

AAS is the actual average size of catfish reared for a period of six months

EAS is the Expected average size of catfish reared for a period of six months

Budgetary Analysis

Budgetary analysis was used to analyze the net farm income of the catfish enterprise in the study area. The budgetary equation was specified as:

NFI = ∑P_YiY_i – ∑ P_Xj-∑ Fk………………………………………….... (ii)

RPNO = NFI/TC=∑P_YiY_i – ∑ P_Xj- ∑ Fk/(∑ P_Xj-∑ Fk)…………………(iii)

BCR = GM/TC=∑P_YiY_i -∑ P_Xj/(∑ P_Xj-∑ Fk)…………………………(iv)

Where;

NFI = Net Farm Income (₦)/production cycle

RPNO=Return per naira outlay

BCR=Benefit Cost Ratio

P_Yi = Unit price of the output of catfish (₦)

Y_i = Total output of catfish (kg);

P_Yi= Unit price of variable inputs (₦)

X_j = Quantity of variable inputs (where j = 1,2,3……n)

F_k = Cost of fixed inputs (₦) (where k = 1,2,3………n)

∑ = Summation sign

The Study adopted a multiple regression model to predict the values of independent variables. The econometric model on factors determining the profit of fish production was specified implicitly as;

 Y = f(X_i) ……………………………………………………………………………. (v)

Three functional forms forms-linear, semi-logarithm and double log-regression models were fitted to the models and the best fit was selected. The explicit equation is given as:

Linear; Y₁ = b₀ + b₁ X₂ + b₂ X₃ + ……………...... + b_i X₁₀ + e_i ……………………...  (vi)

Semi – logarithm; Y_i = b₀ + b₁ln X₁ + b₂ lnX₂ + … + b_ilnX₁₀+ lne_i ……...................  (vii)

Double-log (Cobb-Douglas); lnY_i = lnb₀ + b₁ lnX₁ + b₂ lnX₂+…+ b_ilnX₁₀+ lne_i …... (viii)

Where:

Y = Net income (₦)

X_i =1,2,3…10

X₁ = Fingerlings X₅ = Pond size (m²),  X₂ = Experience (Years); X₃ = Marital Status (Married = 1 single = 0); X₄ = Cost of feed (₦); X₆ = Membership of cooperative (member =1, non-member = 0); X₇ = Years of formal education; X₈ = Household size; X₉ = Age of Catfish producers (years); X₁₀= Production gap; and e = Stochastic error term.
Results and Discussions

Socio-Economic Characteristics of the Young Catfish Producers

Table 1 summarized the socioeconomic characteristics of Catfish producers. The result shows that the average age of the Catfish producers was 36.65±9.74 years. This result further confirmed the age categories of the respondents that majority of the young catfish producers are in their active age which might have positive effect on their attitude to risk taking and decision making. The gender distribution revealed that catfish production is dominated by male (92.50%). This implies that female youths are yet to get involved in catfish farming. This result agreed with Oluwasola and Ige [21]. The result also showed that 72.50% of the respondents were married and have average family size of 4.72±1.75. In terms of years of formal education, the result on table 1 shows that average catfish farmer spent 15.4±4.57 years schooling. This further shows that educated youth are gaining interest in catfish farming which can be a boost for the development of the sector’s value chain.  Similarly, average years of experience of respondent was 5.57±5.24 years, and majority (68.75%) of respondents had between 1-5 years’ production experience. This implies that there are new young entrants in the trade in the recent time, and further proves the increasing involvement of youths in agribusiness as claimed by IITA [9] and YESSO [10]. This finding corroborates the report of FMARD [8] that fish farming is the fastest growing sub-sector in Nigeria.

 

Production Gap

The result of the analysis of the production gap is presented in (Table 2). The Catfish producers with positive production gap, that is, those that had their actual average size equal or more than the expected, represented only 7.50% of the total number of the catfish producers while 92.50% of the catfish producers had their actual output less than the expected output. Average market weight of catfish and production gap were 0.76±0.13kg and 0.23kg respectively. This showed that most of the catfish producers in the study area did not get up to the expected output of catfish production which may invariably have negative impact on the income generated from the enterprise.

 

Budgetary Analysis

Table 3 shows that while the average total variable cost was ₦255,572.93, the average total cost was ₦528,554.21. Cost of feed was the highest and accounted for about 74% of the average total variable cost. The average gross margin of the Catfish producers was ₦702,532.07 and the average net income was ₦429,550.79, which indicates that the respondents (Catfish producers) were able to cover their variable costs components in every production cycle. The benefit cost ratio of 1.81 computed shows that for every ₦1.00 cost incurred on Catfish production enterprise there is a return of ₦1.81. These results substantiate the results of Oluwasola and Ige [21].

 

Effect of Production Gap on Net Income of Young Catfish Production

Table 4 shows the results of multiple regression analysis on effect of production gap on net income in Catfish production and the value of R² was 0.204. This suggests that 20.4% of the variability in the Catfish net income of the respondents is jointly explained by variations in the specified independent variables considered in the model. The result shows that years of experience, age and production gap were the only significant variables affecting net farm income of catfish production. The relationship between the years of experience and net income of the Catfish producers was positive and significant (P<0.10). This implies that one percent increase in years of experience in Catfish production will significantly increase the net income of the Catfish producers by 52 percent. This result could be so because all the respondents are youths, still in their economic useful age category. On the other hand, the age of the catfish producers was negatively related but statistically significant (P<0.05). A percent increase in the age of the catfish producers would yield a corresponding decrease of about 57 percent in net income of catfish farmers. This further validate the findings that young farmers are more effective than old ones, as farmers increase in age, their efficiency declines. Similarly, the production gap in Catfish production was negatively related and statistically significant (P<0.05) to net income of the producers. This shows that 1 percent increase in the production gap will lead to a corresponding decrease of about 28 percent in the net income of catfish producers.

 

Table 5 reveals constraints facing catfish production among the youths. In order of importance relative significant index (RSI, P<0.01): small pond size (0.716); followed by unstable input market price (0.712); then, poor access to credit and land (0.698); inadequate market facilities (0.694); sage of outdated implements (0.688); Pilfering/theft (0.686); and inadequate power supply (0.662).  Table 6 presents the remedies suggested for the identified constraints. In all, 31% opined government input policy is a necessity, followed by provision of low interest loan (28%), then power stability (14%) and reduction in transportation cost (9.0%). It is therefore clear that young catfish farmers in Oyo state have not taken advantage of the various credit and input initiatives of Nigerian governments.

 

 

Conclusion and Recommendations

Catfish enterprise is dominated by formally educated male farmers that are married with medium family size. Although catfish business is highly profitable and have high rate of return on investment, there are still production gaps and vast majority of these farmers produced below the expected average table size weight per production cycle. The study also discovered that production gap, age and years of experience of young farmers affect net income of catfish production. However, the relationship between production gap and net income is negative.

It is the prerogative of government, non-governmental organizations, to therefore provide training on best management practices for the Catfish producers to bridge the gap between the expected and actual output in Catfish production. This can be done by enrolling young farmers in the targeted training programs under NIRSAL.  There is also a need to identify better mediums by which awareness about various government farm intervention can be extended to youths in catfish production. This study also suggests study that will isolate determinant factors production gap in catfish production so as to identify the specific area of training needed by the catfish farmers.

Acknowledgement

The authors are grateful to all the Oyo State Agricultural Development Project (OYSADEP) desk officer who provided the list of registered farmers in the State and also appreciate the cooperation of the sample respondents.

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