PROFITABILITY ANALYSIS AND SOCIO-ECONOMIC DETERMINANTS OF MAIZE OUTPUT IN RIJAU LOCAL GOVERNMENT AREA OF NIGER STATE, NIGERIA

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INTRODUCTION
Maize is the seed of a monocot plant, Zea mays belonging to the grass family gramineae. It is a cereals crop that produces grains which can be used as food for human beings as well as livestock. Nigeria is the 14th largest producer of maize in the world (Food and Agricultural Organization [FAO], 2013). It is appraised that 70% of maize farmers are smallscale farmers producing 90% of the total farm output (Cadini & Angelluci, 2013). According to Iken and Amusa (2004), maize crop production in Nigeria has begun as a subsistence production which has progressively risen to commercial production on which numerous agroallied industries exclusively rely on as source of raw materials. Maize is an essential staple food crop produced on a large scale in Nigeria. According to FAO (2013), it is rated as the second most produced crop in Nigeria with an estimated output of 9,180,270 tonnes. Thus, this crop has big impact in the economics of developed and developing countries, with per capita consumption of 40kg/year in Sub-Saharan African countries of which Nigeria is inclusive (Hassan et al., 2014).
Maize has been in the diet of numerous Nigerians for centuries and its production as identified by Fajemisin (1985), originates primarily from three features: first, it can be prepared easily into different forms of meals which accounts for about 65% of the daily total caloric intake of rural people; second, the income realized from the production of maize crop, and third, maize crop has faster biomass recovery and it also prospers in intercropping system (Ezeaku et al., 2002). In line with the three mentioned factors, demand for maize continued to increase in Nigeria with livestock industry consuming more than half of the total maize production annually. Rising demand for maize is also not unconnected with increasing population growth, rapid agro-based and livestock industry growth, and rapid urbanization. Despite this economic importance of the maize crop in Nigeria, its supply to meet the demand of the teeming population is not achieved. Ogundari and Ojo in 2007 postulated that agricultural production in Nigeria is increasing at 2.5% annually while population is estimated to be increasing at 3.2% annually (National Population Commission [NPC], 2006;Hassan et al., 2014;and Ogundari and Ojo, 2007). Thence, this creates demand-supply disparity of food in the country. National requirement for maize is estimated at about 16 million tonnes. With production around 10.3 million tonnes in 2013, supply deficit is about 5.7 million tonnes (National Agricultural Extension Research Liaison Services, Maize Bulletin, 2014).
The demand for maize is on the increase relative to its supply as evidenced from the recurrent rise in its price. This trend has immense implication on the food security condition and economic growth of Nigeria's economy. Several studies have implicated farmers' socioeconomic characteristics among the key factors that influence yield on farmers' fields (Ammani et al., 2016). This study therefore seeks to determine the profitability of maize production in Rijau local government area and the socio-economic variables influencing maize output in the study area.

MATERIALS AND METHODS The Study Area
The study was carried out in Rijau Local Government Area (LGA) of Niger State. It is bordered in the north by Zuru and Fakai Local Government Areas of Kebbi State, in the south by Gulbin-Boka ward of Mariga (Bangi), Magama and Kontagora Local Government Areas (LGAs), and in the east and west by Sakaba, Dirin Daji and Yauri LGAs of Kebbi State. Rijau local government area is made up of 11 wards namely; Rijau Centre, Darangi, Magajiya, Sabon Garin Ushe, Dukku, Dugge, Genu, Bunu, Warrari, and Sahoma-Jama'are wards. The entire region is situated in Northern Guinea Savannah zone of Nigeria, with a population of 230,255 people (Niger State Bureau of Statistics, 2014). It has a land area of 3,432.2km 2 . The headquarters of Rijau Local Government is the town of Rijau, which lies at 11 0 06`N and 5 0 16`E.

Sampling Technique and Sampling Size
A Multi-stage sampling technique was used to collect data from 120 maize farmers. The first stage involved random selection of four (4) wards from the 11 wards of Rijau LGA; the second stage involved the random selection of two (2) farming communities from each of the selected wards, and thirdly the random selection of 15 maize farmers from the selected farming communities in the study area.

Method of Data Collection
The study made use of primary data that was derived by survey research method using a structured questionnaire in collecting relevant data. Information on socio-economic variables such as age, educational level, farm size, access to extension services and membership of cooperative society were collected. Other information collected included the input and output outlined within cost content of the farmers.

Methods of Data Analysis
Descriptive statistics was used to describe the socio-economic characteristics of maize farmers, budgetary technique to determine the profitability of maize production and multiple regression analysis to determine socio-economic variables influencing maize output.
Production simply means the transformation of series of inputs or resources through a particular technology to give an output. According to Jhingan (2003), production was defined as a functional relationship between input and output which shows the degree of changes in output with difference in input during a specified period of time. Production is all economic activities other than consumption. Successful management in agricultural production reckons on appropriate elucidation of revenue and cost profiles of an enterprise. In this elucidation, financial success can be accredited to enterprise of which the profits exceed costs. Whether the accounting profits of enterprise is satisfactory to acknowledge an enterprise as victorious is debatable.
Costs and returns analysis has been greatly utilized by many researchers in determining the profitability of a farm enterprise. In spite of the problems associated with this technique as a basis for profitability appraisal, researchers find it convincing to use. Bernard (2003) identified two major problems of using costs and returns analysis. These include; i. Costs and returns analysis do not depict the relative importance of each of the resources in production. ii. The technique is location bound and specific in pertinence for the reason that money is used as the common unit of measurement and the prevailing price of the estimates (Sadiq et al., 2013). The budgetary technique involves the utilization of net farm income (NFI) and gross margin (GM) in determining the profitability of a farm. The Net farm income is the difference between the total revenue and farm expenditures while gross margin is the difference between gross income and total variable cost and it is used where fixed cost is negligible. Net farm income and return on Naira invested (ROI) was used to determine the profitability of maize production in Rijau LGA.
Following Olukosi and Erhabor (1988); and Lawal et al. (2013), the net farm income was estimated based on per hectare this is expressed as: The multiple regression analysis was used to determine the socio-economic variables influencing maize output. Three functional forms of the ordinary least square (OLS) method namely; Linear, Semi-log, and Cobb-Douglas were fitted to the data collected from the field.
The implicit form of the model was specified as: Y= (X1, X2 The explicit forms of the functional forms of the model are specified as: Y = b0+ b1X1 + b2X2 + b3X3 + b4X4 + b5X5 + b6X6 + et (Linear) … (6) InY = Inb0 + b1InX1 + b2InX2 + b3InX3 + b4InX4+ b5InX5 +b6InX6 +et (Double-log) … (7) Y = Inb0 + b1InX1 + b2InX2 + b3InX3 + b4InX4 + b5InX5+ b6InX6+et (Semi-log) … (8) Table 1 presents the results of socio-economic characteristics of maize farmers. Age is one of the determinants of productivity of labour and of significance particularly when considering the form and nature of farm operations (Abubakar and Sule, 2017). The study reveals that, 80.8% of the respondents are still in their productive age of between 20 to 50 years. This implies that, majority of the respondents in the study area are still energetic and responsive/active to continue maize production. This finding is in line with the result reported by Sadiq et al. (2013) who found that farmers within the age bracket of 19 -49 years are economically active and at their productive stages. It was observed that 19.2% of the respondents are within the age category of 51 years above. The respondent's highest level of education modal class was non-formal education with 34.2%, followed by tertiary 27.5%, secondary 26.7% while primary education was 11.7%. In spite of the substantial difference in number of people enrolment to formal education and non-formal education, still there is the need for extension agents to sensitise rural farmers on the importance of formal education in order to avail them to keen in adoption of new innovation. Similar suggestion was raised in the study carried out by Sadiq et al. (2013) on profitability and production efficiency of small-Scale maize production in Niger State, Nigeria; that extension workers should do more by sensitizing farmers on the importance of formal education.

RESULTS AND DISCUSSION Socio-economic Characteristics of the Respondents
From Table 1, majority of the respondents (80.8%) had farming experience of 1 to 20 years while 19.2% had farming experience that range between 21 and 31 years and above. By implication, this result revealed that maize farmers of the study area have acquired sufficient knowledge in maize production. The modal class for farm size of the respondents was 46.7% that lied between 0.1 -2.0 hectares, while 52.2% of the respondents had farm size of between 2.1 to 6.0 hectares and 4.2% had farm size above 6.1 hectares. This result implies that, maize production in the study area is in the hands of small-scale farmers. According to Ibrahim et al. (2012), size of farm is an important contributor to the quantity and types of technology required. respondents that were not engaged in any non-farm activity, 42.5% were engaged in non-farm activity that earned them income aside from farming. By implication, this result showed that majority of farmers of the study area are not engaged in any form of non-farm activity, thus depend solely on farming to earn income.

Costs and Returns Associated with Maize Production
The derived costs were classified into variables and fixed cost constituents. The variable costs include cost of: seed, herbicide, labour, transportation, and fertilizer, while the fixed costs components include the cost of: oxen, sprayer, cutlass and hoe. These components were depreciated overtime using the straight line depreciation method. Maize production profitability was determined using the estimated average costs and returns analysis depicted in Table 2. The gross margin per hectare earned by the small-scale maize farmers averagely was ₦343,772.5 per hectare. The total variable cost was ₦133,200.5 whereas depreciation on fixed cost was ₦4,246.41. Thus, fixed cost was negligible as such gross margin per hectare was used as indicator for the measurement of maize profitability. The return per Naira invested was estimated at ₦3.47 inferring that for each naira invested ₦2.47 was realised as profit. Hence, maize production in the study area is profitable. It could be observed that the ROI of ₦3.47 was higher when compared with the 1.13, 1.26, and 2.27 reported by Zalkuwi et al. (2010), Awaisu (2015) and Momoh (2016).
Labour constitutes 42.1% of the total cost of production, followed by fertilizer 30.6%, processing 6.1%, storage (bags) 6.1%, seed 4.7%, and agrochemical 4.3% then transportation 2.9%. The study revealed that total variable cost accounts for 96.8% (₦133,200.5) of the total cost of production while depreciation on fixed cost represents 3.1% (₦4,246.41) of the total cost of maize production in the study area. This finding corroborates with the finding of Zalkuwi et al. (2010) who reported that variable cost represents 97% of the total cost of production while depreciation on fixed cost accounts for 3% of the total cost of production.

Regression Results of Socio-Economic Determinants of Maize Output
Three (3) functional forms of ordinary least square were tested; linear, semi-log and double-log. Linear was chosen as the lead equation based on the coefficients of multiple determinants (R 2 ) and the coefficient signs in line with the a priori expectations. In Table 3, the adjusted R-square value of 0.598 indicates that 59.8% of the observed variation in maize production could be attributed to the combined influence of the socio-economic variables included in the regression equation while the remaining 40.2% could be attributed to error and variables not included in the equation. The F-value of 30.492 is statistically significant at 1% probability level which confirms the significance of the model.
It was found that farm size and household size were positive and significant variables which influenced maize output in the study area. This implies that increase in these variables will lead to increase in the level of maize output in the area. This finding agrees with the findings of Ajah and Nmadu (2012) and Lawal and Adigun (2012) that household size and farm size significantly influenced output of the farmers. Note: ***significant at P≤0.01; **significant at P≤0.05

CONCLUSION AND RECOMMENDATIONS
The study revealed that total variable cost accounted for 96.8% (₦133,200.5) of the total cost of production while depreciation on fixed cost represented 3.1% (₦4,246.41) of the total cost of maize production. The gross margin per hectare earned by the small-scale maize farmers averagely per hectare was ₦343,772.5 while the return per Naira invested was estimated at ₦3.47; this infers that for each naira invested ₦3.47 was realised as profit. Hence, maize production in the study area is profitable. The regression analysis revealed that farm size and household size have significant effect on the output of maize in the study area.
It was recommended that effort should be made in providing efficient and accessible extension service system in order to educate farmers on the importance of improved farming practices and adoption of advanced technology. In view of the profitable nature of maize production in the study area, it is recommended that farming inputs such as fertilizer, seeds and herbicide should be made available at subsidized rate in order to encourage farmers to expand production.