INTRODUCTION Groundnut

INTRODUCTION
Groundnut (Arachis hypogea) is the 13th most important food crop of the world (FAO, 2011). It is the world 4th most important source of vegetable protein. Groundnut seeds contain high quality edible oil (50%) easily digestible protein (25%) and carbohydrate (20%) groundnut is grown in nearly 100 countries with China, India, Nigeria, USA and Indonesia and Sudan’s major producers (National Peanut Council, 2006). Before the world war Nigeria’s groundnut expert figured prominently in world trade, accounting for 29% of Africa’s expert and 12% of the world expert in the 1950’s world expert. In the early 70’s, Nigeria accounted for 41% of the total groundnut production in West Africa (Adesinmi 2003). The role of Agriculture in providing food and cash crop security, thereby reducing poverty cannot be over emphasized. It is in this light that Nigeria’s agricultural policy focused on developing a progressive, dynamic and viable agricultural economy that would ensure food security, income growth and hence pov erty reduction as well as promoting sustainable agriculture and a thriving agric business sector (NAERLS, 2011). It is estimated that over 90% of the farm holders in Nigeria are small scale; similarly most of these farmers produce are subsistence basis and thus, face cash insecurity problems. It is in the light of this that many people believe that the production of cash crops such as groundnut is way out at such cash insecurity. Groundnut is cultivated in both tropical and sub-tropical countries. FAO (2011) estimated that Nigeria’s cultivated area under groundnut cultivation is about 1.0-2.5million hectares annually and yield in the range of 500-3000kg/ha. It was repented that seed yield in northern Nigeria’s is about 3000kg/ha developing countries account for 92% and 96% of global output and production area respectively (FAO 2011).
PROBLEM STATEMENT
Groundnut believed to be the most popular and widely cultivated legume in Nigeria because of its adaptation to varied climatic conditions. Groundnut production in northern Nigeria is very pronounced and about 92% of the national production comes from northern Nigeria (Girei et.al. 2013). However, NAERLS (2011) laments that groundnut yield in Nigeria has generally been poor due to a combination of factors including unreliable rain, little technology available to small-scale farmers, poor seed varieties and increased non-supportive small farm policies which have negatively impacted on groundnut production while some of these factors are outside the control of the farmers, other are within their control. Despite numerous crop improvement practices and vast resources of land and labour as reported by national peanut council (national peanut council, 2006).There seem to be inadequate supply of groundnut to meet the demand of the teeming population. Groundnut is mainly under taken by small holder farmers at subsistence level of production, using traditional methods and employing low yielding variety with low yields per hectare (Girei et.al. 2013). This decline in groundnut production has also been attributed to the discovery of petroleum in Nigeria, groundnut rosette epidemic, drought and lack of organized inputs and inadequate structures marketing. It is important to find out the extent to which the latter influence the efficiency levels of the farmers so that specific policies may be designed to step up the production of groundnut in the study area.
OBJECTIVES OF THE STUDY
The broad objective of the study is to analyze the profitability and determinants of groundnut production in Dambatta local government area of Kano State, while the specific objectives are to;
i) estimate the profitability of groundnut production;
ii) determine the input and output relationship of groundnut production; and
iii) identify the constraints of groundnut production in the study area.
HYPOTHESIS
Ho: There is no input and output relationship in groundnut production.

JUSTIFICATION
Groundnut used to be a very important foreign exchange earner for Nigeria prior to the oil boom of the 1970s. It was the groundnut sub-sector that established the basis for the industrial development of the country and improved rural economies. More than 2 million hectares are planted to groundnuts annually producing variable pod yields ranging from 800-3500 kg/ha (FAO, 2011). However, groundnut production in Nigeria drastically declined due to several factors. The persistent declines in groundnut production over several decades has generated great concern of the Nigerian government which has resulted in the evaluation of various means of revitalizing the production through research for improved yields, yet there still seems to be inadequate supply of groundnut to meet the demand of the teeming population (NAERLS, 2005). Groundnut is mainly under taken by small holder farmers at subsistence level of production, using traditional methods and employing low yielding variety with low yields per hectare (Taru et al. 2010). There is therefore a serious need to reverse this negative trend, with a view to improving groundnut production. Some analysts argue that realizing the above objectives of increasing food supply and incomes, hinges on the improvement of farmer’s efficiency, while also depending on improving the existing resource base and available technology (Awoke, 2003). It against this backdrop that we seek, in this study to find out the determinants of groundnut production by farmers in the study area and also the mitigating factors that affect their productivity.
METHODOLOGY
Dambatta is situated in northern part of Kano State it is enclosed between latitude 12º25’N and longitude o8º3055’E with a land mass of 2732km2. Dambatta local government area is located in Dambatta town just about 40km north east of Kano metropolis. It has a population of 207,968 and expansion rate of 6.2 -percent per-annum (NPC, 2006). It has a land mass area of 305.51km2. Humidity at times rise up to 100º percent with a daily maximum and minimum temperature of 33.1°C and 15.85ºC respectively. Rainfall varies considerably from year to year ranging between 635mm – 889mm and it reaches its peak from storms followed by tomatoes mainly during the month of May and at the end of the rainy season in September or early October (NAERLS, 2011). Most of the populations are small scale farmers producing food crops like groundnut, millet, sorghum, cowpea and moreover, villages that are located close to the nearby oasis irrigational project engage in production of rice, pepper, onions, tomatoes and wheat. In addition, they are livestock, goats, sheep and poultry.
SAMPLING TECHNIQUE
Multi-stage sampling technique was employed in the drawing of samples for the study. The first stage involved the systematic random selection of four districts in the study area out of ten (10), which included Dambatta yamma, Dambatta Gabas, Ajumawa and Gwarabjawa and the final stage involved the random selection of 20 groundnut famers in each of the selected districts giving a sample size of 80 respondents from the sample frame provided by Agricultural Development Project (ADP) and Groundnut co-operative farmers association in the study area.
METHOD OF DATA COLLECTION
A well-structured questionnaire designed in line with the objectives of the study was used for the collection of data. The data collected for this study were obtained from primary sources. The primary data will be collected for this research through scheduled interviews and observations, using a well-structured questionnaire. A total of 80 questionnaires were administered to the respondents, which were all retrieved and found to be valid enough for further analysis, giving a response rate of 100%.
METHOD OF DATA ANALYSIS
Analytical techniques such as, farm budgeting tools (gross margin, net farm income and profitability ratios) were used to analyze objective i. Multiple regression analysis was used to determine the effects of the variable inputs on the output of groundnut; this was used in analyzing objective ii. Descriptive statistics (frequency distribution and percentages) were used to analyze objective iii. Thus, combinations of statistical, budgetary and parametric techniques were used in the analysis of data collected.
FARM BUDGETING (PROFITABILTY) ANALYSIS
The budgetary techniques used were gross margin analysis and net farm income per hectare of farmland at various scales of operation, as adapted by (Akinpele and Ogbonna, 2005) to analyzed objective i, explicitly the farm budgeting model used is expressed as follows:
G.M=TR-TVC ….. (1)
Where; G.M = gross margin, T.R=total returns, T.V.C=total variable costs
Also, N.F.I = G.M-TFC ….. (2)
Where; N.F.I = net farm income, GM=gross margin, TFC=total fixed cost
Total Cost (TC) = TVC+TFC ….. (3)
Where; TC = total cost, TVC=total variable cost, TFC=total fixed cost
TR = Total Revenue (N)
TR = PY.YI ….. (4)
TC = Total cost (N)
TC = TVC + TFC ….. (5)
TVC = Total variable cost (N)
TVC = PX. XI ….. (600)
PY = unit price of output produced (N)
PX = unit price of variable inputs (kg/liter)
YI = quantity of output (kg)
XI = quantity of Ith input (kg/lt)
TFC =land rent, depreciation cost of assets (N).
To determine the financial success of groundnut production the Benefit-cost, fixed and operating ratios were calculated. They are presented as follows:
B-C = TR/TC ….. (7)
Where; B-C = Benefit cost ratio, TR = Total returns, TC = Total cost
F.R=TFC/TR ….. (8)
Where; F.R=fixed ratio, TFC=total fixed cost, TR=total return
O.R=TVC/TR ….. (9)
Where; O.R=operating ratio, TVC=total variable cost, TR=total return
REGRESSION ANALYSIS
Data were also analyzed with the use of multiple regression analysis to estimate the input and output relationship in groundnut production. Four different functional forms (linear, semi-log, double log and exponential functional forms) were fitted to the data. The double-log function gave the best fit and was chosen as the lead equation on the basis of the number of significant variables, magnitude of the coefficients, statistical and econometric criteria and was used to analyze objective ii. The model in its explicit form is stated as follows:
Log Y = b0+b1logX1 + b2logX2 + b3logX3 + b4logX4 + b5logX5+ b6logX6+ei ….. (10)
Where;
Y = Groundnut output/yield (kg/ha)
×1= Farm size; land area allocated to groundnut production (ha)
×2 = Quantity of groundnut seed used (kg/ha)
×3 = Quantity of fertilizer used (kg/ha)
×4 = Quantity of labour used (man-days/ha)
×5 = Quantity of agrochemicals used (lt/ha)
×6 = Access to agricultural credit (1=yes, 0=no)
b0 = Intercept term showing the value of Y when ×1, ×2, ×3, ×4, ×5,×6 are zero.
The a priori expectation is that X1-X6 will have a positive effect on production

RESULTS
Table 1: Profitability (costs and return) analysis for groundnut production (N/ha)
Variables Amount (N/ha) Percentage (%)
(A) Variable cost
(i) Labour 16,200 27
(ii) Seed 2,400 4
(iii) Fertilizer 18,400 30
(iv) Agro-chemicals 8,400 14
(v) Organic manure 3,200 5.3
(B) Total Variable cost 48,600
(C) Fixed cost
(vi) Farmland rent
(vii) Depreciation cost of farm assets 7,500
4,500 12.4
7.3

(D) Total fixed cost 12,000
(E) Total cost (TC)
(TVC + TFC) 60,600 100
(F) Total return 120,000
(G) Gross margin (TR –TVC) 71,400
(H) Net farm income (GM –TFC)
(I) Profitability ratios: 59,400
(i)Benefit-cost ratio (TR?TC)
(ii)Fixed ratio(TFC/TR)
(iii)Operating ratio(TVC/TR) 1.98
0.1
0.41

Source: Onuwa et al. (2017).

Table 2: Estimated Regression (Double log production function) analysis for Groundnut production
Variable Coefficient Standard error T-ratio
Constant 3.212** 1.369 2.346
Farm size(X1) 0.348*** 0.130 2.676
Labour(X2) 0.205* 0.114 1.798
Seed(X3) -0.322* 0.177 -1.819
Fertilizer(X4) 0.561** 0.252 2.226
Herbicides(X5)
Credit(X6)
R2
F Ratio
0.217*
0.436***
0.739
6.912***
0.132
0.152 1.644
2.868
***= significant at (p