PROFITABILITY AND EFFICIENCY OF CUCUMBER PRODUCTION AMONG SMALLHOLDER FARMERS IN OYO STATE , NIGERIA

Cucumber is one of the most important exotic vegetables in Nigeria. Its profile is rising due to widespread knowledge of its inherent health benefits. To sustain the availability of the crop in order to meet increasing demand, there is the need to enhance its productivity. Crop productivity depends on the efficient use of both material and human resources utilized in the production process. This study therefore examined profitability and efficiency of cucumber production in Iseyin local government area of Oyo state. Primary data on socioeconomic characteristics of farmers, input and output quantity and prices were collected from 73 cucumber farmers and analyzed using descriptive statistics, budgetary technique and stochastic frontier. Majority of the farmers were male (96.7%) with average age of 46.4 years. An average of 17.1 years of farming experience cut across both gender groups. The average hectare was 1.5 with average yield of 5,368 kg/ha. Budgetary analysis revealed that net profit of N=239,440/ha, profit margin percentage of 55.8% and returns on every naira invested of 1.26 were obtained. This is an indication that cucumber production is profitable in the study area. The result of the stochastic frontier indicated that farm size and volume of agrochemical used significantly influenced cucumber production. Age, education status of farmers and access to credit were the significant factors determining technical efficiency of the farmers in the study area. Mean technical efficiency of production was 0.68. The study recommends capacity building for farmers on an appropriate combination of resources.


Introduction
Cucumber (Cucumis sativus L.) is one of the most important exotic vegetables in the country.It is the fourth most cultivated vegetable in the world and known to be one of the best foods for body's overall health (Natural News, 2014).It is one of the most popular members of the cucurbitaccae family.Cucumbers are a valuable source of conventional antioxidant nutrients including vitamin C, beta-carotene, and manganese.It is acknowledged that increased agricultural productivity would help in attaining the needed food security.Enhanced productivity is a combination of measures designed to increase the level of farm resources as well as to make efficient use of resources (Adeyemo and Kuhlmann, 2009).Productivity and efficiency of resource use in the production must be sustained in order to benefit maximally from production practices.
Efficiency and productivity are indicators of overall competitiveness (Cechura et al., 2014).The efficiency, with which farmers use available resources and improved technologies, is important in agricultural production (Rahji, 2005).The efficient use of farm resources is an important part of agricultural sustainability (Goni et al., 2013) and a prerequisite for optimum farm production since inefficiency in resource use can distort food availability and security (Etim et al., 2005).An efficiency measurement is important because it leads to substantial resource savings (Bravo-Ureta and Rieger, 1991).Technically efficient production is defined as the maximum quantity of output attainable by a given input (Pitt and Lee, 1981).According to Njeru (2004), technical efficiency is the ability of a firm to maximize output for a given set of resource inputs.
Cucumber can contribute to economic empowerment if efficiently produced due to the high unit price of the commodity compared to local fruit vegetables.Inefficiency in the use of available scarce resources has been the bane of increased food production.There is scarce information on economics and efficiency of cucumber production in Oyo State.Empirical studies on the technical efficiency of vegetables in various regions of Nigeria include those of Oguniyi and Oladejo (2011), Adenuga et al. (2013), Ayinde et al. (2011) and Adeoye et al. (2011).The studies focused on tomato, pumpkin and watermelon.None of the studies examined the economics and determinants of the technical efficiency of cucumber production in Oyo state.This study is therefore carried out to examine the profitability and efficiency of cucumber production in Iseyin local government area of Oyo state.

Area of study
The study was carried out in Iseyin local government area of Oyo State.The local government is one of the 33 local governments in the state.Iseyin (7°58′N 3°36′E ) is approximately 100 kilometers north of Ibadan.The city is estimated to have a population of 236,000.Crops produced in Iseyin include watermelon, cassava, cucumber, pepper and tomato, among others.There are 11 wards in the local government with landmass of 988.54 km 2 (Wikipedia, 2014).Iseyin was selected because it is particularly known for horticultural crop production and a large percentage of the inhabitants are farmers.

Sampling procedure and data collection
A two-stage sampling technique was used in selecting respondents for the study.Iseyin local government area is made up of 11 wards.In the first stage of the sampling, 4 wards were purposively selected due to the intensity of cucumber farming in the wards.In the second stage of the sampling, farmers were randomly selected from each of the selected wards based on probability proportionate to size of each ward to constitute a total number of 73 farmers.Primary data were collected through the use of a pretested questionnaire.Data collected include socioeconomic characteristics of the respondents, input requirement, yield, prices of input and output.

Methods of analysis
This study employed descriptive statistics, costs and returns analysis and stochastic frontier model.Descriptive statistics was carried out using the mean, percentage and frequency.Costs and returns analysis was carried out using the budgetary technique.Indicators such as net income, profit margin percentage and return per naira invested were analyzed:

Stochastic frontier production function
The stochastic frontier production model for the estimation of the technical efficiency is specified as follows: (4) Y = Yield in kg, X i = Vector of input quantities, β is a vector of parameters to be estimated and ei = Error term.The error term consists of two components V i and U i : e i = V i -U i .The components (V i and U i ) are assumed to be independently distributed.V i is the symmetric component and permits random variation of the production function across farms.It also captures factors outside the control of the farmer.A one-sided component (U i >0) reflects the technical efficiency relative to the stochastic frontier.U i = 0 indicates that production lies on the stochastic frontier, while if U i =0, production lies below the frontier and is inefficient.
The technical efficiency of the individual farmers is calculated as: The stochastic production frontier is specified as: The efficiency model is as follows: where: U i = Technical efficiency of the cucumber farmers, Z 1 = Marital status (married = 1, 0 = otherwise), Z 2 = Sex (male = 1, female = 0), Z 3 = Age of farmers (years), Z 4 = Years spent in school (years), Z 5 = Marketing information (yes =1, no = 0), Z 6 = Years of experience in farming, Z 5 = Access to credit (yes=1, no = 0), α i 's = Parameters to be estimated.

Socioeconomic characteristics of cucumber farmers
The socioeconomic characteristics of the cucumber farmers in the study area are presented in Table 1.The results indicate that most of the farmers (96.7%) were male while 3.3 percent were female.This indicates that male dominated cucumber production in the study area.This is in line with the findings of Oyediran et al. (2014) and Tambo and Gbemu (2010), whose findings indicated that men were majorly involved in melon and tomato production in their respective study areas.The results disagree with the findings of Adebisi et al. (2012) and Owombo (2012) that discovered that female farmers dominated food/fruit crop production in south-western Nigeria.The distribution of the farmers by age shows that 50% of cucumber farmers were in the age range of 31-50 years, 38.3% of the farmers were in the age range greater than 50 years while the mean age of farmers was 46.4 years.This is an indication that majority of the farmers in the study area are still in the working age range.Most of cucumber farmers were married and literate.The educational level may improve the level of adoption of new technologies necessary to improve productivity.About 53.3% of the farmers had farming experience of more than 10 years.This implies that cucumber farming is a source of livelihood for the producers in the study area.The results agree with the inference of Nandi et al. (2011) that most farmers in Nigeria have been farming for years.The distribution of farmers by access to credit revealed that 64.4% of the cucumber farmers had benefited from a credit institution while 35.6% had not benefitted from credit institutions and hence relied on their savings.The results show that over half of the cucumber farmers did not have access to market information.

Yield and other explanatory variables
Findings (Table 2) reveal that an average yield of 5,368 kg of cucumber was produced by the farmers with 641g of seeds.An average of 175 kg of fertilizer was utilized by the farmers while the average farm size of 1.5 ha was utilized in the study area.

Costs and returns in cucumber production
The results of the analysis (Table 3) indicate that the total cost estimated for cucumber production in the study area was N=190,000/ha while the total revenue estimated was N=429,440/ha.Labour cost (41.8%)constituted the highest percentage of cost followed by cost on tools and transportation cost (13.16%).The least cost of production was incurred with rent on land (2.63%).The profit margin percent of 55.8% was obtained while the return on naira invested was N=1.26.This is an indication for every naira invested in cucumber production; N=1.26 will be obtained in return.Cucumber production was profitable in the study area since the total cost of production was less than the total revenue obtained.

Factors affecting cucumber production
Table 4 shows the results of the stochastic frontier model of cucumber farmers.The maximum likelihood estimate of the Cobb-Douglas production function shows that the lambda and gamma values were 0.737 and 0.99 respectively and significant at the 1% level.The values were significantly different from zero suggesting that the model was a good fit.The results of the analysis indicate that production factors influencing cucumber production in the study area were farm size and volume of chemical utilized.The coefficient of farm size was positive and statistically significant at the 5% level.This is in line with the findings of Nwachuckwu and Onyenweaku (2007) and Tambo and Gbemu (2010), who indicated a positive relationship between farm size and profit level of farmers in telfairia and tomato production.Thus the capacity of farmers to employ improved techniques should be looked into to ensure the ability to manage bigger farm size.The coefficient of volume of chemical (0.53) was negative and significant at the 1% level indicating that increasing the quantity of chemical by one litre would lead to about 53% percent reduction in the output of the cucumber farmers in the study area.Farmers should therefore be encouraged to use an appropriate dosage of agrochemicals and to adhere strictly to manufacturers' instructions.However, the coefficient of seed and fertilizer was positive and not statistically significant.It therefore suggests that increasing seed rate and improvement in the fertility status of the land may lead to improvement in the yield of the farmers.For inefficiency variables (Table 4), the coefficients of variables relating to age, educational status and access to credit were significant at the 1% level.This is an indication that these factors are important determinants of efficiency in cucumber production.The coefficients of age and education were negative indicating that they may contribute to the technical efficiency in cucumber production in the area.These results are consistent with the findings of Abdulai and Eberlin (2001).An increase in efficiency with age of farmers may also be attributable to the experience they have gained over time especially with regard to combination of resources.The number of years spent in school is a proxy for the literacy level of the farmers.The results show that it was negatively related to the technical efficiency of cucumber farmers.This implies that farmers with better education were technically more efficient.These findings are similar to Dey et al. (2000), who reported the increased farm efficiency with the level of education.The increased level of education may lead to a better evaluation of importance of farming decision making, including the efficient use of inputs.The negative and significant relationship between access to credit and efficiency suggests that farmers who had access to credit for the purchase of inputs experienced higher technical efficiency.The coefficient of sex, marital status, market information and years of experience were not statistically significant.The coefficients of sex of farmers and farming experience were negative while the coefficients of marital status and market information were positive.The positive coefficient of marital status indicates that being married means additional responsibility for the cucumber farmer.Market information was negatively related to efficiency of cucumber farmers in the study area.The negative value of the coefficient of market information is an indication that the farmer with some market information will be more technically efficient in production compared to those with no appreciable information of prices.
Quantity of seed used (kg per hectare), X 3 = Quantity of fertilizer (kg per hectare), X 4 = Volume of chemical (litre), X 5 = Number of labour employed (man-day), In's = Parameters estimated, Ln's = Natural logarithms, Vi = Random error associated with random factor under the control of cucumber farmers, Ui = The asymmetric error component which represents the deviation from the frontier production.

Table 1 .
Socioeconomic characteristics of cucumber farmers.

Table 2 .
Summary of yield and other explanatory variables.

Table 3 .
Costs and returns in cucumber production.

Table 4 .
Stochastic frontier model of cucumber farmers.

Table 5 .
Distribution of technical efficiency indices.