This study estimated resource-use efficiency and factors influencing maize production in Kuje Area Council, Federal Capital Territory, Nigeria. The specific objectives were to; determine the socioeconomic characteristics of maize farmers; analyse cost and returns associated with maize production; evaluate factors influencing the output of maize production; determine the resource-use efficiency of maize production and identify the constraints faced by farmers in maize production in the study area. Multistage sampling technique was employed to select 60 7sampled maize farmers in the study area. The following tools of analysis were used to achieve the specific objectives of the study. Descriptive statistics; Gross margin analysis; resource-use efficiency and Cobb Douglass production function. The results showed that majority, 75 percent, of the sampled respondents were male while 73.3 percent were married. From the results it can further be deduced that 48.3 percent of the sampled respondents attended secondary school and 31.7 percent attended tertiary institution while the rest stopped at primary school level or did not have any formal education. The results also indicated that about 55 percent of the sampled maize farmers had household size ranges within 6-10. 100 percent of the sampled respondents had no access to credit and 83.4 percent had no access to extension services. From the analysis of cost and returns associated with maize production in the study area, the total revenue (TR) realized on average was N1,269,152.69 and the average total variable cost (TVC) was N188,462.69, the gross margin obtained was N1,080,690. With this result we can say that maize production is profitable in the study area. The results of the resource-use-efficiency revealed that farm size, seed input and labour input were underutilized while fertilizer input and chemical input were over utilized by maize farmers. The results of the Cobb Douglass production function model revealed that the factors influencing total output of maize production in the Study area were farm size (P<0.1), labour (P<0.01), chemical (P<0.01) and Fertilizer P<0.05). The major constraints faced by maize farmers in the study area include; inadequate capital, lack of fertilizer and lack of extension agent. Therefore, the study recommends that maize farmers should be encouraged to join the farmers’ association, and supported with credit facilities. Government should supply inputs like agrochemical, fertilizer and improved seed varieties to maize farmers at a subsidized rate and at appropriate time and extension agents are to guide the farmers in the usage of these inputs while mechanize farming system should be encouraged by providing tractors to replace local farm implements. Good roads are essential in linking maize production areas with available markets around the study area.

The study evaluated the socio-economic characteristics, income inequality and poverty status of female headed cassava farming households in Federal Capital Territory, Nigeria. Primary data were used for the study. A multi-stage sampling technique was used to select a total sample size of three hundred and three (303) households from the two area councils. The data were analyze using descriptive statistics, Foster-Greer-Thorbecke (FGT) poverty index, Gini coefficients, Probit model analysis, and principal components analysis (Factor Analysis). From the results about 59.73% of the female headed cassava farming households were less than 50 years old. 31.35% of the female headed cassava farming household were married. The mean household size was about12.00 persons. The mean annual income was 374, 868 Naira. About 56.77% of the female headed cassava farming household were poor given a poverty line N9, 009.37. In addition, 76% of female headed cassava farming households fell into annual income of below N500, 000 and they control 40% of the market share. The Gini coefficient was calculated to be 0.62. Maximum Likelihood Estimates (MLE) of the Probit Model shows that the coefficients of marital status (P<0.01), educational level (P<0.05), household size (P<0.01), income (P<0.1), and sources of livelihood (P<0.1) were the statistically and significant factors influencing poverty status among the female headed farming households in the study area. The results of the multinomial Logit model analysis show that the factors that statistically and significantly influencing the income inequality of female headed farming households in the study area, were coefficient of marital status (P<0.05), educational level (P<0.10), access to credit(P<0.05), and sources of livelihood (P<0.05) for low income earners. Educational level (P<0.01), access to credit (P<0.10) and farm size (P<0.01), were statistically and significant factors influencing income inequality or income distribution among high income earners among female headed farming households. Trading enterprise, cassava flour/garri processing, and palm/ groundnut oil pressing were major coping strategies employed by the female headed households to against poverty and income inequality. Based on the findings it was concluded that there was high income gap or income inequality among female headed farming households and they were poor. It was recommended that policies that will help create more credit access/programs in terms of loan at low interest rates for women should be implemented at all tiers of government to help mitigate and reduce the poverty among female headed household. Women should also be encouraged to diversify their sources of livelihood this will help them to have a relative equality or balance in their income levels all year round. Facilities should be made accessible to farmers, provision of rice processing equipment should be made available, more effort to empower women should be designed, contract farming and marketing should be encouraged, and information dissemination via communication devices for increased market participation and increased value sold among rice farmers should be a priority to eradicate poverty and improve livelihood.

This study examined the effects of microcredit schemes on rice production among smallholder farmers in Kwali area council Abuja, FCT. A survey research design was employed in the study. A total of 100 respondents were used in the study and they were sampled using a multi-stage sampling technique. Primary data was used for the study, and these were collected using well–structured questionnaires Regression analysis based on Cobb-Douglas model was conducted to check how micro-credit influences productivity. Based on the findings, it was discovered that 60% of the respondents were male, 52% were married with an average household size of 5 persons. Results further revealed that 70% of the respondents had 5-15 years of farming experience, and 45% of the respondents had secondary education. The main source of credit accessed by the smallholder farmers is the cooperative society. The study revealed as follows; educational level, household size, farming experience and access to credit were the significant variables that increased rice production among smallholder farmers. This study recommends that commercial banks should ensure that agricultural loan is giving priority, especially to smallholder farmers, as this will enhance the increase in quantity and quality of rice production.

This study focused on evaluation of maize farmers’ attitude towards risk management and preference for crop insurance in Nigeria. Multi-stage method of sampling was used. One hundred (100) maize producers were sampled and selected. Primary sources of data were used for this study and the data were collected through the use of well-structured and well-designed questionnaire. Econometrics and statistical tools employed were used for data analysis. The results obtained show that 51% of maize farmers were risk averse, 21% were risk preferring, and 28% were risk neutral. Age, gender, and education level were statistically and significant predictors influencing risk averse attitudes of maize farmers. Age, farm size, household size, gender, risk aversion, education level, and access to agricultural extension services were the statistically and significant predictors influencing preference of maize farmers for crop insurance policy. Garrett index ranking technique employed for risk management strategies and crop insurance policy adopted by maize farmers show that crop diversification was ranked 1st, weather information was ranked 2nd, crop insurance was ranked 3rd, and off-farm activities was ranked 4th respectively. The results of constraints faced by maize producers revealed that lack of extension services was ranked 1st, lack of credit facilities was ranked 2nd, inadequate knowledge of agricultural insurance was ranked 3rd, high premium of agricultural insurance was ranked 4th, while lack of fertilizer was ranked 5th respectively. The constraints retained explained 74.85% of all constraints in the analysis. The study recommends that extension officers should be employed to disseminate research results, innovations and information on risk management strategies and crop insurance to maize farmers. Weather information should be made available to maize farmers, and credit facilities at low interest rate should be provided to maize farmers. Bureaucratic process and cumbersome administrative procedures in accessing credit facilities should be removed.