The scourge of poverty, including its correlates, has been witnessing an incremental sequence over the years in Nigeria despite the natural endowment of the country. Efforts by various stakeholders to address this problem have not yielded tangible results. Using cross-sectional data collected in 2015 on 775 cassava farmers spread across four geographical zones, this study estimates multidimensional poverty of cassava producers in Nigeria. This is to determine the factors responsible for poverty increase and contribution(s) of these factors to poverty. The study found that about 74% of the respondents were multidimensionally poor. Assets and public/housing utility were the main contributors to aggregate multidimensional poverty index (MPI), while education and health contributed most to povertyreduction. The results also showed major contributing indicators to MPI to be formal employment, school enrolment, years of schooling, frequency of hospital visits, and household assets’ ownership. The South-eastzone of Nigeria had the highest adjusted headcount of poverty among cassava producers. The estimated coefficient of age, farming experience, years of schooling, household size, and access to informal credit were significant determinants of poverty in the study area. In conclusion, the results suggest that although Nigeria is a federation of more than 30 states that continue to rely on nation-wide policy initiatives of the central government, policies on cassava aiming to lift millions of people out of poverty should instead vary according to the peculiar poverty dimensions of each federation unit. We suggest reform in the agriculture sector that will emphasize facilitation and access to incentives (credits, training, extension, cooperate system, etc.) by younger farmers to engage in modern cassava farming, thereby, enhancing the chances of rural cassava growers to move out of poverty.

Food security, at national and household levels, is on the decline because traditional capital (physical, natural, human and financial) has not fully led to its improvement. There is an increasing shift of attention to social capital as an element that explains household food security, but there is a lack of adequately documented information on this. Therefore, this study investigates the effects of social capital on food security, using data collected on a cross-section of 775 cassava farming households from four zones of Nigeria. About 58% of the respondents (cassava farming households) fall under the intermediate category in terms of the benefits received from belonging in social groups. Age and educational level increased the probability to receive benefit from group activities (p < 0.05), while membership density, labor contribution and decision making significantly affected the level of benefit received (p < 0.10). Based on the estimated food security line, 41% of the cassava households were food secure, while 59% were food insecure. Membership density, cash and labor contribution significantly affected food security. Membership density (p < 0.10) and cash contribution (p < 0.05) increased the probability of being food secure. It was recommended that cassava farming households should be encouraged or aided to form cooperatives or farmers’ groups, participate in the activities, and make financial contributions to investments that reduce manual labor-input in the farming activities to enhance household food security.

This study analysed cocoa farmers’ attitude to risk and effects on their income in Ondo State, Nigeria. Multistage sampling technique was used to select a representative sample (234) for this study. Attitudinal Scale Approach (ASA) model, Gross margin and Likert’s scale were used to analysed the data collected. Results showed that the mean age of the respondents was 50.27 years with an average of 15.98 years of experience. The sources of risks perceived by the cocoa farming households as threats to cocoa production were Natural risks (63.68%), social risks (88.89%), economic risks (75.21%), production risk (52.14%) and marketing risks (76.92%). The result of ASA model using Likert’s scale showed that 37.61%, 36.75% and 25.64% of the respondents were respectively categorized as risk averse, neutral and preferring individuals. Results of costs and returns analysis of cocoa farms in the study area indicated that the average farm’s profitability level wasN185,423,725. Regression result showed that the variables that determine farmer’s income included social risks (p<0.001), economic risks (p<0.001) and production risks (p<0.001) and marketing risks (p<0.001). The study concluded that plant diseases, theft of the crop, low market demand, low labour supply and Instability of price among others are the severe types of risks that affect cocoa productivity and all year source of risk to cocoa production in the study area.

Maize consumption is widespread across the country and among households of different wealth. The challenge to increase the efficiency in food production level in Nigeria appears to be more urgent now than it has ever been in the history of the country and in particular, Kajola Local Government area of Oyo State. This study analyzes the technical efficiency and profitability among maize base farmer in Kajola Local Government of Oyo State. A multi-stage sampling technique was used to select 80 maize based farmers in the five villages using well-structured questionnaire. Descriptive statistics, gross margin and stochastic frontier analysis were employed to analyze the data collected. Result showed that the mean age and household size of the respondents were 46 years and 5 respectively. The profitability analysis showed a profit of ₦2711842.6 was recorded. The stochastic analysis revealed that capital, is the most important factors to increase maize productivity. The study concluded that the productivity of the factors could be improved by expanding the capital base, and adequate and timely education through constant training in the latest farming techniques while alternative capital sources through financial capital (savings, funding, remittances etc.) government grants, be available to farmers in other to boost production.

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