Agricultural Economics
Permanent URI for this communityhttps://repository.ui.edu.ng/handle/123456789/3531
Browse
2 results
Search Results
Item Are Yam Farmers Aware and Willing to Adopt the Aeroponics Farming System in Oyo State, Nigeria?(2021) Adepoju, A. O.; Olaseni, O. C.Despite the immense returns of new agricultural technologies to increase agricultural productivity and meet rising food demand, there is a lag in the adoption of these technologies by farmers. The aeroponics system is one of such innovative technologies implemented for seed yam propagation. This study assessed the awareness and the determinants of the willingness of yam farmers to adopt the aeroponics farming system, employing the likert scale and the logit regression model. Results showed that more than three-fifths of the farmers had never heard of the aeroponics farming system but were willing to adopt it for yam and seed yam propagation, although high cost of capital required for adoption was a major constraint. Key determinants of farmers' awareness of the aeroponics system include gender, age, education, membership of cooperative society, monthly income and access to extension agent, while the main factors influencing its adoption were marital status, age, access to credit, membership of cooperative society, farm size and income. Efforts at dissemination of aeroponics farming system for increased productivity should be intensified for its effective adoption by the farmers.Item Nutritional Vulnerability Transitions among Rural Households in Nigeria(2023) Adepoju, A. O.Aims: It has long been considered that specific age/gender groups, such as women and children, are predisposed to nutritional vulnerability. Thus, nutritional vulnerability among agricultural households is neglected and understudied. This study aims at an empirical assessment of nutritional vulnerability dynamics among rural households in Nigeria. Study Design: Secondary data used for this study was waves 2 and 3 of the general household survey panel data. The sampling design consisted of two stages of sampling: the selection of enumeration areas based on probability proportionate to the size of the enumeration areas and the systematic random selection of ten households from each enumeration area. There were 3370 households selected in rural areas and 1630 households selected in urban areas. 2090 rural households with the required information for this study were included in the analysis. Methodology: Descriptive statistics, nutritional vulnerability score, logit regression model, Markov model, and multinomial logit regression models were used to analyse nutritional vulnerability transitions among rural households in Nigeria. Results: Nutritionally vulnerable households in rural Nigeria include those with aged heads, little or no formal education, limited assets, and no access to land or credit. Nutritional vulnerability in rural Nigeria is primarily transient, with around two-fifths of households experiencing transient nutritional vulnerability and nearly one-third experiencing chronic nutritional vulnerability. While the age of the household head, tertiary education, and access to credit all had a substantial impact on transient nutritional vulnerability, gender, tertiary education, asset value, and access to credit all had an impact on chronic nutritional vulnerability. Conclusion: Support mechanisms such as initiatives to promote access to healthy food, credit, land, and education are critical. To successfully address the issues affecting the nutrition and health of persons facing vulnerabilities, social welfare programs with interventions based on the characteristics of each vulnerable group and the predisposing factors should be adopted.