INVESTIGATING CLIMATE SMART AGRICULTURAL PRACTICES IN LIVESTOCK PRODUCTION IN SOKOTO STATE, NIGERIA: AN APPLICATION OF PRINCIPAL COMPONENT ANALYSIS - Ekpa, D.; Akinyemi, M.; Ibrahim, H. I. (FUDMA JOURNAL OF SCIENCES, 2023)
This study sought to investigate the factors influencing the use of climate smart agricultural practices in livestock production in Sokoto State, Nigeria. Multi-stage sampling procedure was used to select 60 respondents for the study. Data analysis was carried out using descriptive statistics, Principal Component Analysis (PCA) and Ordinary Least Square (OLS) regression. The descriptive statistical analysis reveals that the average age of the livestock farmers in Sokoto State was 54 years. Regression results shows that the significant determinants of using climate smart agricultural practices in livestock production were education and communication equipment which were both significant at (p<0.01). This implies that those who had informal education had their indices of climate smart agricultural practices for livestock enterprise being significantly lower by 33.59% when compared with their counterparts with formal education. Farm size was positively significant (p<0.05). This connotes that a unit increase in farm size will lead to corresponding increase in the indices of climate smart agricultural practices by 0.0664 for livestock farmers. The study concludes that livestock farmers were adversely influenced by education.This might be as a result of the predominance of Arabic education in the study area. It is recommended that: Government, Non- Governmental Organizations and farmers’ associations should create a conducive learning environment to encourage the livestock climate smart Practioners to improve on their performance. Policy on informal education should be enriched and developed in the curriculum to meet the livestock climate smart agricultural challenges. Extension delivery system approach should be upgraded to meet the present information.