
This study examined the socio-economic factors influencing choice of climate change adaptation practices and the effects of these practices on cassava productivity in Nigeria. Using a multi-stage sampling technique, structured questionnaire was used to survey 100 cassava farmers. The result was analyzed with a multivariate probit and generalized linear regression models. The result showed male dominance (78%) in cassava farming and the mean age of the cassava farmers was 45.46 ± 9.36 years. About 66% of the farmers belonged to cooperative associations and 67% had access to credit facilities. The multivariate model revealed that age of farmers, gender, education qualification, primary occupation, total income, membership of cooperative associations, farming objectives, farming experience, access to extension visit, access to credit, type of land ownership, farm size and climatic conditions significantly influenced choice of climate change adaptation practices among cassava farmers. The generalized linear model identified farming system, multiple crop types/improved crop varieties used, crop diversification, organic manuring, multiple planting dates, use of alternate fallowing, education and credit access to significantly affect cassava productivity. The study concluded that, eco-friendly methods for adapting to climate change increase cassava productivity. Thus, cassava farmers should be trained on the use of best climate change adaptation practices that can boost cassava productivity. In order to practice climate smart farming, it is important to stress the usage of organic manure and alternate fallowing.
H1-99, Science (General), CSA, Random utility theory, Social sciences (General), Discrete choice model, Q1-390, Multivariate analysis, MVP, GLM, Research Article
H1-99, Science (General), CSA, Random utility theory, Social sciences (General), Discrete choice model, Q1-390, Multivariate analysis, MVP, GLM, Research Article
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 20 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
