Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/3692
Title: Factors affecting the adoption of climate smart agricultural practices among smallholder farmers in Bungoma County, Kenya
Authors: Njuguna, Joyce Wangoi
Keywords: Climate smart
Land security
Issue Date: 2020
Publisher: Moi University
Abstract: Globally, agricultural undertakings are responsible for 14% of global greenhouse gas (GHG) emissions; it is the main driver of deforestation and land degradation, which is responsible for an extra 17% of GHG emissions. Although a better understanding of factors influencing adoption of climate smart agricultural practices is important to inform policies aimed at promoting successful climate change adaptation strategies there is little information on the various practices adopted by smallholders. This study sought to analyse the factors influencing adoption of climate smart agricultural practices in Bungoma, County. It describes how social factors such as age, sex, education, economic factors such farm size and income and institutional factors such as access to extension services and noting of unpredictable temperature influence the adoption of climate smart agricultural practices. The study adopted a descriptive and an explanatory research design. Four practices were considered, soil fertility management, improved crop varieties and livestock breed, agro forestry and water harvesting and management. Theory of planned behaviour and technology acceptance theory guided this study. Based on the 30% rule 3 Sub Counties out of 11 were selected using simple random selection. Secondly, systematic random sampling procedure was employed. A sample size of 228 respondents was interviewed using structured questionnaire. Data collected was analysed using combination of descriptive and inferential statistics. Findings indicated that farm size (0.0293**, p < 0.05) and noticing of unpredictable temperatures (-0.1643*** p < 0.001) had a statistically significant negative influence on the adoption of soil fertility management practices in Bungoma County while income (0.0002**, p < 0.05) had a statistically significant positive influence. Access to extension services (0.0792*** p < 0.001) had a positive statistically significant effect on the adoption of improved crop and livestock breed as an adaption response to climate change and variability. Age (-0.0020* p < 0.05) and unpredictability of temperatures (0.1497***, p < 0.001) had a statistically significant positive influence on the adoption of agro forestry. Sex had a statistically significant positive influence on the adoption of water harvesting and management practices as an adaptation to climate change (0.0922**, p < 0.05). The log likelihood chi square ratio of 64% (63.83) was highly significant implying that the overall model with predictor was preferred. The study recommends that more integration between extension partners should be considered. There is need for better land security since it increases the likelihood of farmers adopting Climate Smart Agriculture. Policies and strategies should place more emphasis on strengthening the existing agricultural extension service, supporting proven technologies such as soil fertility management, improved crop and livestock breed, agro forestry and water harvesting and management. Capacity enhancement is needed for climate smart agricultural practices including access to weather information adapted to farmers’ needs.
URI: http://ir.mu.ac.ke:8080/jspui/handle/123456789/3692
Appears in Collections:School of Agriculture and Natural resources

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