ASSESSING ADOPTION LEVEL OF CLIMATE SMART AGRICULTURAL PRACTICES AND TECHNOLOGIES AND THEIR CONTRIBUTION TO FOOD SECURITY OF SMALLHOLDER FARMERS IN ARTUMA-FURSI WOREDA, OROMO-SPECIAL ZONE OF AMHARA REGION, ETHIOPIA

Climate-Smart Agriculture (CSA) is a new agricultural approach designed to improve resilience and food security of farmers in the face of climate change. The study was thus intended to assess CSA adoption level and its contribution to food security of farmers in Artuma-Fursi Woreda, Oromo Zone of Amhara Region, Ethiopia. Two-stage sampling was used to select 259 households, from whom primary data were collected via cross sectional household survey. Content analysis was used to identify farm level CSA Practices/Technologies (CSAPTs) with close examination of locally specific character of climate-induced food insecurity. Adaptation Strategy Use Index and Composite Score Method were used to assess CSA adoption level and classify households as Low/L, Medium/M and High/H adoption groups (AG). Household Food Balance Model (HFBM) was used to assess food security of households. An ordered Probit regression model was applied to assess factors influencing adoption level of CSAPTs. The study identified 30 CSAPTs. Results showed that Crop and Livestock Management were most frequently adopted, while the later 2 were least frequently adopted CSAPTs. Results also indicated that 22.8%, 32.8% and 44.4% of the households fall under HAG, MAG and LAG with a mean dietary energy scores of 1946.0, 1785.82 and 1692.84kcals/household/day. Results of the one-way between-groups ANOVA showed that the observed differences in mean dietary energy scores of the three adoption groups were larger than what would be expected by chance with p < 05 significant level. HFBM showed that 49.2% of HAG were in acceptable consumption category, in which only 4.7% of low adopters were found. On contrary, 64.7% of LAG were in poor consumption category, in which only 13.56% of high adopters were found, implying that increased level of CSA adoption had higher contribution to improve households’ food security. Results of the ordered probit model indicated that membership in SACCOs, livestock ownership and education level of household head were significant explanatory variables determining CSA adoption level in LAG, MAG and HAG at 1%, 5% & 10% significant levels, respectively. Marginal effects estimated for the rest of variables were negatively related in LAG, while they were positively related in HAG, implying that increases in these variables make it less likely to find households in LAG and more likely to boost adoption in HAG showing potential entry points for future intervention.