Factors affecting the adoption of climate-smart agriculture technologies in rice farming systems in Mali, West Africa

Abstract

Rice is a major staple crop in Mali, yet it is very vulnerable to climate change. Climate-Smart Agriculture (CSA) has been proposed as a solution to simultaneously address the challenges of climate change adaptation, mitigation, and food security. However, there is limited understanding of the factors that influence farmers’ decisions to adopt CSA practices in Malian rice farming systems. This study aimed to identify CSA practices in rice farming systems and determine the factors that drive farmers’ adoption. We conducted interviews with 440 rice producers, 70% of which were women, and organized 16 focus group discussions (FGDs), including nine exclusively for women, in the Sikasso region of Mali. Data was collected through interviews, surveys, and FGDs. We conducted surveys using a questionnaire and the FGDs and interviews followed a standardized guide. Descriptive statistics were used to explore the data, and we analyzed the factors influencing the adoption of CSA technologies using a logistic regression model. The findings showed that crop diversification, improved rice varieties, crop rotation, tree planting, micro-doses of organic manure, and micro-doses of mineral fertilizer were highly adopted CSA practices in the study area. Key barriers to the successful adoption of CSA practices included limited input availability, lack of control over technologies, insufficient labor availability, insufficient availability and high cost of seedlings for reforestation, lack of information on developed technologies, and limited land access for women and youth. The adoption of CSA technologies was significantly influenced by social factors such as respondents’ age, education level, experience in rice production systems, gender, marital status, and membership in a rice producer cooperative. The results of this study are valuable for guiding extension services’ approach and implementation to scaling up the adoption of CSA technologies. These findings also underscore the benefit of policies and programs focused on disseminating rice farming system CSA practices.

Keywords

• Food security
• Logistic regression model
• Social factors
• Technologies adoption