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<p>This study seeks to assess farmers’ current knowledge and adoption of available agricultural innovations in their localities. A total of 368 sample households were selected via simple random sampling method and 36 KII through purposive sampling. A mixed-method approach was employed as the research design. Primary data were collected through structured interview schedules and key informant interviews, while the secondary data was mined from online sources. Qualitative data was analyzed using thematic and content analysis, whereas quantitative data was analyzed using descriptive statistics and econometrics model. The result of the study indicates that 47.73, 34.46, and 17.81% of the respondents had low, moderate, and high levels of knowledge of agricultural innovation respectively. The results also revealed that differences in knowledge of agricultural innovation due to their socio-demographic differences. Furthermore, the result showed the immense contribution of the social network of farmers to agricultural knowledge dissemination. Potential interventions to fill the gap are delivering of extension a system that is mission and climate-oriented. Furthermore, the extension system requires development agents with a background in climate-smart agriculture. As a result, it was very recommended that agricultural extension experts receive training in this goal-oriented academic program at a university or college.</p>

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Assessment of Smallholder Farmers’ Level of Knowledge and Adoption of Agricultural Innovations Across Various Categories of Farmers in Central Gondar Zone, Ethiopia

  • 期刊论文

  • 发表日期：

    2025年6月17日

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  • Molla Tadesse Lakew,
  • Jemal Yousuf Hassen,
  • Getachew Shambel Endris,
  • Chanyalew Seyoum Aweke

摘要

This study seeks to assess farmers’ current knowledge and adoption of available agricultural innovations in their localities. A total of 368 sample households were selected via simple random sampling method and 36 KII through purposive sampling. A mixed-method approach was employed as the research design. Primary data were collected through structured interview schedules and key informant interviews, while the secondary data was mined from online sources. Qualitative data was analyzed using thematic and content analysis, whereas quantitative data was analyzed using descriptive statistics and econometrics model. The result of the study indicates that 47.73, 34.46, and 17.81% of the respondents had low, moderate, and high levels of knowledge of agricultural innovation respectively. The results also revealed that differences in knowledge of agricultural innovation due to their socio-demographic differences. Furthermore, the result showed the immense contribution of the social network of farmers to agricultural knowledge dissemination. Potential interventions to fill the gap are delivering of extension a system that is mission and climate-oriented. Furthermore, the extension system requires development agents with a background in climate-smart agriculture. As a result, it was very recommended that agricultural extension experts receive training in this goal-oriented academic program at a university or college.