Abstract
Current research focuses disproportionately on the characteristics of farmers to understand the factors that influence the introduction of climate-smart agriculture (CSA). As a result, there has been a failure to take a holistic view of the range of drivers and barriers to CSA implementation. Many aspects of technologies or practices that may encourage or inhibit the implementation of CSA and define its applicability are, therefore, not systematically considered in the design of interventions. The uptake of any practice should depend on both farmers’ characteristics and factors inherent in the practice itself. This paper, therefore, examines procedures for incorporating the applicability of CSA practices in a farm-level analysis based on the investigations conducted in King Cetshwayo District Municipality (KCDM) of the KwaZulu-Natal (KZN) Province of South Africa. How the farmers perceived the social, technical, economic, and environmental compatibility of the practices constituted the key goal of the inquiry. Data were collected through structured interviews using close-ended questionnaires, from a sample of 327 small-scale farmers (farmers with farm sizes of less than or equal to 5 hectares). The analysis made use of the Acceptance Level Index (ALI) and Composite Score Index (CSI). This paper establishes that, based on social compatibility, the farmers showed high acceptance for cultivation of cover crops (ALI = 574), agroforestry (ALI = 559), and diet improvement for animals (ALI = 554), based on technical compatibility, the use of organic manure (ALI = 545), rotational cropping (ALI = 529), mulching (ALI = 525) and cultivation of cover crops (ALI = 533) were highly accepted. With economic compatibility in perspective, the farmers showed high preference for mulching (ALI = 541), organic manure (ALI = 542) and rotational cropping (ALI = 515), while the use of organic manure (ALI = 524) was highly embraced based on environmental compatibility. Consequently, it is recommended that policies aimed at mainstreaming CSA technologies should pay adequate attention to their applicability in locations under consideration and emphasize the critical role of the provision of information on CSA technologies or practices.
Highlights
There is a rapidly growing interest in climate-smart agriculture (CSA), especially in the developing world as a result of its promising potential to improve food security, climate change resilience, and mitigation of greenhouse gas (GHG) emissions [1]
Given the analysis of the acceptance level index of the practices, the results reveal that the planting of cover crops (ALI = 193) and agroforestry (ALI = 190) had a high level of social acceptance among the farmers in Mthonjaneni Municipality, while agroforestry (ALI = 371), cultivation of cover crops (381) and diet improvement for animals (ALI = 378) had a high level of social acceptance among the farmers in uMhlathuze Municipality
Results from the combined (Mthonjaneni and uMhlathuze Municipality) analysis show a similar result obtained for uMhlathuze Municipality, where agroforestry (ALI = 559), cultivation of cover crops (ALI = 574) and diet improvement for animals (ALI = 554) had a high level of social acceptance among the farmers in King Cetshwayo District Municipality (KCDM)
Summary
There is a rapidly growing interest in climate-smart agriculture (CSA), especially in the developing world as a result of its promising potential to improve food security, climate change resilience, and mitigation of greenhouse gas (GHG) emissions [1]. Climate-smart agriculture is crucial in African countries where the agricultural sector is highly vulnerable to changes in climatic conditions, and agricultural growth plays a significant role in economic development [2]. Mainstreaming CSA depends on institutional instruments, resource tenancy, socioeconomic factors, and climate and ecology setting [4]. These influencers are critical players in the acceptance of CSA practices at the farm-level [4]. Farmers’ decisions on whether and how to adapt agricultural technologies are influenced by the dynamic interaction between the characteristics of the technologies and an array of conditions and circumstances [6]
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