Md Maruf Billah , Mohammad Mahmudur Rahman , Santiago Mahimairaja , Alvin Lal , Asadi Srinivasulu , Ravi Naidu
{"title":"Constraints and prospects of adoption of climate smart agriculture interventions: Implication for farm sustainability","authors":"Md Maruf Billah , Mohammad Mahmudur Rahman , Santiago Mahimairaja , Alvin Lal , Asadi Srinivasulu , Ravi Naidu","doi":"10.1016/j.csag.2025.100066","DOIUrl":null,"url":null,"abstract":"<div><div>Climate Smart Agriculture (CSA) is the core of agricultural systems and adoption of CSA interventions plays a vital role in supporting sustainable agricultural development. The study aimed at evaluating the perceived constraints and prospects of adoption of CSA interventions in relation to farm sustainability. The mixed-method research (qualitative and quantitative) was conducted employing focus group discussion, key informant interviews and face-to-face interviews with 390 farm household head using semi-structured questionnaire in Bangladesh during 2024. A positive and significant perception regarding adoption of CSA interventions was perceived among surveyed respondents. The commonly adopted CSA interventions were integrated pest management (88.46 %), high yielding varieties (84.87 %), stress tolerant varieties (80.26 %) and so forth. Among the broad spectrum of problems, institutional constraints (<span><math><mrow><mover><mi>x</mi><mo>¯</mo></mover></mrow></math></span> = 617.2), economic constraints (<span><math><mrow><mover><mi>x</mi><mo>¯</mo></mover></mrow></math></span> = 587.4) and technological constraints (<span><math><mrow><mover><mi>x</mi><mo>¯</mo></mover></mrow></math></span> = 586.6) ranked most severe. However, illiteracy, high cost of innovations, inadequate farmers' organization, lack of modern technologies, and poor access to weather information were identified as acute specific constraints. In contrast, increased farm productivity (87.95 %), ensure food security (83.08 %), and alleviation of poverty (79.74 %) were professed as decidedly potential prospects of CSA interventions. Machine learning evaluation indicates that proximity to office, access to extension services, training exposure, and group membership were the most significant factors prompting adoption of CSA interventions. The study explores the insights of adoption of CSA interventions. The outcomes will assist concerned departments and policymakers to plan and initiate feasible strategies (awareness and motivational programs, subsidy for CSA innovations, and reformation of extension and advisory services) for developing climate smart agricultural system and supporting farm sustainability.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"2 3","pages":"Article 100066"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Climate Smart Agriculture","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950409025000279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Climate Smart Agriculture (CSA) is the core of agricultural systems and adoption of CSA interventions plays a vital role in supporting sustainable agricultural development. The study aimed at evaluating the perceived constraints and prospects of adoption of CSA interventions in relation to farm sustainability. The mixed-method research (qualitative and quantitative) was conducted employing focus group discussion, key informant interviews and face-to-face interviews with 390 farm household head using semi-structured questionnaire in Bangladesh during 2024. A positive and significant perception regarding adoption of CSA interventions was perceived among surveyed respondents. The commonly adopted CSA interventions were integrated pest management (88.46 %), high yielding varieties (84.87 %), stress tolerant varieties (80.26 %) and so forth. Among the broad spectrum of problems, institutional constraints ( = 617.2), economic constraints ( = 587.4) and technological constraints ( = 586.6) ranked most severe. However, illiteracy, high cost of innovations, inadequate farmers' organization, lack of modern technologies, and poor access to weather information were identified as acute specific constraints. In contrast, increased farm productivity (87.95 %), ensure food security (83.08 %), and alleviation of poverty (79.74 %) were professed as decidedly potential prospects of CSA interventions. Machine learning evaluation indicates that proximity to office, access to extension services, training exposure, and group membership were the most significant factors prompting adoption of CSA interventions. The study explores the insights of adoption of CSA interventions. The outcomes will assist concerned departments and policymakers to plan and initiate feasible strategies (awareness and motivational programs, subsidy for CSA innovations, and reformation of extension and advisory services) for developing climate smart agricultural system and supporting farm sustainability.