1. Bridging the gap: challenges and adoption of climate-resilient agriculture technologies in agricultural landscapes across agro-climatic zones of Bihar, India
- Author
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Raj Kumar Jat, Vijay Singh Meena, Shubham Durgude, Ravindra Kumar Sohane, Ratnesh Kumar Jha, Abhay Kumar, Ujjwal Kumar, Anjani Kumar, Raj Narain Singh, Suneel Kumar, Illathur R. Reddy, S. Pazhanisamy, Rakesh Kumar, Sunita Kumari Meena, Ved Prakash, Sanjay Kumar, Anirban Mukherjee, Brijendu Kumar, Umesh Narayan Umesh, Ranjan Kumar Singh, Ravikant Chaubey, Vikash Kumar, Mukesh Kumar, Vinod Kumar, Kumari Sharda, Susheel Singh, Rama Kant Singh, Seema Kumari, Kamleshwari Prasad Singh, Govind Kumar, Ravindra Kumar Tiwari, Vineeta Kashyap, Suneeta Kushwaha, Sripriya Das, Prem Prakash Gautam, Nurnabi Meherul Alam, Shailesh Kumar, Bharati Upadhaya, Sumit Kumar Singh, Sanchita Ghosh, Shubham Bhagat, and Amit Kumar Lenka
- Subjects
climate-resilient agriculture ,minimum tillage ,laser land levelling ,crop diversification ,site-specific nutrient management ,direct seeded rice ,Nutrition. Foods and food supply ,TX341-641 ,Food processing and manufacture ,TP368-456 - Abstract
How effective are climate resilient agricultural technologies (CRATs) in overcoming barriers faced in agri-food system by farmers across the different agro-climatic zones (ACZs) of Bihar? This study examines the barriers that hinder farmers in Bihar from adopting CRATs amidst the growing impacts of climate change on global agri-food systems. It focuses on key CRATs, including zero tillage/minimum tillage (ZT/MT), laser land leveling (LLL), climate-resilient variety selection (CRVS), crop diversification (CD), site-specific nutrient management (SSNM), crop calendar and timely sowing (CCTS), and direct-seeded rice (DSR), and investigates the factors affecting their adoption. Using descriptive statistics, correlation analysis, and logistic regression, key factors that influence the adoption of CRATs were identified. Descriptive statistics showed moderate levels of soil health awareness (mean value = 2.70) and climate change awareness (mean value = 2.63). Correlation analysis found that social factors like training received had a positive correlation with the adoption of DSR (correlation coefficient = 0.410). Logistic regression results highlighted that technology awareness significantly influences the adoption of DSR (coefficient = 0.400, p = 0.253), while initial investment costs are major barriers for ZT/MT and LLL (coefficient = 0.400, p = 0.267). Results highlight the need to improve awareness through educational programs, provide technical support, and offer financial incentives to overcome the various barriers farmers faced. Targeted efforts in these areas can significantly increase the adoption of the CRATs, leading to more resilient and sustainable farming systems. Study supports not only the sustainable agricultural development but also align with the United Nations Sustainable Development Goals (SDGs), particularly SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 13 (Climate Action), and SDG 15 (Life on Land).
- Published
- 2025
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