DEVELOPMENT OF ADAPTIVE AGRICULTURAL TECHNOLOGIES SUPPORTING SUSTAINABLE PRODUCTION UNDER CHANGING CLIMATIC CONDITIONS

Abstract

Purpose - This study explores the development and implementation of adaptive agricultural technologies aimed at enhancing sustainable agricultural productivity amidst increasingly volatile climatic conditions. The paper emphasizes the integration of precision farming, climate-resilient crop varieties, and decision-support systems to mitigate risks and improve resilience. Design/methodology/approach - The methodology involves a multi-dimensional analysis combining empirical data, a systematic literature review, and case studies of recent technological applications. Primary and secondary data were analyzed using climate modeling tools, GIS-based assessments, and machine learning models to identify effective adaptive interventions. Findings - The research identifies that integrating adaptive technologies, such as AI-based weather prediction tools, drought-resistant seeds, and remote sensing, leads to improved yield stability, reduced resource use, and greater sustainability in production systems. These technologies demonstrated significant improvements in smallholder and commercial farming resilience. Practical implications - The findings provide actionable insights for policymakers, agri-tech developers, and farmers on technology adoption strategies that align with climate adaptation goals. The proposed framework also supports digital infrastructure expansion and data-driven decision-making. Originality/value - This work offers a novel synthesis of climate-smart agricultural technologies and a practical implementation roadmap. It contributes to closing the gap between scientific innovation and on-ground adoption in agricultural systems.