Decision-Support Systems for Enhancing Yield Stability under Variable Climatic Conditions

Abstract

Climate variability, characterized by droughts, heat waves, and irregular rainfall, has become a major constraint to agricultural productivity, causing yield fluctuations and threatening food security. In response, decision-support systems (DSS) have emerged as essential tools for climate-resilient agriculture by integrating climate data, soil properties, crop models, and management practices to provide timely, site-specific recommendations. DSS supports critical decisions such as sowing time, irrigation, nutrient management, and risk mitigation, thereby improving resource efficiency and reducing vulnerability to climatic uncertainties. The integration of advanced technologies like artificial intelligence, remote sensing, and IoT has further enhanced DSS through real-time monitoring and predictive analytics. By addressing multiple interacting climatic stresses and offering a holistic decision-making framework, DSS plays a vital role in improving crop resilience, yield stability, and sustainable agricultural systems under changing climatic conditions.