Digital Intelligence for Sustainable Agriculture: The Role of Expert Systems in India

Abstract

Agricultural Expert Systems, one of the earliest applications of artificial intelligence in agriculture, have emerged as effective decision support tools by simulating the reasoning capabilities of human experts. These systems integrate a knowledge base, inference engine, user interface, and explanation facility to provide scientific recommendations on crop production, nutrient management, irrigation scheduling, pest and disease diagnosis, weather-based advisories, and farm management. This article reviews the key features, components, and working mechanism of agricultural expert systems, and examines several operational Indian platforms such as EXOWHEM, AGREX, Rice Crop Manager, and Agri Daksh that are currently assisting farmers across major crops. The article also compares expert systems with conventional extension approaches and discusses their contribution to improving decision-making, enhancing knowledge dissemination, and supporting precision agriculture, while acknowledging existing limitations such as connectivity gaps, digital literacy barriers, and the need for continuous knowledge updation. As India advances toward Digital Agriculture and Agriculture 5.0, agricultural expert systems are expected to strengthen extension services, empower farmers with real-time, personalized advisories, and contribute significantly to sustainable and climate-resilient agricultural development.