Future Farming in India 2025

the blanket use of fertilizers, sometimes with the notion that “more is good”. In contrast, AI-enabled rapid soil analysis uses spectroscopy to study soil characteristics such as composition, nutrient availability, water retention capability and alkalinity. Rapid and on-site soil monitoring provides instant feedback on nutrient levels, moisture and soil acidity, helping to prevent the overuse of chemical inputs. Testing can also help optimize fertilizer use and provide crop rotation guidance to restore soil fertility.Enabling datasets The government must establish a centralized database that consolidates soil-health data from various sources and makes it accessible to researchers, policy-makers and digital start-ups aiming to develop AI-driven applications. Creating such foundational datasets will significantly accelerate the development and deployment of effective AI models in agriculture. Transforming soil-health analysis and management using AI FIGURE 5 Today, nearly 30% of India’s soil is degraded, posing significant challenges to agricultural productivity.Farmers struggle to know the exact nutrient needs of their soil. They often follow general soil-nutrient recommendations that ignore specific needs, leading to nutrient imbalances, environmental harm, higher cultivation costs and lower incomes.The absence of incentives for sustainable soil management discourages farmers from adopting regenerative practices, leaving soil health to decline and threatening future food security. Vision 2030AI-enabled rapid soil-health analysisCurrent scenario India has significantly reduced agricultural soil degradation by supporting farmers’ efforts to optimize the use of fertilizers and follow regenerative crop planning.Farmers use a spectroscopic device for real-time soil analysis, receiving instant insights into nutrients, organic matter or contaminants. The analysis offers fertilization and crop-rotation plans, helping to lower costs, boost yields and raise income.India has national soil dashboards with real-time soil data. This has been coupled with soil-health credits that reward farmers for replenishing soil health. These have significantly improved the resilience of food systems, while providing additional income to farmers. Farm-level soil data Includes farm-level data on soil profiles (e.g. composition, texture, microbial activity, pH level, organic carbon).Historical soil degradation and erosion data Includes data on changes in soil quality over time at a jurisdictional level.Historic nutrition and water management data Includes historic data on fertilizers and irrigation processes that have been used.Best practices and advisory from research institutions Includes recommendations on cultivation practices/ crop selection for different soil characteristics to generate advisory.Enabling datasets required for rapid soil-health analysis FIGURE 6 Future Farming in India 19