Future Farming in India A Playbook for Scaling Artificial Intelligence in Agriculture 2025

Appendix 4: A repository of AI use cases in agriculture AI use cases in agriculture Crop monitoring and management Use case DescriptionHigh-level flowchart of AI value delivery Start-up examples Satellite-based crop monitoringAI analyses satellite images to monitor crop health and growth patterns and detect issues such as drought stress or nutrient deficiencies. This helps farmers make timely decisions to improve yields and manage resources efficiently. –Satellites capture images of fields –AI analyses images for crop health indicators –AI identifies areas needing attention –Farmers receive easy-to-understand reports –Farmers adjust practices accordinglySatSure (India): Case study Planet Labs: Agriculture case studies Crop variety selectionAI helps farmers select the best crop varieties for their fields by analysing soil type, climate and historical yield data, leading to better yields and resilience to pests and diseases. –Soil, climate and yield data are gathered –AI evaluates suitable crop varieties –Farmers receive suggestions on the best varieties to plant –Farmers choose varieties based on advice –Improved yields and crop resilienceSatSure (India): Case study AgroStar (India): Successful applications Drone-based field analysisDrones equipped with cameras capture detailed images of crops. AI processes these images to detect pests, diseases or water stress early, enabling precise interventions and reducing crop losses. –Drones fly over fields capturing images –AI analyses images for issues –AI pinpoints problem areas –Maps highlighting issues are sent to farmers –Targeted treatments are applied where neededDJI Agriculture: Solutions Weather forecasting for farmingAI models predict weather patterns to help farmers plan planting, irrigation and harvesting schedules. Accurate forecasts reduce risks associated with adverse weather conditions. –Collect historical weather data and information on current conditions –AI analyses data to predict weather –Provides localized weather forecasts –Farmers receive weather advisories –Farmers plan activities accordinglyIBM’s The Weather Company: Case study Skymet (India): Case studyTABLE 7 Future Farming in India 45