AI in Agriculture
Precision Farming and Digital Advisory
Artificial intelligence in agriculture encompasses applications in crop health monitoring (using satellite imagery and sensors), yield prediction, pest and disease detection, precision irrigation, and market price forecasting. India's agriculture sector employs approximately 42% of the workforce but contributes only about 18% of GDP, indicating significant productivity gaps that technology can address. AI-driven advisory systems use machine learning models trained on weather data, soil data, and historical crop performance to generate personalised recommendations.
- India's agriculture sector: ~42% of workforce, ~18% of GDP (2024-25 estimates).
- Total food grain production: 332.3 million tonnes (2023-24 Fourth Advance Estimate).
- Key challenges: fragmented landholdings (average 1.08 hectares per holding), information asymmetry, post-harvest losses (estimated 5-15% for different crops).
- Government digital agriculture initiatives: PM-KISAN (direct benefit transfer), eNAM (electronic national agricultural market), Soil Health Card Scheme.
- IMD provides block-level weather forecasts used in agricultural advisories.
● Tracked since February 16, 2026 · last seen March 06, 2026 · updates as the daily brief publishes
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