Digital Twin Learning Initiative Targets 10,000 Farmers in Maharashtra

Mumbai, August 21 – Maharashtra has embarked on a cutting‑edge agricultural project that combines artificial intelligence with digital‑twin learning to create virtual replicas of farms. The government will initially roll out the scheme to 10,000 farmers selected from across the state.

The digital twin framework will ingest data from satellite images, drone surveillance, IoT moisture probes and weather stations. By mirroring real‑world field conditions in a virtual environment, researchers can test irrigation schedules, fertilizer regimes and pest‑control strategies before applying them on the ground.

The pilot focuses on eight key crops: cotton, soybean, pigeon pea, sugarcane, orange, turmeric, onion and maize. According to the project brief presented to the chief minister, the Baramati Agricultural Development Trust designed the effort to counteract climate variability, water stress, soil degradation and rising input costs.

Chief Minister Devendra Fadnavis emphasized that the unified digital platform will consolidate multiple data streams, enabling machine‑learning models to generate precise, farm‑specific recommendations. The aim is to reduce input spend, conserve water and boost farm income.

Preliminary outcomes from sugarcane fields are promising. Average yields rose from 65.45 tonnes per acre to 73.12 tonnes per acre – a gain of 17.66 tonnes per acre. AI‑guided irrigation cut water consumption by 42 percent, translating into roughly 90,000 litres saved per hectare each day. AI‑processed drone imagery identified disease outbreaks early, and actionable advice was sent directly to farmers’ mobile devices.

More than 10,000 farmers have already reported improved results, prompting the state to evaluate the model’s performance across different crops and regions before extending it to the entire agricultural landscape.