Mumbai, Aug 21 (PTI) Maharashtra will launch a pilot project using artificial intelligence (AI), satellite technology, drones, IoT sensors and data analytics to boost farm productivity, with 10,000 farmers to be initially selected for the initiative.
During a meeting at the Sahyadri Guest House on Friday, Chief Minister Devendra Fadnavis reviewed a presentation on the project, titled ‘Artificial Intelligence and Digital Twin Learning in Agriculture’, which will cover crops, including cotton, soybean, tur, sugarcane, oranges, turmeric, onion and corn.
The Agriculture Department has been asked to study the project crop-wise and region-wise to develop an integrated digital system using information on crop growth, water requirements, soil moisture, weather conditions, pest and disease outbreaks and likely yields, an official said.
The data should be analysed using machine learning to provide crop-specific and farm-specific advice to cultivators, to increase their incomes, the chief minister said.
The project has been developed by the Agricultural Development Trust, Baramati, to address challenges such as climate change, water scarcity, declining soil fertility, increasing pest and disease attacks and rising input costs, he said.
He directed that the first phase should study selected crops and farmers and, if successful, the model should subsequently be scaled up across the state.
AI-based irrigation management should be used to reduce water consumption and lower cultivation costs, while the model should be developed in a manner that enables it to reach the maximum number of farmers, he said.
Agriculture Minister Dattatray Bharane said the AI and digital twin project could transform the agriculture sector and the government was committed to implementing AI-based farming solutions across Maharashtra.
Agricultural Development Trust CEO Nilesh Nalawade said AI-based farming solutions developed for various crops had shown encouraging results.
In a pilot involving sugarcane, 164 valid records out of 200 farmers showed average production increasing from 65.45 tonnes per acre initially to 73.12 tonnes per acre at the final stage, he said.
AI-based irrigation management resulted in an average 42 per cent water conservation, with the potential to save around 90,000 litres of water per hectare per day, Nalawade said.
He said crop images captured through drones could be analysed using AI and machine learning to detect pests and diseases at an early stage.
Information generated through the system could then be made available directly to farmers on their mobile phones to help them plan irrigation and spraying, he said.
According to Nalawade, more than 10,000 farmers have already reported positive experiences with AI-based farming implementation. PTI MR ARU
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