The Indian Sugar and Bioenergy Manufacturers Association (ISMA) has launched a pioneering National AI ML Network Program in collaboration with the Agriculture Development Trust (ADT), Baramati, and agri intelligence platform Map My Crop (MMC). ISMA formalized this partnership through a Memorandum of Understanding (MoU) to promote the use of artificial intelligence and machine learning in sugarcane farming.
By driving data driven decision making in cane cultivation, the program aims to support more efficient and sustainable farm practices across key sugarcane producing states including Uttar Pradesh, Maharashtra, and Karnataka. The initiative will also engage sugar mills, research institutions, and farmer collectives, while field demonstrations and capacity building sessions are planned to accelerate adoption on the ground, as per the statement released by ISMA.
ISMA Leverages Trial Success
As per the statement released by the ISMA, the National AI ML Network Program is based on a project that demonstrated the practical benefits of technology adoption in farming. In 2024, the Agriculture Development Trust, in collaboration with Microsoft and the University of Oxford, conducted a pilot initiative titled “Application of AI, computer vision and machine learning for Game-Changing Improvements in Sugarcane Crop Farming Practices” was started in 2024, involving more than 1,000 sugarcane farmers.
According to ISMA, the outcomes were noticeable with a 40 percent increase in yield, a 35 percent reduction in overall labour costs, 30 percent savings in water usage, improvement in harvest schedule, and lower rate greenhouse gas(GHG) emissions. ISMA has stated that these results reinforce the potential of data driven approaches to address longstanding inadequacies particularly in irrigation, input use and sugracane harvest.
There was a notable reduction in overall expenditure in the ADT led project, ISMA said, adding that precision farming also contributed to lower greenhouse gas (GHG) emissions. As ISMA stated, the new digital initiative is built upon the urgency to raise average sugarcane production above 100 tonnes per hectare and improve overall sugar recovery rates to over 11 percent.
At the heart of this initiative is the Indian farmer. When we talk about increasing productivity, we are ultimately talking about increasing farmer income, ensuring their long-term sustainability, and making agriculture more resilient. This technology-backed network will help farmers take better decisions, use fewer resources, and get better returns per acre.
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ISMA’s Smart Tools
Based on the findings of the project, ISMA’s AI ML Network will launch a suite of advanced tools tailored to the local agro climatic conditions. This will include satellite based soil fertility mapping, remote sensing for detecting pests and diseases in advance, and image based weed identification. As part of ISMAs’ focus on precision farming, it will also introduce an IoT enabled Variable Rate Application (VRA) of fertilizers aimed at reducing input waste and improving productivity per acre.
The integrated technology stack will also include location specific weather advisories and crop stress monitoring, which will enable timely responses to micro level field conditions. To ensure widespread adoption of the technology, ISMA will make these tools accessible through mobile platforms and farmer friendly interfaces in local languages, that will cater to all the levels of digital literacy. The initiative is being implemented through a coordinated framework involving sugar mills, Krishi Vigyan Kendras, farmer producer organizations (FPOs), and field level agri-extension teams. Demonstration farms, WhatsApp helplines, and training camps are also being set up to engage farmers with the new tools and interpretation of data based recommendations.
ISMA has stated that this initiative is being contemplated to serve as a national model for a digitally driven, sustainable agriculture that will prioritize farmers, strengthening India’s bio-energy value chain, and support the nation’s ambitious agro-based export targets.