In a collaborative effort that blends modern agricultural methods with the needs of the farming community, Gangamai Sugar Mill in Maharashtra has become the first private sugar mill in the state to integrate artificial intelligence (AI) and remote sensing technologies into its sugarcane harvesting planning. This move comes through a partnership with Mahindra & Mahindra, a company that has spent the past few years developing and refining AI-driven tools for the agricultural sector.
This collaboration represents more than just an update in machinery or software—it marks a shift in how data is being used to support real-time decisions in farming. By bringing in satellite imagery, multispectral analysis, and predictive models, Gangamai is rethinking how sugarcane fields are assessed, monitored, and managed, not only to improve outcomes for the mill but also to support the livelihoods of the farmers they depend on.
Integrating Technology With Experience
The success of the project stems from a clear and coordinated effort between Mahindra’s tech specialists and Gangamai’s field teams. Together, they focused on applying AI and satellite data to gain a clearer, more timely picture of crop health and maturity.
Mahindra contributed high-resolution satellite imagery and proprietary AI models designed to interpret it. These tools assess factors like the vegetation index, photosynthetic activity, and weather data, all of which play a role in predicting how much sugar a crop will yield. According to Gangamai’s in-house testing, the AI models have been able to forecast sugar recovery rates with up to 95 percent accuracy. These predictions are verified each week in their lab.
This level of precision helps the mill plan harvests more efficiently, reducing waste and optimizing the timing of field operations. Not only does this translate into higher sugar recovery, but it also keeps input costs in check.
Field Monitoring Brings New Benefits to Farmers
While this technology has clear advantages for the mill’s operations, its benefits reach far beyond the factory gates. As part of a pilot program, around 1,500 sugarcane farms were included in satellite-based monitoring for issues such as pest infestations and water stress. The idea was simple: detect problems early enough so that farmers could intervene before yield loss occurred.
The results have been encouraging. Farmers received alerts about pest outbreaks or potential water shortages, often days before these issues became visible to the naked eye. This early warning system gave them the opportunity to respond in time—whether by adjusting irrigation schedules, applying targeted pest control, or consulting with agronomists. For many, this meant preserving crop health and securing a better harvest.
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Results From the 2024–25 Crushing Season
This integration of data and field insight made a noticeable impact during the 2024–25 season. Gangamai Sugar Mill processed over 8.8 lakh metric tons of sugarcane, achieving a sugar recovery rate of more than 10 percent. Compared to previous years, this was a meaningful improvement, attributed largely to more precise harvest timing and better field management.
The adoption of AI-driven planning has enabled Gangamai to schedule harvesting when the sugar content in the cane is at its peak, which is critical for maximizing output. Meanwhile, farmers benefited from reduced guesswork and better alignment with market demands.
Supporting Farmers Beyond Technology
In addition to the tech rollout, Gangamai has continued to invest in farmer engagement and training. They organized a series of awareness programs focused on best practices in cultivation and harvest planning. These sessions also helped farmers understand the implications of improved sugar recovery on their earnings, especially with respect to Fair and Remunerative Price (FRP) payments.
Improved sugar recovery directly influences FRP payouts, since they are partially calculated based on how efficiently sugar is extracted from cane. When recovery improves, farmers stand to gain more for the same volume of produce. By equipping them with both knowledge and tools, Gangamai is ensuring that the shift to more data-informed agriculture is inclusive and beneficial at every level.
A Broader Context for India’s Sugar Sector
Mahindra & Mahindra’s role in this project is part of its longer-term engagement with sugar mills across India. For over four years, the company has been working on developing precision agriculture systems, including those that use spectrometry and AI algorithms to analyze plant characteristics. Their approach involves measuring photosynthetic content and tracking plant maturity, so that harvesting can be timed for the highest sugar yield.
While Gangamai is the first private mill in Maharashtra to formally implement this system, other mills have been observing the results closely. The hope is that as word spreads and outcomes continue to improve, more mills and farmers will feel confident in exploring similar approaches.
The integration of AI and remote sensing into sugarcane farming at Gangamai Sugar Mill marks a thoughtful and carefully executed advancement. It shows that high-tech tools, when introduced with collaboration and support, can work hand-in-hand with traditional farming knowledge.
Rather than replacing the farmer’s intuition or experience, technology here acts as a companion—one that provides additional clarity and a wider view. For now, the focus remains on improving both sugar yield and farmer incomes, but the larger story is about building resilience in an industry that depends heavily on environmental factors and timely action.
As other mills consider adopting similar practices, the work done at Gangamai could serve as a useful reference point—not just for technology’s capabilities, but for how it can be meaningfully applied in partnership with those who work the land.
