Mahindra's AI-tech supports sugarcane harvesting for SM Shankarao Kolhe SSK Ltd
The technology aims to increase sugar content assessment and optimise harvest timing, improving yield and efficiency in sugarcane production.
Mahindra & Mahindra has introduced an AI-enabled sugarcane harvesting program for Sahakar Maharshi Shankarao Kolhe SSK Ltd. (formerly Sanjeevani Sugars) in Ahmednagar, Maharashtra. This technology, used during the 2024 crushing season, aims to improve the accuracy of sugar content assessment for timely harvesting.
The AI-based technology, deployed on over 100,000 acres across Maharashtra, Uttar Pradesh, Tamil Nadu, and Haryana, provides insights into the optimal harvest time for maximising yield and sugar recovery.
Vivek Kolhe, Chairman of Kolhe Sugar Factory, mentioned that the technology, previously piloted on 3,000 acres, has shown improvements in sugar recovery. Based on these results, the mill has expanded the use of AI to its entire catchment area, aiming to benefit the broader sugar industry and farming community in India.
Mahindra's AI-based system employs precision farming techniques, including spectrometry and satellite imaging, to assess sugar content and maturity stages of sugarcane. This approach aims to improve overall efficiency in sugarcane production.
Sugarcane farming plays a crucial role in India's economy as it is a major cash crop and a key contributor to agricultural GDP. It supports the livelihoods of millions of farmers and is integral to the sugar industry, which provides employment and generates revenue.
Sugarcane is also vital for producing sugar, jaggery, and ethanol, contributing to food security, energy needs, and industrial sectors. The crop's widespread cultivation across several states underpins regional economies and supports ancillary industries such as packaging and transportation, highlighting its economic significance.
AI is revolutionising agriculture by enhancing efficiency and productivity through advanced technologies. It enables precision farming by analysing data from sensors, drones, and satellite imagery to optimise crop management, soil health, and irrigation.
AI-driven tools predict weather patterns, monitor pest activity, and suggest optimal planting and harvesting times. These applications help reduce resource waste, increase yields, and improve overall farm management.
By automating tasks and providing actionable insights, AI supports sustainable farming practices and boosts agricultural productivity, addressing challenges like climate change and food security.
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