India’s Sugar Cane Farmers Use AI to Predict Weather, Fight Pests and Optimize Harvests
As sugarcane farmers worldwide face increasing challenges from unpredictable weather, pest outbreaks, and rising production costs, India has taken a bold step forward by adopting Artificial Intelligence (AI) and Data-Driven Agriculture to sustainably increase sugarcane yields. This presents a valuable model for Thai farmers to consider.
How AI Helps Sugarcane Farmers Overcome Drought, Pests, and Improve Crop Quality
Mr. Jagtap, a 65-year-old farmer from Maharashtra, India, is among the pioneers using AI to manage his sugarcane fields. He has partnered with the Agricultural Development Trust (ADT) Baramati and Microsoft to apply AI technology to monitor and manage climate, soil, water, and pests effectively.
On Jagtap’s farm, smart weather stations measure wind, rain, temperature, humidity, and sunlight, while soil sensors monitor moisture levels, pH, and essential nutrients like potassium and nitrogen. All this data is automatically sent to Microsoft Azure Data Manager for Agriculture, where it is analyzed along with satellite and drone images, as well as historical farm data.
The results are delivered to farmers via Agripilot.ai, a mobile application providing daily actionable recommendations, such as:
- Whether irrigation is needed.
- Where and how much fertilizer to apply.
- Which areas are at risk of pest outbreaks and need immediate inspection.
Using GPS-based precision, this system helps reduce resource wastage and ensures targeted actions. Agripilot.ai supports multiple languages, including English, Hindi, and local dialects, making it accessible to smallholder farmers.
Boosting Yields, Cutting Costs, and Shortening Crop Cycles
From a pilot trial on a one-acre sugarcane plot, Jagtap reported impressive results:
- Sugarcane stalks grew larger and taller, with weight increasing by 30–40% per stalk.
- Sucrose content increased by 20%, improving the sugar yield for processing.
- Reduced water and fertilizer use due to precise AI recommendations.
- Shortened growing cycle from 18 months to just 12 months, enabling more frequent harvests and income.
This breakthrough was first introduced at the Krushik Farmers’ Festival 2024, attended by over 200,000 farmers, and led to more than 20,000 farmers signing up to adopt AI in sugarcane farming.
AI for Thai Sugarcane: An Opportunity to Embrace
Looking at Thailand’s sugarcane industry, which faces similar issues like drought, flooding, pests, and high production costs, AI offers a powerful solution that should be urgently explored.
AI can increase yields per hectare by analyzing local soil, water, and climate data, allowing farmers to manage each field according to its specific conditions, instead of a one-size-fits-all approach. This helps minimize crop losses and ensures consistent quality from the start.
In terms of cost reduction, AI can precisely recommend the optimal amount of fertilizers and chemicals, cutting unnecessary inputs, reducing costs, and lowering environmental impacts.
For pest and disease management, AI acts as a “smart assistant” analyzing satellite and drone imagery to detect early signs of outbreaks, issue timely warnings, and recommend suitable countermeasures — reducing damage and losses.
AI also helps improve sugarcane quality, by recommending the best harvesting time when sucrose content is at its peak, aligned with factory requirements, maximizing crop value and market competitiveness.
A New Era for Thai Sugarcane Industry
Although Thailand has started adopting smart farming technologies in some cash crops, sugarcane remains a crop in urgent need of modernization to address rising costs, labor shortages, and growing environmental demands.
Developing AI for Thai sugarcane should start with pilot projects led by sugar mills, sugarcane grower associations, government agencies, and research institutions to create models suited to Thailand’s unique climate, soil, and farming practices.
India’s case study proves that AI is no longer a distant future technology but a practical tool available today — to boost farm productivity, reduce costs, and promote sustainable practices.
As Thailand’s sugarcane industry faces global market pressures, stricter production standards, and carbon reduction goals, AI could be the key to empowering “Next-Gen Thai Sugarcane” — competitive, sustainable, and environmentally friendly.
Conclusion
AI in sugarcane farming offers real, actionable solutions to meet the demands of today’s fast-evolving agricultural landscape. Learning from India’s success, Thailand has an opportunity to lead Southeast Asia in modern sugarcane production by embracing AI and smart agriculture.
