According to a study by the Wadhwani Institute for AI, cotton farmers in Maharashtra, Gujarat, and Telangana have seen reductions in pink bollworm damage and improved crop quality by using artificial intelligence (AI)-based pest management applications.
The institute's approach is based on a simple smartphone and offers real-time, localized, and reliable pest advisory that can assist farmers in mitigating pest problems and saving crops. The remedy, which is available in eight Indian languages, makes pesticide recommendations based on the severity of the pink bollworm infestation.
According to Wadhwani AI, the solution, which has been deployed in four districts across three Indian states, has helped cotton farmers boost cotton quality while also saving money. Though India is the world's largest producer and exporter of cotton, more than 75 percent of the country's nearly 6 million cotton farmers are smallholders.
According to the institute, farmers in the three states saw an 11 percent increase in yield and a 20-25 percent increase in income (due to lower pesticide costs and better crop quality) over the previous year. In Kharif 2020, the solution was implemented with nearly 15,000 farmers in Maharashtra, Gujarat, and Telangana, three of India's largest cotton-producing states, in collaboration with the Better Cotton Initiative's Welspun Foundation and Deshpande Foundation.
“The Maharashtra government gave us a problem in 2017-18 when there was a pink bollworm attack that damaged 60-70 percent of the crop. According to Rajesh Jain, senior director of programs at Wadhwani Institute of AI, "this was declared a disaster."
He mentioned that the first year of deployment yielded positive results. “The results indicate a 20-25 percent rise in net profit over the previous year, as well as a decline in the use of pesticides, which saves money and is better for the environment,” Jain said.
The institute's senior product manager, Dhruvin Vora, mentioned that they are looking to scale this up. The products we develop should be simple to use, even for users with limited digital literacy, function well in the context in which they are used, and add value to the farmer and our partners.
“We added features including offline inference, microlearning images, and multi-language support after multiple rounds of usability tests, user & partner interactions. "Now that we have these results, we will look to scale and leverage the product capabilities to tens of millions of farmers over the next few years," Vora said.
You can also fight Pink Bollworm in cotton by following the ICAR-CICR Recommendations.
