This project will later go to Rajasthan and Haryana after the pilot in Punjab turns out to be successful.
AI Pheromone traps for Pink Bollworm PBW attack, farmers' agriculture news: Cotton farmers often face hardship in tackling pink bollworm (PBW) that significantly impacts their income. However, there's news of hope for such farmers as some of them have been chosen for a pilot project by the Central Institute for Cotton Research (CICR) under the Indian Council of Agricultural Research (ICAR). It utilizes cutting-edge artificial intelligence (AI) for real-time pest monitoring.
With the help of AI-powered pheromone traps, the CICR aims to empower farmers with the information that helps in making timely decisions. It is for the first time in India that AI is being used for pest control in any crop.
The pilot program focuses on three major cotton-growing districts in Punjab — Muktsar, Bhatinda, and Mansa, a total of 18 fields, 6 from each district. These districts have been selected for the project. The project has the potential to significantly reduce economic losses for farmers grappling with PBW infestations.
This project will later go to Rajasthan and Haryana after the pilot in Punjab turns out to be successful.
Notably, the PBW (Pectinophora gossypiella) destroys parts of the developing cotton fruit, including the square (flower bud) and the boll (rounded sac of seeds with cotton fibers). In the past, it has posed a threat to the cotton crop and affected the farmers’ livelihoods.
How does the new technology work?
Pheromone traps containing the pheromone gossyplure, a chemical that is taken from female moths to attract male moths, have long been used to reduce crop pests. The farmers install 5 pheromone traps per hectare and then monitor the activity of male moths to determine whether it exceeds the economic threshold level or ETL.
ETL refers to the insect population level or the extent of crop damage at which the crop value exceeds the cost of pest control.
On the other hand, farmers find it difficult to conduct this monitoring regularly, especially when other Kharif crops are to be cultivated simultaneously.
In the new digital approach, farmers will receive hourly crop updates via their mobile phone while a camera fixed in the trap will take regular pictures of the moths that stick to the trap due to the pheromones’ lure. These pictures would be transmitted in real-time to a remote server in the cloud.
The images of insects would be analyzed using a machine learning algorithm, trained to identify and count PBWs caught in traps. Those with a username and password, from ICAR scientists to farmers and agriculture extension officers, will have access to pest alert information in real-time on their mobile phones.
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