Telangana: AI helps yield bumper cotton
What’s it about: State IT department takes up pilot project on AI based pest management for cotton 2,800 villages in Karimnagar, Nagarkurnool, Nalgonda, Khammam, Wanaparthy and Mahabubabad covered AI based solution enabled cotton farmers to identify pest attacks in the early stages and initiate corrective measures accordingly to avoid crop damage Hyderabad: This Kharif season, […]
What’s it about:
- State IT department takes up pilot project on AI based pest management for cotton
- 2,800 villages in Karimnagar, Nagarkurnool, Nalgonda, Khammam, Wanaparthy and Mahabubabad covered
- AI based solution enabled cotton farmers to identify pest attacks in the early stages and initiate corrective measures accordingly to avoid crop damage
Hyderabad: This Kharif season, cotton crops cultivated in the State fetched whopping prices, ranging from Rs 8,800 per quintal to Rs 9,100 per quintal. And, in some places, it even fetched a record Rs 10,000 per quintal.
Not many may know that the State IT Department played a crucial role in improving cotton yield for farmers in many villages. During Kharif 2021, the department conducted an Artificial Intelligence-based pilot project for pest management in cotton in six districts, including Karimnagar, Nagarkurnool, Nalgonda, Khammam, Wanaparthy and Mahabubabad.
Under the project, the department, in partnership with the Wadhwani Institute of AI, deployed AI solution at the field level. Cotton farmers in over 2,800 villages were identified to be included in the project. The AI-based solution enabled cotton farmers to identify pest attacks, particularly Pink Bollworm, in the early stages and initiate corrective measures accordingly to prevent crop damage. All these measures helped farmers in improving the quality of yield and eventually increase their incomes, an official from the Emerging Technologies wing of the department told ‘Telangana Today’.
As part of the project, officials captured images of the plants in various stages including the saplings phase and flowering phase. The images were then scanned in the system to assess any pest infestation, the official explained. Based on symptoms like leaf colour change and stem colour change, the algorithm identifies the pest. Depending on these assessments, agriculture officials suggested pest management or any precautionary measures to the farmers, the official said.
A phase-wise data of images was prepared from a particular village and training camps were conducted by the AEOs to alert farmers on pest attacks in advance. In addition to these, they also conducted soil assessment and guided farmers on improving soil fertility, the official said. Since most of the cotton crop harvest has been completed and the yield sold in the markets, efforts are on to set up a dashboard on the kind of pest attacks and the corrective measures to be taken for particular pests. This would help in maintaining on-hand data and suggestive measures for early intervention of pest management and help the farmers in improving cotton quality, the official added.
– As part of the project, officials captured images of the plants in different stages, including saplings phase, flowering phase, etc
– Based on the symptoms like leaf colour change and stem colour change, the algorithm identifies the pest
– Depending on the assessment, agriculture officials suggest pest management or precautionary measures to farmers
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