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This study presents a machine learning-based method for evaluating pest damage in broccoli seedlings by analyzing images to identify wormholes. The algorithm calculates the ratio of wormhole areas to leaf areas, achieving a determination coefficient of 0.85 with a low error rate. This approach aims to enhance precision in pesticide application, reducing environmental impact and improving agricultural practices.

Author

as23161pag

Language

EN