Object Detection and Optimization Algorithm for Improving Organic Food Production and its Environmental Impact
Autour(s)
- Zheng Xiang, Chang Li, Lee Chen, Bing Pan, Don Chen, Lixuan Zhang
Abstract
Organic food production has gained popularity in recent years due to its perceived health benefits and environmental sustainability. However, organic food production faces several challenges, such as pests and diseases, which can significantly affect crop yields and quality. In this article, we propose an approach that combines object detection techniques and optimization algorithms to improve organic food production and its environmental impact. Our approach uses object detection to identify pests and diseases in crops and optimization algorithms to develop effective strategies for reducing their impact on crop yields and quality. The result is a comprehensive analysis of the impact of organic food production on the environment and strategies for improving its sustainability.