Towards Developing an Epidemic Monitoring and Warning System for Diseases and Pests of Hot Peppers in Guizhou, China

文献类型： 外文期刊

第一作者： Liu, Kaige

作者： Liu, Kaige;Chen, Xiaohui;Ding, Zhihuan;Li, Ming;Liu, Kaige;Song, Min;Li, Ming;Liu, Kaige;Mu, Yumei;Xing, Dan

作者机构：

关键词： hot pepper; plant disease forecast model; powdery mildew; anthracnose; decision support system

期刊名称：AGRONOMY-BASEL （ 影响因子：3.949； 五年影响因子：4.117 ）

ISSN：

年卷期： 2022 年 12 卷 5 期

页码：

收录情况： SCI

摘要： Guizhou province is the largest area of hot pepper cultivation and processing in China. However, diseases and pests are major bottlenecks for the sustainable development of the industry. This study proposes a solution that combines intelligent monitoring equipment, a prediction model and decision support system for hot peppers, including a demonstration of the solution in Guizhou province. We scouted hot pepper diseases and pests in Zunyi city, and deployed weather stations and automatic pathogens and pest monitoring equipment. A prediction model was developed to forecast powdery mildew and anthracnose based on long short-term memory, with accuracy of 0.74 and 0.68, respectively. Using big data analysis and an app for pest outbreaks as the front desks, we developed an epidemic monitoring and warning system for hot peppers in Guizhou. The results could effectively serve grass-roots managers, increase productivity, reduce production costs and overall have a high demonstration effect. This concept could be extended to other crops to accelerate the process of agricultural modernization in China.

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