2023
DOI: 10.1111/pce.14749
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Deep learning and targeted metabolomics‐based monitoring of chewing insects in tea plants and screening defense compounds

Yifan Chen,
Zhenyu Wang,
Tian Gao
et al.

Abstract: Tea is an important cash crop that is often consumed by chewing pests, resulting in reduced yields and economic losses. It is important to establish a method to quickly identify the degree of damage to tea plants caused by leaf‐eating insects and screen green control compounds. This study was performed through the combination of deep learning and targeted metabolomics, in vitro feeding experiment, enzymic analysis and transient genetic transformation. A small target damage detection model based on YOLOv5 with … Show more

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