AUTHOR=Choi Nak Jung , Ku Kibon , Mansoor Sheikh , Chung Yong Suk , Tuan Thai Thanh TITLE=A novel 3D insect detection and monitoring system in plants based on deep learning JOURNAL=Frontiers in Plant Science VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2023.1236154 DOI=10.3389/fpls.2023.1236154 ISSN=1664-462X ABSTRACT=

Insects can have a significant impact on biodiversity, ecology, and the economy. Certain insects, such as aphids, caterpillars, and beetles, feed on plant tissues, including leaves, stems, and fruits. They can cause direct damage by chewing on the plant parts, resulting in holes, defoliation, or stunted growth. This can weaken the plant and affect its overall health and productivity. Therefore, the aim of this research was to develop a model system that can identify insects and track their behavior, movement, size, and habits. We successfully built a 3D monitoring system that can track insects over time, facilitating the exploration of their habits and interactions with plants and crops. This technique can assist researchers in comprehending insect behavior and ecology, and it can be beneficial for further research in these areas.