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A novel 3D insect detection and monitoring system in plants based on deep learning
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 stu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502161/ https://www.ncbi.nlm.nih.gov/pubmed/37719226 http://dx.doi.org/10.3389/fpls.2023.1236154 |
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author | Choi, Nak Jung Ku, Kibon Mansoor, Sheikh Chung, Yong Suk Tuan, Thai Thanh |
author_facet | Choi, Nak Jung Ku, Kibon Mansoor, Sheikh Chung, Yong Suk Tuan, Thai Thanh |
author_sort | Choi, Nak Jung |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10502161 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105021612023-09-16 A novel 3D insect detection and monitoring system in plants based on deep learning Choi, Nak Jung Ku, Kibon Mansoor, Sheikh Chung, Yong Suk Tuan, Thai Thanh Front Plant Sci Plant Science 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. Frontiers Media S.A. 2023-08-31 /pmc/articles/PMC10502161/ /pubmed/37719226 http://dx.doi.org/10.3389/fpls.2023.1236154 Text en Copyright © 2023 Choi, Ku, Mansoor, Chung and Tuan https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Choi, Nak Jung Ku, Kibon Mansoor, Sheikh Chung, Yong Suk Tuan, Thai Thanh A novel 3D insect detection and monitoring system in plants based on deep learning |
title | A novel 3D insect detection and monitoring system in plants based on deep learning |
title_full | A novel 3D insect detection and monitoring system in plants based on deep learning |
title_fullStr | A novel 3D insect detection and monitoring system in plants based on deep learning |
title_full_unstemmed | A novel 3D insect detection and monitoring system in plants based on deep learning |
title_short | A novel 3D insect detection and monitoring system in plants based on deep learning |
title_sort | novel 3d insect detection and monitoring system in plants based on deep learning |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502161/ https://www.ncbi.nlm.nih.gov/pubmed/37719226 http://dx.doi.org/10.3389/fpls.2023.1236154 |
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