A novel 3D insect detection and monitoring system in plants based on deep learning

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Choi N. J., Ku K., Mansoor S., Chung Y. S., Tuan T. T.

FRONTIERS IN PLANT SCIENCE, cilt.14, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 14
  • Basım Tarihi: 2023
  • Doi Numarası: 10.3389/fpls.2023.1236154
  • Dergi Adı: FRONTIERS IN PLANT SCIENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, Directory of Open Access Journals
  • Recep Tayyip Erdoğan Üniversitesi Adresli: Hayır

Özet

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.