Deep learning for automated detection of Drosophila suzukii: potential for UAV-based monitoring

Peter P.J. Roosjen*, Benjamin Kellenberger, Lammert Kooistra, David R. Green, Johannes Fahrentrapp

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

Abstract

BACKGROUND: The fruit fly Drosophila suzukii, or spotted wing drosophila (SWD), is a serious pest worldwide, attacking many soft-skinned fruits. An efficient monitoring system that identifies and counts SWD in crops and their surroundings is therefore essential for integrated pest management (IPM) strategies. Existing methods, such as catching flies in liquid bait traps and counting them manually, are costly, time-consuming and labour-intensive. To overcome these limitations, we studied insect trap monitoring using image-based object detection with deep learning. RESULTS: Based on an image database with 4753 annotated SWD flies, we trained a ResNet-18-based deep convolutional neural network to detect and count SWD, including sex prediction and discrimination. The results show that SWD can be detected with an area under the precision recall curve (AUC) of 0.506 (female) and 0.603 (male) in digital images taken from a static position. For images collected using an unmanned aerial vehicle (UAV), the algorithm detected SWD individuals with an AUC of 0.086 (female) and 0.284 (male). The lower AUC for the aerial imagery was due to lower image quality caused by stabilisation manoeuvres of the UAV during image collection. CONCLUSION: Our results indicate that it is possible to monitor SWD using deep learning and object detection. Moreover, the results demonstrate the potential of UAVs to monitor insect traps, which could be valuable in the development of autonomous insect monitoring systems and IPM.

Original languageEnglish
Pages (from-to)2994-3002
JournalPest Management Science
Volume76
Issue number9
DOIs
Publication statusPublished - 20 Apr 2020

Keywords

  • deep learning
  • Drosophila suzukii
  • integrated pest management (IPM)
  • object detection
  • unmanned aerial vehicle (UAV)

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