Detection of Monema flavescens (Lepidoptera: Limacodidae) Cocoons Using Small Unmanned Aircraft System

Current unmanned aircraft system (a.k.a. drone) technology is an effective tool for aerial survey of pests including weeds, plant diseases, and insects. This study was conducted to develop an aerial survey method that can locate cocoons of the oriental moth, Monema flavescens Walker, for precise and...

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Bibliographic Details
Published inJournal of economic entomology Vol. 114; no. 5; pp. 1927 - 1933
Main Authors Park, Yong-Lak, Cho, Jum Rae, Lee, Gwan-Seok, Seo, Bo Yoon
Format Journal Article
LanguageEnglish
Published US Entomological Society of America 01.10.2021
Oxford University Press
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Summary:Current unmanned aircraft system (a.k.a. drone) technology is an effective tool for aerial survey of pests including weeds, plant diseases, and insects. This study was conducted to develop an aerial survey method that can locate cocoons of the oriental moth, Monema flavescens Walker, for precise and accurate detection of the cocoons in winter to prevent defoliation in the subsequent summer. We used a rotary-wing drone for an aerial survey of M. flavescens cocoons on 15 trees at 3–5 m above the tree canopy. We also conducted a conventional ground survey of M. flavescens cocoons on the same trees for two different conditions of cocoons: open (i.e., adult moths already emerged from cocoons) and closed (i.e., adult moths were not emerged yet). A validation census with destructive sampling was conducted to determine the precision and accuracy of the aerial and ground survey methods. The results of this study showed that from the aerial survey with the drone, images of open cocoons differed from those of closed cocoons. We found higher precision and accuracy and lower type I and II error rates for closed cocoons by the aerial survey with the drone than those by the ground survey. No significant relationships of the number of cocoons with tree height and diameter at breast height were found. This is the first study to demonstrate direct detection of insects with an aerial survey by using a drone.
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ISSN:0022-0493
1938-291X
DOI:10.1093/jee/toab060