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Discrimination of Hover Fly Species and Sexes by Wing Interference Signals

Li, Meng LU orcid ; Runemark, Anna LU ; Hernandez, Julio ; Rota, Jadranka LU orcid ; Bygebjerg, Rune LU and Brydegaard, Mikkel LU (2023) In Advanced Science
Abstract
Remote automated surveillance of insect abundance and diversity is poised to revolutionize insect decline studies. The study reveals spectral analysis of thin‐film wing interference signals (WISs) can discriminate free‐flying insects beyond what can be accomplished by machine vision. Detectable by photonic sensors, WISs are robust indicators enabling species and sex identification. The first quantitative survey of insect wing thickness and modulation through shortwave‐infrared hyperspectral imaging of 600 wings from 30 hover fly species is presented. Fringy spectral reflectance of WIS can be explained by four optical parameters, including membrane thickness. Using a Naïve Bayes Classifier with five parameters that can be retrieved... (More)
Remote automated surveillance of insect abundance and diversity is poised to revolutionize insect decline studies. The study reveals spectral analysis of thin‐film wing interference signals (WISs) can discriminate free‐flying insects beyond what can be accomplished by machine vision. Detectable by photonic sensors, WISs are robust indicators enabling species and sex identification. The first quantitative survey of insect wing thickness and modulation through shortwave‐infrared hyperspectral imaging of 600 wings from 30 hover fly species is presented. Fringy spectral reflectance of WIS can be explained by four optical parameters, including membrane thickness. Using a Naïve Bayes Classifier with five parameters that can be retrieved remotely, 91% is achieved accuracy in identification of species and sexes. WIS‐based surveillance is therefore a potent tool for remote insect identification and surveillance. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
insect, lidar, WIPs
in
Advanced Science
publisher
John Wiley & Sons Inc.
external identifiers
  • pmid:37847885
  • scopus:85174283831
ISSN
2198-3844
DOI
10.1002/advs.202304657
language
English
LU publication?
yes
id
02191072-ccb5-43c6-be0b-b83eaa0de36d
alternative location
https://onlinelibrary.wiley.com/doi/10.1002/advs.202304657
date added to LUP
2023-10-18 19:15:53
date last changed
2023-12-15 04:02:09
@article{02191072-ccb5-43c6-be0b-b83eaa0de36d,
  abstract     = {{Remote automated surveillance of insect abundance and diversity is poised to revolutionize insect decline studies. The study reveals spectral analysis of thin‐film wing interference signals (WISs) can discriminate free‐flying insects beyond what can be accomplished by machine vision. Detectable by photonic sensors, WISs are robust indicators enabling species and sex identification. The first quantitative survey of insect wing thickness and modulation through shortwave‐infrared hyperspectral imaging of 600 wings from 30 hover fly species is presented. Fringy spectral reflectance of WIS can be explained by four optical parameters, including membrane thickness. Using a Naïve Bayes Classifier with five parameters that can be retrieved remotely, 91% is achieved accuracy in identification of species and sexes. WIS‐based surveillance is therefore a potent tool for remote insect identification and surveillance.}},
  author       = {{Li, Meng and Runemark, Anna and Hernandez, Julio and Rota, Jadranka and Bygebjerg, Rune and Brydegaard, Mikkel}},
  issn         = {{2198-3844}},
  keywords     = {{insect; lidar; WIPs}},
  language     = {{eng}},
  month        = {{10}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Advanced Science}},
  title        = {{Discrimination of Hover Fly Species and Sexes by Wing Interference Signals}},
  url          = {{http://dx.doi.org/10.1002/advs.202304657}},
  doi          = {{10.1002/advs.202304657}},
  year         = {{2023}},
}