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Towards the automated identification of Chrysomya blow flies from wing images
Author(s) -
Macleod N.,
Hall M. J. R.,
Wardhana A. H.
Publication year - 2018
Publication title -
medical and veterinary entomology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.028
H-Index - 82
eISSN - 1365-2915
pISSN - 0269-283X
DOI - 10.1111/mve.12302
Subject(s) - calliphoridae , biology , forensic entomology , wing , identification (biology) , myiasis , evolutionary biology , zoology , digital image analysis , ecology , computer vision , computer science , larva , engineering , aerospace engineering
Abstract The Old World screwworm fly (OWSF), Chrysomya bezziana (Diptera: Calliphoridae), is an important agent of traumatic myiasis and, as such, a major human and animal health problem. In the implementation of OWSF control operations, it is important to determine the geographical origins of such disease‐causing species in order to establish whether they derive from endemic or invading populations. Gross morphological and molecular studies have demonstrated the existence of two distinct lineages of this species, one African and the other Asian. Wing morphometry is known to be of substantial assistance in identifying the geographical origin of individuals because it provides diagnostic markers that complement molecular diagnostics. However, placement of the landmarks used in traditional geometric morphometric analysis can be time‐consuming and subject to error caused by operator subjectivity. Here we report results of an image‐based approach to geometric morphometric analysis for delivering wing‐based identifications. Our results indicate that this approach can produce identifications that are practically indistinguishable from more traditional landmark‐based results. In addition, we demonstrate that the direct analysis of digital wing images can be used to discriminate between three Chrysomya species of veterinary and forensic importance and between C. bezziana genders.