Species Identification of Sarcosaprophagous Flies Based on Vein Digital Image Analysis.
10.12116/j.issn.1004-5619.2020.400506
- Author:
Yan Jie SHANG
1
;
Peng Liang PAN
2
;
Xiang Rong LI
1
;
Ke LI
1
;
Jiang LIN
1
;
Ya Dong GUO
1
Author Information
1. Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China.
2. Xinyang Agriculture and Forestry University, Xinyang 464000, Henan Province, China.
- Publication Type:Journal Article
- Keywords:
forensic entomology;
sarcosaprophagous flies;
vein;
digital image processing
- MeSH:
Animals;
Calliphoridae;
Diptera;
Female;
Male;
Reproducibility of Results
- From:
Journal of Forensic Medicine
2021;37(3):325-331
- CountryChina
- Language:English
-
Abstract:
Objective To identify species of common sarcosaprophagous flies based on digital image analysis of veins, in order to provide new idea for fast and accurate species identification of sarcosaprophagous flies in forensic entomology. Methods Random trapping of 226 male and female sarcosaprophagous flies that comprised of 7 common species, including Sarcophaga peregrina, Parasarcophaga ruficornis, Sarcophaga dux, Seniorwhitea reciproca, Bercaea cruentata, Aldrichina grahami, and Synthesiomysia nudiseta with carrion in the field was conducted. The 17 landmarks on the right wing of each fly were digitally processed and the images were analyzed. The effects of allometry were evaluated using a permutation test. Wing shape variations among 7 sarcosaprophagous fly species and female species was analyzed using canonical variate analysis （CVA）. Additionally, cross-validation test was used to evaluate the reliability of classification. Results Among 7 sarcosaprophagous fly species and female species, the effect of allometry had statistical significance （P<0.05）. The CVA results showed that among 7 sarcosaprophagous fly species and female species, differences in the wing shape were significant, and the first two canonical variates accounted for 82.9% and 84.1% of the total variation of vein shape. Vein digital image analysis can be used to separate the 7 common sarcosaprophagous flies, with an overall species identification accuracy of 81.2%-100.0%, and with a species identification accuracy of 75.0%-100.0% to distinguish the female flies of the 7 sarcosaprophagous flies species. Conclusion Vein digital image analysis is a relatively convenient and reliable method for identification of insect species, which can be used for species identification of common sarcosaprophagous flies.
