Random forests for predicting species identity of forensically important blow flies (Diptera: Calliphoridae) and flesh flies (Diptera: Sarcophagidae) using geometric morphometric data: Proof of concept

Khang, Tsung Fei and Mohd Puaad, Nur Ayuni Dayana and Teh, Ser Huy and Mohamed, Zulqarnain (2021) Random forests for predicting species identity of forensically important blow flies (Diptera: Calliphoridae) and flesh flies (Diptera: Sarcophagidae) using geometric morphometric data: Proof of concept. Journal of Forensic Sciences, 66 (3). pp. 960-970. ISSN 0022-1198, DOI https://doi.org/10.1111/1556-4029.14655.

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Abstract

Wing shape variation has been shown to be useful for delineating forensically important fly species in two Diptera families: Calliphoridae and Sarcophagidae. Compared to DNA-based identification, the cost of geometric morphometric data acquisition and analysis is relatively much lower because the tools required are basic, and stable softwares are available. However, to date, an explicit demonstration of using wing geometric morphometric data for species identity prediction in these two families remains lacking. Here, geometric morphometric data from 19 homologous landmarks on the left wing of males from seven species of Calliphoridae (n = 55), and eight species of Sarcophagidae (n = 40) were obtained and processed using Generalized Procrustes Analysis. Allometric effect was removed by regressing centroid size (in log(10)) against the Procrustes coordinates. Subsequently, principal component analysis of the allometry-adjusted Procrustes variables was done, with the first 15 principal components used to train a random forests model for species prediction. Using a real test sample consisting of 33 male fly specimens collected around a human corpse at a crime scene, the estimated percentage of concordance between species identities predicted using the random forests model and those inferred using DNA-based identification was about 80.6% (approximate 95% confidence interval = 68.9%, 92.2%]). In contrast, baseline concordance using naive majority class prediction was 36.4%. The results provide proof of concept that geometric morphometric data has good potential to complement morphological and DNA-based identification of blow flies and flesh flies in forensic work.

Item Type: Article
Funders: University of Malaya Postgraduate Research Grant (PG074-2015A)
Uncontrolled Keywords: Calliphoridae; Forensic entomology; Geometric morphometrics; Random forests; Sarcophagidae; Species identity prediction; Wing shape
Subjects: Q Science > QA Mathematics
Q Science > QH Natural history > QH301 Biology
R Medicine > R Medicine (General)
Divisions: Faculty of Science
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 01 Apr 2022 07:57
Last Modified: 01 Apr 2022 07:58
URI: http://eprints.um.edu.my/id/eprint/26641

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