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A novel use of infra-red spectroscopy (NIRS and ATR-FTIR) coupled with variable selection algorithms for the identification of insect species (Diptera: Sarcophagidae) of medico-legal relevance.
- Source :
-
Acta Tropica . Sep2018, Vol. 185, p1-12. 12p. - Publication Year :
- 2018
-
Abstract
- Unequivocal identification of fly specimens is an essential requirement in forensic entomology. Herein, a simple, non-destructive and rapid method based on two vibrational spectroscopy techniques [Near-Infrared Spectroscopy (NIRS) and attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy] coupled with variable selection techniques such as genetic algorithm-linear discriminant analysis (GA-LDA) and successive projection algorithm-linear discriminant analysis (SPA-LDA) were applied for identifying and discriminating six species of flesh flies (Diptera: Sarcophagidae) native to Neotropical regions. This novel approach is based on the unique spectral “fingerprints” of their biochemical composition. One hundred sixty (160) NIRS and FT-IR specimens (120 male, 40 female) were acquired; different pre-processing methods such as baseline correction, derivative and Savitzky-Golay smoothing were also performed. In addition, the multivariate classification accuracy results were tested based on sensitivity, specificity, positive (or precision) and negative predictive values, Youden index, positive and negative likelihood ratios. Principal components analysis (PCA) was employed for male vs. female category using NIRS, strongly showing the separation between the classes with only three principal components and 99% explained variance. Differentiation between the genera Oxysarcodexia, Peckia and Ravinia was efficiently confirmed by both techniques. In comparison with other biological methods, this approach represents an effective choice for fast and non-destructive identification in forensic entomology. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0001706X
- Volume :
- 185
- Database :
- Academic Search Index
- Journal :
- Acta Tropica
- Publication Type :
- Academic Journal
- Accession number :
- 130541774
- Full Text :
- https://doi.org/10.1016/j.actatropica.2018.04.025