Barbosa Taciano M, de Lima Leomir A S, Dos Santos Marfran C D, Vasconcelos Simão D, Gama Renata A, Lima Kássio M G
Insects of Forensic Importance Research Group, Department of Zoology, Federal University of Pernambuco, Av. Prof. Moraes Rego, Recife, PE, 50.670-420, Brazil.
Biological Chemistry and Chemometrics, Institute of Chemistry, Federal University of Rio Grande do Norte, Natal, RN, 59.072-970, Brazil.
Acta Trop. 2018 Sep;185:1-12. doi: 10.1016/j.actatropica.2018.04.025. Epub 2018 Apr 24.
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.
准确鉴定蝇类标本是法医昆虫学的一项基本要求。在此，一种基于两种振动光谱技术[近红外光谱（NIRS）和衰减全反射傅里叶变换红外（ATR-FTIR）光谱]并结合可变选择技术（如遗传算法-线性判别分析（GA-LDA）和连续投影算法-线性判别分析（SPA-LDA））的简单、无损且快速的方法，被用于鉴定和区分新热带地区原产的六种麻蝇（双翅目：麻蝇科）。这种新方法基于其生化组成的独特光谱“指纹”。采集了160个NIRS和FT-IR标本（120个雄性，40个雌性）；还进行了不同的预处理方法，如基线校正、导数和Savitzky-Golay平滑处理。此外，基于灵敏度、特异性、阳性（或精确性）和阴性预测值、约登指数、阳性和阴性似然比来测试多变量分类准确性结果。使用NIRS对雄性和雌性类别进行主成分分析（PCA），仅用三个主成分就强烈显示出类别之间的分离，且解释方差为99%。这两种技术都有效地证实了尖麻蝇属、腐麻蝇属和黑麻蝇属之间的区分。与其他生物学方法相比，这种方法是法医昆虫学中快速无损鉴定的有效选择。
