Laboratório de Química Biológica e Quimiometria, Instituto de Química, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil.
Laboratório de Insetos e Vetores, Departamento de Microbiologia e Parasitologia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil.
Acta Trop. 2022 Nov;235:106672. doi: 10.1016/j.actatropica.2022.106672. Epub 2022 Aug 28.
Infrared spectroscopy has been gaining prominence in entomology, such as for solving taxonomic problems, sexing adult specimens, determining the age of immature specimens, detecting drugs of abuse in fly larvae, and can be an important technique in Forensic Entomology. In order to help identify the species of Calliphoridae and Sarcophagidae families, the present study aimed to evaluate the use of near infrared spectroscopy (NIRS) coupled with chemometric methods for separating fly specimens into taxonomic categories and understanding the taxonomic relationship between them. Spectra collected from nine species of flies were subjected to unsupervised principal component analysis (PCA) and hierarchical cluster analysis (HCA), in which we sought to visualize the relationship between the samples (segregation of genera and families) with subsequent identification. In PCA, the best model was achieved using five principal components (PCs), which explained 99.16% of total variance of the original data set. The first principal component (PC1) and the fourth principal component (PC4) provided the best segregation, the latter being more important in the segregation of the species Chrysomya albiceps, Lucilia eximia, and Ravinia belforti from the others. In the HCA dendrogram, there was a clear separation between the specimens by family (Calliphoridae and Sarcophagidae) and genera (Chrysomya, Lucilia, Oxysarcodexia, Peckia and Ravinia). This study shows that NIRS is efficient to identify flies' taxonomic properties, such as family and genera, providing quick evidence for the tested species identity.
近红外光谱技术在昆虫学领域的应用日益广泛，例如解决分类问题、鉴定成虫性别、确定幼虫年龄、检测蝇幼虫中的滥用药物等，并且可以成为法医昆虫学中的重要技术。为了帮助鉴定丽蝇科和麻蝇科的物种，本研究旨在评估近红外光谱（NIRS）结合化学计量方法在将蝇类标本分为分类类别的用途，以及理解它们之间的分类关系。对来自九个蝇种的光谱进行了无监督主成分分析（PCA）和层次聚类分析（HCA），我们试图通过随后的鉴定来可视化样本之间的关系（属和科的分离）。在 PCA 中，使用五个主成分（PC）实现了最佳模型，解释了原始数据集总方差的 99.16%。第一主成分（PC1）和第四主成分（PC4）提供了最佳的分离，后者在 Chrysomya albiceps、Lucilia eximia 和 Ravinia belforti 等物种的分离中更为重要。在 HCA 树状图中，通过科（丽蝇科和麻蝇科）和属（丽蝇属、绿蝇属、Oxysarcodexia 属、Peckia 属和 Ravinia 属）可以清楚地区分标本。本研究表明，NIRS 可有效地识别蝇类的分类特征，如科和属，为测试物种的身份提供快速证据。
