Department of Chemistry, Faculty of Science, Kuwait University, Safat, Kuwait.
Department of Chemistry, University at Albany, SUNY, Albany, New York.
J Biophotonics. 2020 Mar;13(3):e201960123. doi: 10.1002/jbio.201960123. Epub 2019 Dec 5.
Raman spectroscopy has proven to be a valuable tool for analyzing various types of forensic evidence such as traces of body fluids. In this work, Raman spectroscopy was employed as a nondestructive technique for the analysis of dry traces of oral fluid to differentiate between smoker and nonsmoker donors with the aid of advanced statistical tools. A total of 32 oral fluid samples were collected from donors of differing gender, age and race and were subjected to Raman spectroscopic analysis. A genetic algorithm was used to determine eight spectral regions that contribute the most to the differentiation of smokers and nonsmokers. Thereafter, a classification model was developed based on the artificial neural network that showed 100% accuracy after external validation. The developed approach demonstrates great potential for the differentiation of smokers and nonsmokers based on the analysis of dry traces of oral fluid.
拉曼光谱已被证明是分析各种法医证据（如体液痕迹）的有价值的工具。在这项工作中，拉曼光谱被用作一种非破坏性技术，借助先进的统计工具，分析干燥的口腔液体痕迹，以区分吸烟者和非吸烟者。从不同性别、年龄和种族的供体中收集了总共 32 个口腔液体样本，并对其进行了拉曼光谱分析。遗传算法用于确定对区分吸烟者和非吸烟者贡献最大的八个光谱区域。此后，基于人工神经网络开发了一种分类模型，经外部验证后准确率达到 100%。所开发的方法基于对干燥的口腔液体痕迹的分析，显示出区分吸烟者和非吸烟者的巨大潜力。
