Since Raman spectroscopy has proven to be a valuable tool for analyzing various types of forensic evidence such as traces of body fluids, this article reports on a research project in which Raman spectroscopy was used 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 they 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 percent accuracy after external validation. The developed approach demonstrates potential for the differentiation of smokers and nonsmokers based on the analysis of dry traces of oral fluid. (publisher abstract modified)