The development of novel methods for forensic science is a constantly growing area of modern analytical chemistry. Raman spectroscopy is one of a few analytical techniques capable of nondestructive and nearly instantaneous analysis of a wide variety of forensic evidence, including body- fluid stains found at the scene of a crime. In the current study, Raman spectra were acquired in mapping mode from multiple spots on a bloodstain to account for intrinsic sample heterogeneity. The obtained Raman spectroscopic data showed highly similar spectroscopic features for female and male blood samples; however, support vector machines (SVM) and artificial neuron network (ANN) statistical methods applied to the spectroscopic data enabled the differentiation between male and female bloodstains with high confidence. Specifically, the statistical approach based on a genetic algorithm (GA) coupled with an ANN classification showed approximately 98 percent gender differentiation accuracy for individual bloodstains. These results demonstrate the potential of the developed method for forensic applications, although more work is needed for method validation. When this method is fully developed, a portable Raman instrument could be used for the field identification of traces of body fluids and to obtain phenotypic information about the donor, including gender and race, as well as for the analysis of a variety of other types of forensic evidence. (Publisher abstract modified)
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