Since confirmation of the human origins of bloodstains is important in practical forensics, but current serological blood tests are destructive and often provide false positive results, this article reports on the development of a nondestructive method that could potentially be applied at the crime scene for differentiation of human and animal blood, using attenuated total reflection Fourier transform-infrared (ATR FT-IR) spectroscopy and statistical analysis.
The following species were used to build statistical models for binary human–animal blood differentiation: cat, dog, rabbit, horse, cow, pig, opossum, and raccoon. Three other species (deer, elk, and ferret) were used for external validation. A partial least squares discriminant analysis (PLSDA) was used for classification purposes and showed excellent performance in internal cross-validation (CV). The method was externally validated first using blood samples from new donors of species used in the training data set, and second using donors of new species that were not used to construct the model. Both validations showed excellent results, demonstrating the potential of the developed approach for nondestructive, rapid, and statistically confident discrimination between human and animal blood for forensic purposes. (publisher abstract modified)
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