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.
A partial least squares discriminant analysis (PLSDA) was used for classification purposes and showed excellent performance in internal cross-validation (CV). Three other species (deer, elk, and ferret) were used for external validation. The following species were used to build statistical models for binary human–animal blood differentiation: cat, dog, rabbit, horse, cow, pig, opossum, and raccoon. Here, we report on the development of a nondestructive method that could potentially be applied at the scene for differentiation of human and animal blood using attenuated total reflection Fourier transform-infrared (ATR FT-IR) spectroscopy and statistical analysis. Current serological blood tests are destructive and often provide false positive results.
Confirmation of the human origins of bloodstains is important in practical forensics. This field has been rapidly growing over the last several decades.
Forensic chemistry is an important area of analytical chemistry.