This study achieved an important advancement of a previous study of nondestructive differentiation of human and animal blood, using Raman spectroscopy coupled with partial least squares discriminant analysis (PLSDA).
The identification of blood samples is a crucial facet of forensic investigations, particularly for violent crimes. One step in forensic serology (i.e., the analysis of bodily fluids) that is often skipped or overlooked is the determination of whether a bloodstain is of human or nonhuman origin. Typically, after identifying a stain as blood using a presumptive blood test, which has the propensity of providing false positive results, the stain is submitted for extraction of a DNA profile to compare with those in a database. It is uncommon for evidentiary bloodstains to be confirmed as being of human origin throughout the serological analysis; therefore, time, money, and other resources can be wasted on obtaining a DNA profile from a bloodstain that may not be of human origin if the intent was to obtain a human DNA profile and not that of an animal. In the current study, Raman spectra of blood from six species of animals not previously accounted for - including chimpanzee, deer, elk, ferret, fish, and macaque - were used to test a PLSDA classification method. These animal species are forensically relevant since they are (i) involved in wildlife crimes, (ii) consumed by humans, or (iii) known to produce a false positive result when their blood is tested with certain presumptive human blood tests. An external validation sensitivity of 1.00 and specificity of 0.93 for human class predictions was obtained from the PLSDA model constructed for this study. Using receiver operating characteristic (ROC) analysis of external human class predictions, the PLSDA model demonstrated 99 percent accuracy in being able to correctly classify any random blood sample as human or nonhuman. This is a significant advancement over the previous work and an important finding, since it demonstrates the superb selectivity of the developed method with high accuracy in being able to correctly predict the nonhuman origin of bloodstains from unknown animal species. (publisher abstract modified)
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Date Published: January 1, 2018