Discrimination Between Human and Animal Blood Using Raman Spectroscopy and a Self-Reference Algorithm for Forensic Purposes: Method Expansion and Validation

Abstract

Determining whether the origin of a bloodstain is human or non-human is important during a forensic investigation. In their pioneering work, Bian et al. introduced a self-reference peak algorithm for the analysis of the Raman spectra of bloodstains and demonstrated the great potential of this approach for differentiating between human and non-human blood. However, this work only used three non-human species in the creation of their original model. The current study expands the capability of a self-referencing algorithm to discriminate between human and 18 non-human species based on the Raman spectra of blood samples. The intensity ratios between the bands at 1003 and 1341 cm−1 of the samples’ Raman spectra were compared between species to determine whether a threshold existed that separates human samples from those of non-humans. The self-referencing algorithm was capable of correctly categorizing spectra averaged from donors of all 18 non-human species. The use of this algorithm is simple and requires little training or knowledge of statistics, which makes it accessible for forensic applications, compared to computationally difficult analysis methods. This technique using Raman spectroscopy is rapid, nondestructive, and highly accurate making it a promising tool for forensic applications.