Date of Award




Document Type

Master's Thesis

Degree Name

Master of Science (MS)


Department of Chemistry

Content Description

1 online resource (v. 13 pages) : illustrations (some color)

Dissertation/Thesis Chair

Igor K Lednev

Committee Members

Alexander Shekhtman, Maksim Royzen


Blood species discrimination, Hemoglobin, Raman Spectroscopy, Self-reference algorithm, Bloodstains, Blood, Forensic hematology, Raman spectroscopy

Subject Categories



Determining whether the origin of a bloodstain is human or non-human is an important capability of a forensic investigation. In their pioneering work, Bian et al. (Journal of biomedical optics, 2017) introduced a self-reference peak algorithm for the analysis of bloodstain Raman spectra and demonstrated a great potential of this approach for differentiating human and nonhuman blood. However, this work only used three non-human species in the creation of their model. This study investigates the capability of a self-referencing peak algorithm to discriminate between human and 18 non-human species based on the Raman spectra of blood samples. The intensity ratios between the peaks at 1003 cm-1 and 1341 cm-1 of the samples’ Raman spectra were compared between species to determine whether a threshold existed which separates human samples from those of non-humans. It was determined that a self-referencing algorithm was capable of correctly categorizing spectra from all donors of 17 of 18 non-human species. Usage of this algorithm is simple and requires little training or knowledge of statistics, which makes it more accessible for forensic applications. This technique using Raman spectroscopy is rapid, non-destructive, and highly accurate making it a promising tool for forensic applications.

Included in

Chemistry Commons