title: Blood species identification for forensic purposes using Raman spectroscopy combined with advanced statistical analysis.
abstract: Forensic analysis has become one of the most growing areas of analytical chemistry in recent years. The ability to determine the species of origin of a body fluid sample is a very important and crucial part of a forensic investigation. We introduce here a new technique which utilizes a modern analytical method based on the combination of Raman spectroscopy and advanced statistics to analyze the composition of blood traces from different species. Near-infrared Raman spectroscopy (NIR) was used to analyze multiple dry samples of human, canine, and feline blood for the ultimate application to forensic species identification. All of the spectra were combined into a single data matrix, and the number of principle components that described the system was determined using multiple statistical methods such as significant factor analysis (SFA), principle component analysis (PCA), and several cross-validation methods. Of the six principle components that were determined to be present, the first three, which contributed over 90% to the spectral data of the system, were used to form a three-dimensional scores plot that clearly showed significant separation between the three groups of species. Ellipsoids representing a 99% confidence interval surrounding each species group showed no overlap. This technique using Raman spectroscopy is nondestructive and quick and can potentially be performed at the scene of a crime.
authors: Department of Chemistry, University at Albany, State University of New York, 1400 Washington Avenue, Albany, New York 12222, USA.
authors: Kelly
authors: K
authors: Virkler
authors: Igor K
authors: IK
authors: Lednev
mesh_terms: D000818:Animals; D001801:Blood Stains; D002415:Cats; D004285:Dogs; D005554:Forensic Medicine / Q000379:methods*; D006801:Humans; D025341:Principal Component Analysis; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D013059:Spectrum Analysis, Raman / Q000379:methods*