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Near-infrared Excitation Raman Spectroscopy of Colored Fabric Contaminated with Body Fluids

NCJ Number
309450
Journal
Scientific Reports Volume: 14 Issue: 19080 Dated: Aug 2024
Date Published
August 2024
Length
11 pages
Annotation

This paper explores an option for a robust and reliable analytical approach to the forensic analysis of fabric; investigating the extent of the impacts on accuracy for the analysis that blood, semen, and urine have on cotton fabrics containing green, pink, and light red dyes, as well as the extent to which body fluids could be identified using NieRS on blank and colored cotton fabric.

Abstract

Confirmatory identification of dyes in the physical pieces of evidence, such as hair and fabric, is critically important in forensics. This information can be used to demonstrate the link between a person of interest and a crime scene. High performance liquid chromatography is broadly used for dye analysis. However, this technique is destructive and laborious. This problem can be overcome by near-Infrared excitation Raman spectroscopy (NIeRS), non-invasive and non-destructive technique that can be used to determine chemical structure of highly fluorescent dyes. Analyzed fabric materials often possess body fluid stains, which may obscure the accuracy of NIeRS-based identification of dyes. In this study, the authors investigate the extent to which fabric contamination with body fluids can alter the accuracy of NIeRS. Their results showed that NIeRS coupled with partial-least squared discriminant analysis (PLS-DA) enabled on average 97.6 percent accurate identification of dyes on fabric contaminated with dry blood, urine and semen. They also found that NIeRS could be used to identify blood, urine and semen on such fabric with 99.4 percent accuracy. Furthermore, NIeRS could be used to differentiate between wet and dry blood, as well as reveal the presence of blood on washed fabric. These results indicate that NIeRS coupled with PLS-DA could be used as a robust and reliable analytical approach in forensic analysis of fabric. (Published Abstract Provided)

Date Published: August 1, 2024