Literature DB >> 23890631

Circumventing substrate interference in the Raman spectroscopic identification of blood stains.

Gregory McLaughlin1, Vitali Sikirzhytski, Igor K Lednev.   

Abstract

Raman spectroscopy has demonstrated remarkable capabilities in identifying blood in controlled laboratory conditions. However, substrate interference presents a significant challenge toward characterizing body fluid traces with Raman spectroscopy at a crime scene. Here, several possible solutions are explored, including the selection of laser excitation, isolating the signal of blood using spectral subtraction and using a favorable substrate for collection which minimizes interference. Simulated blood stain evidence was prepared and analyzed using a Raman microscope with variable laser capabilities. It is shown that the best approach for detecting blood depends on the nature of the substrate and the type of interference encountered.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Keywords:  Blood detection; Forensic science; Raman spectroscopy; Statistical analysis; Substrate interference

Mesh:

Year:  2013        PMID: 23890631     DOI: 10.1016/j.forsciint.2013.04.033

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  4 in total

1.  Detection and discrimination of seminal fluid using attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy combined with chemometrics.

Authors:  Sweety Sharma; Rajinder Singh
Journal:  Int J Legal Med       Date:  2019-12-09       Impact factor: 2.686

2.  Comparative Study of Sample Carriers for the Identification of Volatile Compounds in Biological Fluids Using Raman Spectroscopy.

Authors:  Panagiota Papaspyridakou; Michail Lykouras; Christos Kontoyannis; Malvina Orkoula
Journal:  Molecules       Date:  2022-05-20       Impact factor: 4.927

3.  Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis.

Authors:  Ayari Takamura; Ken Watanabe; Tomoko Akutsu; Takeaki Ozawa
Journal:  Sci Rep       Date:  2018-05-31       Impact factor: 4.379

4.  Correction of Substrate Spectral Distortion in Hyper-Spectral Imaging by Neural Network for Blood Stain Characterization.

Authors:  Nicola Giulietti; Silvia Discepolo; Paolo Castellini; Milena Martarelli
Journal:  Sensors (Basel)       Date:  2022-09-27       Impact factor: 3.847

  4 in total

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