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

Body fluid (BF) identification is a critical part of a criminal investigation because of its ability to suggest how the crime was committed and to provide reliable origins of DNA. In contrast to current methods using serological and biochemical techniques, vibrational spectroscopic approaches provid...

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Bibliographic Details
Published in:Scientific reports 2018-05, Vol.8 (1), p.8459-10, Article 8459
Main Authors: Takamura, Ayari, Watanabe, Ken, Akutsu, Tomoko, Ozawa, Takeaki
Format: Article
Language:English
Subjects:
631/92/630
639/638/11/2257
639/638/11/872
Deoxyribonucleic acid
DNA
Forensic science
Fourier transforms
Humanities and Social Sciences
Identification
Infrared spectroscopy
multidisciplinary
Peripheral blood
Saliva
Science
Science (multidisciplinary)
Semen
Spectrum analysis
Statistical analysis
Sweat
Urine
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Summary:Body fluid (BF) identification is a critical part of a criminal investigation because of its ability to suggest how the crime was committed and to provide reliable origins of DNA. In contrast to current methods using serological and biochemical techniques, vibrational spectroscopic approaches provide alternative advantages for forensic BF identification, such as non-destructivity and versatility for various BF types and analytical interests. However, unexplored issues remain for its practical application to forensics; for example, a specific BF needs to be discriminated from all other suspicious materials as well as other BFs, and the method should be applicable even to aged BF samples. Herein, we describe an innovative modeling method for discriminating the ATR FT-IR spectra of various BFs, including peripheral blood, saliva, semen, urine and sweat, to meet the practical demands described above. Spectra from unexpected non-BF samples were efficiently excluded as outliers by adopting the Q-statistics technique. The robustness of the models against aged BFs was significantly improved by using the discrimination scheme of a dichotomous classification tree with hierarchical clustering. The present study advances the use of vibrational spectroscopy and a chemometric strategy for forensic BF identification.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-018-26873-9