Using surface-enhanced Raman spectroscopy to probe artificial dye degradation on hair buried in multiple soils for up to eight weeks.

Hair Hair dyes Raman spectroscopy SERS Soils

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
18 Mar 2024
Historique:
received: 13 11 2023
accepted: 14 03 2024
medline: 19 3 2024
pubmed: 19 3 2024
entrez: 19 3 2024
Statut: epublish

Résumé

The discovery of clandestine burials poses unique challenges for forensic specialists, requiring diverse expertise to analyze remains in various states. Bones, teeth, and hair often endure the test of time, with hair particularly exposed to the external environment. While existing studies focus on the degradation of virgin hair influenced by soil pH and decomposition fluids, the interaction between artificial dyes on hair and soil remains underexplored. This paper introduces a novel approach to forensic hair analysis that is based on high-throughput, nondestructive, and non-invasive surface-enhanced Raman spectroscopy (SERS) and machine learning. Using this approach, we investigated the reliability of the detection and identification of artificial dyes on hair buried in three distinct soil types for up to eight weeks. Our results demonstrated that SERS enabled the correct prediction of 97.9% of spectra for five out of the eight dyes used within the 8 weeks of exposure. We also investigated the extent to which SERS and machine learning can be used to predict the number of weeks since burial, as this information may provide valuable insights into post-mortem intervals. We found that SERS enabled highly accurate exposure intervals to soils for specific dyes. The study underscores the high achievability of SERS in extrapolating colorant information from dyed hairs buried in diverse soils, with the suggestion that further model refinement could enhance its reliability in forensic applications.

Identifiants

pubmed: 38499595
doi: 10.1038/s41598-024-57147-2
pii: 10.1038/s41598-024-57147-2
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

6469

Subventions

Organisme : National Institute of Justice
ID : 2020-90663-TX-DU

Informations de copyright

© 2024. The Author(s).

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Auteurs

Aidan P Holman (AP)

Department of Entomology, Texas A&M University, College Station, TX, 77843, USA.
Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, 77843, USA.

Mackenzi Peterson (M)

Department of Entomology, Texas A&M University, College Station, TX, 77843, USA.
Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, 77843, USA.

Emily Linhart (E)

Department of Entomology, Texas A&M University, College Station, TX, 77843, USA.

Dmitry Kurouski (D)

Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, 77843, USA. dkurouski@tamu.edu.
Department of Biomedical Engineering, Texas A&M University, College Station, TX, 77843, USA. dkurouski@tamu.edu.
Institute for Advancing Health Through Agriculture, College Station, TX, 77843, USA. dkurouski@tamu.edu.

Classifications MeSH