DyeSPY: Establishing the First Forensic SERS Reference for Hair Dye Colorant Evidence.

ABSTRACT: Hair dyeing is a widespread practice with potential forensic value in individual identification, yet most analytical approaches are destructive, time-intensive, or lack sensitivity for trace residues. Surface-enhanced Raman spectroscopy (SERS) offers a rapid, nondestructive, and highly sensitive alternative. We introduce DyeSPY, the first forensic SERS and machine learning platform for identifying oxidative and nonoxidative hair dye colorants and predicting their perceptual colors. Using spectra from 44 pure colorants, laboratory-prepared mixtures, and 60 commercial dye products applied to hair, we developed a three-phase classification pipeline. Phase I distinguished oxidative from nonoxidative dyes with up to 98.6% accuracy on hair using partial least-squares discriminant analysis. Phase

SUBMITTER: Holman AP 

PROVIDER: S-EPMC12750408 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature