Label-free Raman chemometric analysis for in situ authentication and molecular profiling of Wagyu beef under retail packaging.

Wagyu beef's distinctive flavor and tenderness arise from its high levels of unsaturated intramuscular triglycerides. Although these compositional distinctions provide a unique Raman signature, extensive band overlap and background attenuation from packaging and frozen conditions hinder reliable in situ classification and constrain the interpretability of raw spectra. This study presents a label-free Raman spectroscopic and chemometric approach for authenticating Wagyu beef under realistic retail-like conditions. A supervised partial least squares discriminant analysis (PLS-DA) model was developed using spectra from unwrapped adipose tissue and evaluated with an independent validation set of frozen, plastic-wrapped samples from multiple breeds and suppliers. The model achieved 100% sample-level classification accuracy, supported by receiver operating characteristic and confusion-matrix analyses. To elucidate the molecular basis of discrimination and resolve spectral congestion, a two-stage decomposition combining singular value decomposition (SVD) and nonnegative matrix factorization (NMF) was applied, followed by nonnegative least squares (NNLS) fitting with pure triglyceride standards. The analyses yielded chemically interpretable components, revealing enrichment of unsaturated triglycerides in Wagyu beef consistent with established compositional data. To our knowledge, this is the first report applying Raman-based PLS-DA for Wagyu authentication and integrating SVD, NMF, and NNLS for molecular-level interpretation in food authentication. Overall, Raman spectroscopy integrated with interpretable spectral decomposition provides a rapid, nondestructive, and chemically transparent tool for meat authentication and quality assurance.