Foods (Basel, Switzerland) · 2026
GC-Derived Volatile Profiling of Commercial Thyme and Oregano Labeled Products and Evaluation of Portable NIR Screening.
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Ozdemir-Orhan Necla, Akpinar-Uzun Merve, Gunes Nurhan, Tekin Aziz, Menevseoglu Ahmed
Аннотация
Commercial aromatic herbs sold under the names thyme and oregano may encompass heterogeneous plant materials, making chemical-profile screening important even when botanical identity is unknown. This study characterized 110 commercial products marketed in Türkiye and evaluated whether portable near-infrared (NIR) spectroscopy could predict chemical-profile classes derived independently from GC-FID/MS data. Commercial labels were recorded but were not treated as verified species identities. Essential oils were measured in technical duplicate for 23 volatile compounds; replicate means were subjected to compositional data treatment, principal component analysis and Ward clustering. Two clusters were selected by the silhouette criterion (0.485), and cluster stability under technical-replicate resampling was high (median adjusted Rand index, 0.907). Cluster 1 (n = 17) was relatively enriched in sabinene, caryophyllene, carvacrol and delta-3-carene, whereas Cluster 2 (n = 93) showed higher myrcene, p-cymene, alpha-pinene and beta-pinene. Two NIR spectra were collected per sample. To prevent replicate leakage, spectra were averaged before repeated nested cross-validation; a grouped-replicate analysis was also performed. A majority-class baseline achieved 84.55% accuracy but only 0.500 balanced accuracy. The best primary model, shrinkage linear discriminant analysis, yielded a mean accuracy of 0.689, a balanced accuracy of 0.565, a macro-F1 of 0.530 and a Matthews correlation coefficient of 0.103. The grouped-replicate sensitivity analysis gave a balanced accuracy of 0.592. Thus, GC-FID/MS revealed a stable chemical-profile structure, but portable NIR did not reliably recover the minority chemical class. NIR may support exploratory triage after broader calibration, but the present data do not support stand-alone botanical authentication or definitive chemical-class assignment.