GC-MS-based metabolomics for the detection of adulteration in oregano samples

Oregano is one of the most used culinary herb and it often adulterated with cheaper plants. In this study, GC?MS was for identification quantification metabolites from 104 samples oregano (Origanum vulgare O. onites) olive (Olea europaea), venetian sumac (Cotinus coggygria) myrtle (Myrtus communis) leaves, at five different concentration levels. The metabolomics profiles obtained after two-step derivatization, involving methoxyamination silanization, were subjected to multivariate data analysis reveal markers adulteration build regression models on basis oregano-to-adulterants mixing ratio. Orthogonal partial least squares enabled detection adulterations olive, Venetian leaves. Sorbitol levels distinguished while shikimic quinic acids recognized as discrimination factor sumac. Fructose acid correlated myrtle. discriminant onites samples, where catechollactate found be discriminating metabolite.