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

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Stefan Ivanović
https://orcid.org/0000-0002-3291-9818
Manuela Mandrone
https://orcid.org/0000-0002-0541-390X
Katarina Simić
https://orcid.org/0000-0001-5060-8936
Mirjana Ristić
Marina Todosijević
https://orcid.org/0000-0001-6239-5368
Boris Mandić
https://orcid.org/0000-0001-6103-7657
Dejan Gođevac
https://orcid.org/0000-0002-0555-581X

Abstract

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

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How to Cite
[1]
S. Ivanović, “GC–MS-based metabolomics for the detection of adulteration in oregano samples: Scientific paper”, J. Serb. Chem. Soc., vol. 86, no. 12, pp. 1195–1203, Dec. 2021.
Section
Theme issue honoring Professor Emeritus Slobodan Milosavljevićs 80th birthday

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