Abstract

This study aimed to discriminate 22 samples of commercial Iris rhizomes (orris root) by species and origin (Iris germanica (Morocco), I. albicans (Morocco), I. pallida (Morocco), I. pallida (China), I. pallida (Italy)) by applying a strategy derived from those adopted in metabolomics. The specimens’ fingerprints from conventional analysis methods (LC–UV and/or LC–MS) were unable to provide clear discrimination. A strategy combining UHPLC/TOF-HRMS, in positive and negative modes, with multivariate statistical methods was therefore applied. Exact mass/retention time (EMRT) pairs obtained by UHPLC–TOF/HRMS were successfully submitted to statistical processing by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA), and then orthogonal partial least square-discriminant analysis (OPLS-DA), to extract the discriminating EMRT pairs through their trend views. 146 EMRT pairs were selected on the basis of their trend views, because they significantly varied, and 104 of them were included to discriminate between species and origins. 32 of them were tentatively identified as discriminating markers (flavonoids, isoflavonoids, triterpenoids, benzophenone derivatives and related glycosides …) from the reference database created on the basis of Iris genus components reported in the literature: eight of them specific for I. albicans, four for I. germanica, five for I. pallida (Italy), five for I. pallida (China), and ten for I. pallida (Morocco). The reliability of this strategy was confirmed by identifying species and origin of two unknown samples submitted to the same analytical procedure.

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