4.7 Article

Metabolomics driven analysis of six Nigella species seeds via UPLC-qTOE-MS and GC-MS coupled to chemometrics

Journal

FOOD CHEMISTRY
Volume 151, Issue -, Pages 333-342

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2013.11.032

Keywords

Black cumin; Metabolomics; Natural products; GC-MS; UPLC-MS; Principal component analysis; N. arvensis; N. damascena; N. hispanica; N. nigellastrum; N. orientalis; N. sativa

Funding

  1. Alexander von Humboldt-foundation, Germany

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Nigella sativa, commonly known as black cumin seed, is a popular herbal supplement that contains numerous phytochemicals including terpenoids, saponins, flavonoids, alkaloids. Only a few of the ca. 15 species in the genus Nigella have been characterized in terms of phytochemical or pharmacological properties. Here, large scale metabolic profiling including UPLC-PDA-MS and GC-MS with further multivariate analysis was utilized to classify 6 Nigella species. Under optimized conditions, we were able to annotate 52 metabolites including 8 saponins, 10 flavonoids, 6 phenolics, 10 alkaloids, and 18 fatty acids. Major peaks in UPLC-MS spectra contributing to the discrimination among species were assigned as kaempferol glycosidic conjugates, with kaempferol-3-O-[glucopyranosyl-(1 -> 2)-galactopyranosyl-(1 -> 2)-glucopyranoside, identified as potential taxonomic marker for N. sativa. Compared with GC-MS, UPLC-MS was found much more efficient in Nigella sample classification based on genetic and geographical origin. Nevertheless, both GC-MS and UPLC-MS support the remote position of Nigella nigellastrum in relation to the other taxa. (C) 2013 Elsevier Ltd. All rights reserved.

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