Metabolomics driven analysis of six Nigella species seeds via UPLC-qTOE-MS and GC-MS coupled to chemometrics
Metabolomics driven analysis of six Nigella species seeds via UPLC-qTOE-MS and GC-MS coupled to chemometrics
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DOI:
10.1016/j.foodchem.2013.11.032
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发表时间:
2014-05-15
期刊:
影响因子:
8.8
通讯作者:
Wessjohann, Ludger A.
中科院分区:
文献类型:
--
作者:
Farag, Mohamed A.;Gad, Haidy A.;Wessjohann, Ludger A.
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.