Glucosinolates (GSLs) are secondary plant metabolites that occur mainly in the Brassicaceae plants, which are desirable compounds in human foods due to their diverse biological activities. In this study, we developed an integrated data filtering and identification strategy to characterize the GSLs. An in-depth GSLs profiling was performed on 25 commonly Brassicaceae tissues in Jinan, China. By comparison with the reference standards and previous researches, we tentatively identified 47 GSLs including 8 unknown ones. The GSLs profiles of 25 Brassicaceae tissues were established, and 11 markers of GSLs could be used to distinguish the Brassica and Raphanus. This approach enables accurately characterization the GSLs of Brassicaceae tissues, and demonstrates the potential of GSLs profiles for Brassicaceae species discrimination.
Keywords: Brassicaceae; Diagnostic ion filtering; Glucosinolates; Mass defect filtering; UHPLC-Q-exactive orbitrap-MS.
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