Randomized trial demonstrates enhanced ginsenoside isomer identification via online energy-resolved mass spectrometry, suggesting improved analytical methods.
(PGL and PQL). Among 395 identified ginsenosides, 27 were assigned with enhanced confidence. Furthermore, five markers differentiating PGL and PQL were identified via pseudo-targeted metabolomics and machine learning. Comparative analysis across the mainstream MS platforms established dimeric ions in full-scan spectra as diagnostic markers for distinguishing mono- and bidesmosidic ginsenosides. This study demonstrates the applicability of online ER-MS-derived OCE as a complementary structural descriptor in improved annotation of ginsenoside isomers.
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Zou et al. (2026) studied this question.
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