Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Chemical Differentiation and Quantitative Analysis of Black Ginseng Based on a LC-MS Combined with Multivariate Statistical Analysis Approach

Version 1 : Received: 9 June 2023 / Approved: 9 June 2023 / Online: 9 June 2023 (08:43:03 CEST)

A peer-reviewed article of this Preprint also exists.

Li, L.; Chang, Z.; Wei, K.; Tang, Y.; Chen, Z.; Zhang, H.; Wang, Y.; Zhu, H.; Feng, B. Chemical Differentiation and Quantitative Analysis of Black Ginseng Based on an LC-MS Combined with Multivariate Statistical Analysis Approach. Molecules 2023, 28, 5251. Li, L.; Chang, Z.; Wei, K.; Tang, Y.; Chen, Z.; Zhang, H.; Wang, Y.; Zhu, H.; Feng, B. Chemical Differentiation and Quantitative Analysis of Black Ginseng Based on an LC-MS Combined with Multivariate Statistical Analysis Approach. Molecules 2023, 28, 5251.

Abstract

Black ginseng is a type of processed ginseng that is traditionally used as herbal medicine in East Asian countries. It is prepared from fresh, white, or red ginseng by undergoing a process of steaming and drying nine times. However, the chemical differentiation of black ginseng with different processing levels is not well understood. The aim of this study is to propose a new method for discriminating and quantifying black ginseng. Six ginsenosides from black ginseng were accurately quantified, and based on this, the black ginseng samples were divided into uncompleted and completed black ginseng. Ultra-high-performance liquid chromatography-quadrupole-time of flight/mass spectrometry (UPLC-Q-TOF/MS) combined with a multivariate statistical analysis strategy was then employed to differentiate the two groups. A total of 141 ions were selected as analytical markers of black ginseng, with 45 of these markers being annotated by matching precise m/z and MS/MS data from prior studies.

Keywords

Black ginseng; Ginsenosides; UPLC-Q-TOF/MS; processing; multivariate statistical analysis

Subject

Medicine and Pharmacology, Medicine and Pharmacology

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.