Issue 20, 2011

Comprehensive quality evaluation of Fructus Schisandrae using electrospray ionization ion trap multiple-stage tandem mass spectrometry coupled with chemical pattern recognition techniques

Abstract

Electrospray ionization ion trap multiple-stage tandem mass spectrometry (ESI-MSn) was used to evaluate Fructus Schisandrae of similar species (Schisandra chinensis (Turcz.) Baill. fruits and Schisandra sphenanthera Rehd. et Wils. fruits) and different growth characteristics (color, shape, etc.). The application of chemical pattern recognition in the ESI-MSn data analysis was carried out by principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). Then the antioxidant activity of different Fructus Schisandrae samples were determined by an LC-ESI-MS method and ferric reducing antioxidant power (FRAP) assay. Using the ESI-MSn method coupled with chemical pattern recognition analysis and correlated with the antioxidant activity evaluation, the two similar species were successfully distinguished, thus improving the therapeutic safety and effectiveness. The superior characteristics of Schisandra chinensis (Turcz.) Baill. fruits were obtained and made the selection and breeding of Chinese medicine materials more scientific. This study indicates that ESI-MSn is a valuable tool for the authentication of botanical origin and can also be useful for the quality control of Chinese medicinal herbs.

Graphical abstract: Comprehensive quality evaluation of Fructus Schisandrae using electrospray ionization ion trap multiple-stage tandem mass spectrometry coupled with chemical pattern recognition techniques

Article information

Article type
Paper
Submitted
25 Jun 2011
Accepted
26 Jul 2011
First published
06 Sep 2011

Analyst, 2011,136, 4308-4315

Comprehensive quality evaluation of Fructus Schisandrae using electrospray ionization ion trap multiple-stage tandem mass spectrometry coupled with chemical pattern recognition techniques

X. Huang, F. Song, Z. Liu, S. Liu and J. Ai, Analyst, 2011, 136, 4308 DOI: 10.1039/C1AN15527J

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