Simultaneous determination of content of eight components in Caesalpinia decapetala by UPLC-MS/MS.
10.19540/j.cnki.cjcmm.20211011.201
- Author:
Yue-Ting LI
1
;
Hui LIU
2
;
Wen-Sha MENG
2
;
Ting ZHOU
2
;
Zi-Peng GONG
1
;
Yong HUANG
1
;
Lin ZHENG
1
Author Information
1. Guizhou Provincial Key Laboratory of Pharmaceutics, State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University Guiyang 550004, China.
2. Guizhou Provincial Key Laboratory of Pharmaceutics, State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University Guiyang 550004, China School of Pharmacy,Guizhou Medical University Guiyang 550004, China.
- Publication Type:Journal Article
- Keywords:
Caesalpinia decapetala;
UPLC-MS/MS;
content determination;
hierarchical cluster analysis;
principal component analysis
- MeSH:
Caesalpinia;
Chromatography, High Pressure Liquid;
Chromatography, Liquid;
Principal Component Analysis;
Tandem Mass Spectrometry
- From:
China Journal of Chinese Materia Medica
2022;47(3):692-700
- CountryChina
- Language:Chinese
-
Abstract:
The present study established the ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS) method for simultaneous determination of the content of eight major active components in Caesalpinia decapetala and performed the quality evaluation of C. decapetala from different habitats with the chemical pattern recognition. The analysis was carried out on a Waters BEH C_(18) column(2.1 mm×100 mm, 1.7 μm) at 40 ℃, with the mobile phase of water containing 0.1% formic acid(A) and acetonitrile containing 0.1% formic acid under gradient elution, the flow rate of 0.3 mL·min~(-1), and the injection volume of 1 μL. The electrospray ionization(ESI) source in the negative mode and multiple reaction monitoring(MRM) were used for MS quantitative analysis. The content results were analyzed by the hierarchical cluster analysis(HCA) and principal component analysis(PCA) for the evaluation of the quality difference. Eight components showed good linear relationships within their respective concentration ranges(r>0.999), with the average recoveries of 96.85%-103.4% and RSD of 0.52%-2.8%. The analysis results showed that the quality of samples from different batches was different. The samples were classified into three clusters by HCA and PCA. The method is simple, sensitive, accurate, and efficient, and can be used for the quality evaluation of C. decapetala.
