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Multi-Component Analysis of Ilex Kudingcha C. J. Tseng by a Single Marker Quantification Method and Chemometric Discrimination of HPLC Fingerprints
The quantitative analysis of multiple components with a single marker (QAMS) method was firstly established for simultaneous determination of 18 active components in Ilex kudingcha C. J. Tseng by HPLC. Using rutin, isochlorogenic acid A and kudinoside A as internal refererence substances (IRS), comp...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6017665/ https://www.ncbi.nlm.nih.gov/pubmed/29642536 http://dx.doi.org/10.3390/molecules23040854 |
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author | Yi, Huan Zhou, Jie Shang, Xueying Zhao, Zhongxiang Peng, Qian Zhu, Mingjuan Zhu, Chenchen Lin, Chaozhan Liu, Qide Liao, Qiongfeng Zhang, Lei |
author_facet | Yi, Huan Zhou, Jie Shang, Xueying Zhao, Zhongxiang Peng, Qian Zhu, Mingjuan Zhu, Chenchen Lin, Chaozhan Liu, Qide Liao, Qiongfeng Zhang, Lei |
author_sort | Yi, Huan |
collection | PubMed |
description | The quantitative analysis of multiple components with a single marker (QAMS) method was firstly established for simultaneous determination of 18 active components in Ilex kudingcha C. J. Tseng by HPLC. Using rutin, isochlorogenic acid A and kudinoside A as internal refererence substances (IRS), compatibility results showed that the relative correction factors (RCFs) of all compounds showed good reproducibility under different chromatographic conditions. On the basis of previous studies, the accuracy of the QAMS method was systematically evaluated by investigating the influences of curve intercept, analytes and IRS concentration. The results showed that the concentration (especially at low level) of analytes and curve intercept were the major influencing parameters for the LRG-QAMS method (LRG = linear regression), whereas the influence of IRS concentration seemed more apparent in terms of the AVG-QAMS method (AVG = average). The two approaches were complementary with each other. In addition, hierarchical clustering analysis (HCA), principal components analysis (PCA) and similarity analysis (SA) were performed to differentiate and classify the samples based on the contents of 18 marker compounds. The results of the different chemometric analyses were completely consistent with each other, and could be supported by the quantification results. |
format | Online Article Text |
id | pubmed-6017665 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-60176652018-11-13 Multi-Component Analysis of Ilex Kudingcha C. J. Tseng by a Single Marker Quantification Method and Chemometric Discrimination of HPLC Fingerprints Yi, Huan Zhou, Jie Shang, Xueying Zhao, Zhongxiang Peng, Qian Zhu, Mingjuan Zhu, Chenchen Lin, Chaozhan Liu, Qide Liao, Qiongfeng Zhang, Lei Molecules Article The quantitative analysis of multiple components with a single marker (QAMS) method was firstly established for simultaneous determination of 18 active components in Ilex kudingcha C. J. Tseng by HPLC. Using rutin, isochlorogenic acid A and kudinoside A as internal refererence substances (IRS), compatibility results showed that the relative correction factors (RCFs) of all compounds showed good reproducibility under different chromatographic conditions. On the basis of previous studies, the accuracy of the QAMS method was systematically evaluated by investigating the influences of curve intercept, analytes and IRS concentration. The results showed that the concentration (especially at low level) of analytes and curve intercept were the major influencing parameters for the LRG-QAMS method (LRG = linear regression), whereas the influence of IRS concentration seemed more apparent in terms of the AVG-QAMS method (AVG = average). The two approaches were complementary with each other. In addition, hierarchical clustering analysis (HCA), principal components analysis (PCA) and similarity analysis (SA) were performed to differentiate and classify the samples based on the contents of 18 marker compounds. The results of the different chemometric analyses were completely consistent with each other, and could be supported by the quantification results. MDPI 2018-04-09 /pmc/articles/PMC6017665/ /pubmed/29642536 http://dx.doi.org/10.3390/molecules23040854 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yi, Huan Zhou, Jie Shang, Xueying Zhao, Zhongxiang Peng, Qian Zhu, Mingjuan Zhu, Chenchen Lin, Chaozhan Liu, Qide Liao, Qiongfeng Zhang, Lei Multi-Component Analysis of Ilex Kudingcha C. J. Tseng by a Single Marker Quantification Method and Chemometric Discrimination of HPLC Fingerprints |
title | Multi-Component Analysis of Ilex Kudingcha C. J. Tseng by a Single Marker Quantification Method and Chemometric Discrimination of HPLC Fingerprints |
title_full | Multi-Component Analysis of Ilex Kudingcha C. J. Tseng by a Single Marker Quantification Method and Chemometric Discrimination of HPLC Fingerprints |
title_fullStr | Multi-Component Analysis of Ilex Kudingcha C. J. Tseng by a Single Marker Quantification Method and Chemometric Discrimination of HPLC Fingerprints |
title_full_unstemmed | Multi-Component Analysis of Ilex Kudingcha C. J. Tseng by a Single Marker Quantification Method and Chemometric Discrimination of HPLC Fingerprints |
title_short | Multi-Component Analysis of Ilex Kudingcha C. J. Tseng by a Single Marker Quantification Method and Chemometric Discrimination of HPLC Fingerprints |
title_sort | multi-component analysis of ilex kudingcha c. j. tseng by a single marker quantification method and chemometric discrimination of hplc fingerprints |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6017665/ https://www.ncbi.nlm.nih.gov/pubmed/29642536 http://dx.doi.org/10.3390/molecules23040854 |
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