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Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC

Gentiana rigescens is a precious herbal medicine in China because of its liver-protective and choleretic effects. A method for the qualitative identification and quantitative evaluation of G. rigescens from Yunnan Province, China, has been developed employing Fourier transform infrared (FT-IR) spect...

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Autores principales: Wu, Zhe, Zhao, Yanli, Zhang, Ji, Wang, Yuanzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152034/
https://www.ncbi.nlm.nih.gov/pubmed/28737713
http://dx.doi.org/10.3390/molecules22071238
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author Wu, Zhe
Zhao, Yanli
Zhang, Ji
Wang, Yuanzhong
author_facet Wu, Zhe
Zhao, Yanli
Zhang, Ji
Wang, Yuanzhong
author_sort Wu, Zhe
collection PubMed
description Gentiana rigescens is a precious herbal medicine in China because of its liver-protective and choleretic effects. A method for the qualitative identification and quantitative evaluation of G. rigescens from Yunnan Province, China, has been developed employing Fourier transform infrared (FT-IR) spectroscopy and high performance liquid chromatography (HPLC) with the aid of chemometrics such as partial least squares discriminant analysis (PLS-DA) and support vector machines (SVM) regression. Our results indicated that PLS-DA model could efficiently discriminate G. rigescens from different geographical origins. It was found that the samples which could not be determined accurately were in the margin or outside of the 95% confidence ellipses. Moreover, the result implied that geographical origins variation of root samples were more obvious than that of stems and leaves. The quantitative analysis was based on gentiopicroside content which was the main active constituent in G. rigescens. For the prediction of gentiopicroside, the performances of model based on the parameters selected through grid search algorithm (GS) with seven-fold cross validation were better than those based on genetic algorithm (GA) and particle swarm optimization algorithm (PSO). For the SVM-GS model, the result was satisfactory. FT-IR spectroscopy coupled with PLS-DA and SVM-GS can be an alternative strategy for qualitative identification and quantitative evaluation of G. rigescens.
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spelling pubmed-61520342018-11-13 Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC Wu, Zhe Zhao, Yanli Zhang, Ji Wang, Yuanzhong Molecules Article Gentiana rigescens is a precious herbal medicine in China because of its liver-protective and choleretic effects. A method for the qualitative identification and quantitative evaluation of G. rigescens from Yunnan Province, China, has been developed employing Fourier transform infrared (FT-IR) spectroscopy and high performance liquid chromatography (HPLC) with the aid of chemometrics such as partial least squares discriminant analysis (PLS-DA) and support vector machines (SVM) regression. Our results indicated that PLS-DA model could efficiently discriminate G. rigescens from different geographical origins. It was found that the samples which could not be determined accurately were in the margin or outside of the 95% confidence ellipses. Moreover, the result implied that geographical origins variation of root samples were more obvious than that of stems and leaves. The quantitative analysis was based on gentiopicroside content which was the main active constituent in G. rigescens. For the prediction of gentiopicroside, the performances of model based on the parameters selected through grid search algorithm (GS) with seven-fold cross validation were better than those based on genetic algorithm (GA) and particle swarm optimization algorithm (PSO). For the SVM-GS model, the result was satisfactory. FT-IR spectroscopy coupled with PLS-DA and SVM-GS can be an alternative strategy for qualitative identification and quantitative evaluation of G. rigescens. MDPI 2017-07-24 /pmc/articles/PMC6152034/ /pubmed/28737713 http://dx.doi.org/10.3390/molecules22071238 Text en © 2017 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
Wu, Zhe
Zhao, Yanli
Zhang, Ji
Wang, Yuanzhong
Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC
title Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC
title_full Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC
title_fullStr Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC
title_full_unstemmed Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC
title_short Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC
title_sort quality assessment of gentiana rigescens from different geographical origins using ft-ir spectroscopy combined with hplc
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152034/
https://www.ncbi.nlm.nih.gov/pubmed/28737713
http://dx.doi.org/10.3390/molecules22071238
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