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Molecules 2017, 22(7), 1238; doi:10.3390/molecules22071238

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

1,2,3
,
1,2
,
1,2
and
1,2,*
1
Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, China
2
Yunnan Technical Center for Quality of Chinese Materia Medica, Kunming 650200, China
3
College of Traditional Chinese Medicine, Yunnan University of Traditional Chinese Medicine, Kunming 650500, China
*
Author to whom correspondence should be addressed.
Received: 9 June 2017 / Accepted: 21 July 2017 / Published: 24 July 2017
View Full-Text   |   Download PDF [1931 KB, uploaded 24 July 2017]   |  

Abstract

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. View Full-Text
Keywords: FT-IR spectroscopy; qualitative; partial least squares discriminant analysis; quantitative; support vector machines regression; Gentiana rigescens FT-IR spectroscopy; qualitative; partial least squares discriminant analysis; quantitative; support vector machines regression; Gentiana rigescens
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wu, Z.; Zhao, Y.; Zhang, J.; Wang, Y. Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC. Molecules 2017, 22, 1238.

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