Geographic origin identification and rapid determination of four constituents of Gentiana rigescens by FTIR combined with chemometrics. (21st February 2019)

• Record Type: Journal Article
• Authors: Zhao, Yanli; Yuan, Tianjun; Zhang, Ji; Wang, Yuanzhong
• Is Part Of: Journal of chemometrics. Volume 33:Number 4(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-02-21
• Subjects: Gentiana rigescens -- Monte Carlo uninformative variable elimination -- partial least squares discriminant analysis -- partial least squares regression -- t test; Chemistry -- Mathematics -- Periodicals; Chemistry -- Statistical methods -- Periodicals; 542.85
• DOI: 10.1002/cem.3115
• Languages: English
• ISSNs: 0886-9383

Abstract

Abstract: Gentiana rigescens is one of the most important traditional Chinese medicines because of its therapeutic effects in protecting the liver and promoting bile discharge, anti‐hypertension, and spasm and pain relief. To enhance quality control, a comprehensive assessment of G. rigescens from different geographic origins by Fourier‐transform infrared (FTIR) in combination with chemometrics was conducted. Through pretreatment by the second derivative, spectrum standard deviation and Monte Carlo uninformative variable elimination (MC‐UVE), the characteristic FTIR spectra were selected and an identification model of the different geographic origins of G. rigescens was built by partial least squares discriminant analysis (PLS‐DA). The validation results showed that the accuracy rates of the model were 100%, 97.22%, and 100% for samples from Yunnan, Guizhou, and Sichuan, respectively. On the basis of the correlation between characteristic spectral points and the contents of swertiamarin, gentiopicroside, sweroside, and loganic acid, quantitative models were established by partial least squares regression (PLSR). The measured and predicted values were not significantly different as assessed through the paired t test ( p > 0.05). Additionally, the characteristic spectra were interpreted, and 93 common peaks were selected. FTIR analysis combined with chemometric methods could accurately identify the different geographic origins of G. rigescens and rapidly predict the content of swertiamarin, gentiopicroside, sweroside, and loganic acid, thus providing a comprehensive method of evaluating traditional Chinese medicines. Highlights: The characteristic Fourier‐transform infrared (FTIR) spectra of Gentiana rigescens were selected by Monte Carlo uninformative variable elimination and 93 common peaks were selected and interpreted. The identification model for G. rigescens from different geographic origins was built by partial least squares discriminant analysis. On the basis of the correlation between characteristic spectral points and content of swertiamarin, gentiopicroside, sweroside, and loganic acid, the quantitative models were established by partial least squares regression.