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[Data fusion and multi-components quantitative analysis for identification and quality evaluation of Gentiana
Qin-Qin Wang1,2, Tao Shen3, Zhi-Tian Zuo2
1College of Traditional Chinese Medicine, Yunnan University of Traditional Chinese Medicine, Kunming 650500, China.
Abstract:
The accumulation of secondary metabolites of traditional Chinese medicine (TCM) is closely related to its origins. The identification of origins and multi-components quantitative evaluation are of great significance to ensure the quality of medicinal materials. In this study, the identification of Gentiana rigescens from different geographical origins was conducted by data fusion of Fourier transform infrared (FTIR) spectroscopy and high performance liquid chromatography (HPLC) in combination of partial least squares discriminant analysis; meanwhile quantitative analysis of index components was conducted to provide an accurate and comprehensive identification and quality evaluation strategy for selecting the best production areas of G. rigescens. In this study, the FTIR and HPLC information of 169 G. rigescens samples from Yunnan, Sichuan, Guangxi and Guizhou Provinces were collected. The raw infrared spectra were pre-treated by multiplicative scatter correction, standard normal variate (SNV) and Savitzky-Golay (SG) derivative. Then the performances of FTIR, HPLC, and low-level data fusion and mid-level data fusion for identification were compared, and the contents of gentiopicroside, swertiamarin, loganic acid and sweroside were determined by HPLC. The results showed that the FTIR spectra of G. rigescens from different geographical origins were different, and the best pre-treatment method was SNV+SG-derivative (second derivative, 15 as the window parameter, and 2 as the polynomial order). The results showed that the accuracy rate of low- and mid-level data fusion (96.43%) in prediction set was higher than that of FTIR and HPLC (94.64%) in prediction set. In addition, the accuracy of low-level data fusion (100%) in the training set was higher than that of mid-level data fusion (99.12%) in training set. The contents of the iridoid glycosides in Yunnan were the highest among different provinces. The average content of gentiopicroside, as a bioactive marker in Chinese pharmacopoeia, was 47.40 mg·g⁻¹, and the maximum was 79.83 mg·g⁻¹. The contents of loganic acid, sweroside and gentiopicroside in Yunnan were significantly different from other provinces (P<0.05). In comparison of total content of iridoid glycosides in G. rigescens with different geographical origins in Yunnan, it was found that the amount of iridoid glycosides was higher in Eryuan Dali (68.59 mg·g⁻¹) and Yulong Lijiang (66.68 mg·g⁻¹), significantly higher than that in Wuding Chuxiong (52.99 mg·g⁻¹), Chengjiang Yuxi (52.29 mg·g⁻¹) and Xundian Kunming (46.71 mg·g⁻¹) (P<0.05), so these two places can be used as a reference region for screening cultivation and excellent germplasm resources of G. rigescens. A comprehensive and accurate method was established by data fusion of HPLC-FTIR and quantitative analysis of HPLC for identification and quality evaluation of G. rigescens, which could provide a support for the development and utilization of G. rigescens.
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