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Determination of Total Flavonoids for Paris Polyphylla Var. Yunnanensis in Different Geographical Origins Using UV and FT-IR Spectroscopy

文献类型: 外文期刊

作者: Yang, Yuangui 1 ; Zhao, Yanli 1 ; Zuo, Zhitian 1 ; Wang, Yuanzhong 1 ;

作者机构: 1.Yunnan Acad Agr Sci, Inst Med Plants, Kunming 650200, Yunnan, Peoples R China

期刊名称:JOURNAL OF AOAC INTERNATIONAL ( 影响因子:1.913; 五年影响因子:1.754 )

ISSN: 1060-3271

年卷期: 2019 年 102 卷 2 期

页码:

收录情况: SCI

摘要: Background: Paris polyphylla var. yunnanensis (PPY) is used in the clinical treatment of tumors, hemorrhages, and anthelmintic. Objective: The aim of this study is to determine total flavonoids of PPY in the Yunnan and Guizhou Provinces, China. Methods: In this study, total flavonoids were determined by UV spectrophotometry at first. Then, Fourier transform mid-infrared (FT-IR) based on various pretreatments include standard normal variate (SNV), first derivative (FD), second derivative (SD), Savitzky-Golay (SG), and orthogonal signal correction (OSC) were investigated. In addition, several relevant variables were screened by competitive adaptive reweighted sampling (CARS). The content of total flavonoids and selected variables of FT-IR were used to establish a partial least squares regression for PPY in different regions. Results: The results indicated that CARS was an effective method for decreasing the variable of the database and improving the prediction of the model. FT-IR with pretreatment SNV + OSC + FD + SG had the best performance, with R2 > 0.9 and residual predictive deviation = 3.3515, which could be used for the predictive model of total flavonoids. Conclusions: Those results would provide a fast and robust strategy for the determination of total flavonoids of PPY in different geographical origin. Highlights: Various pretreatments, including SNV, FD, SD, SG, and OSC, were compared; several relevant variables were selected by CARS; and the content of total flavonoids and selected variable were used to establish a partial least squares regression for PPY in different regions.

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