LAUSR

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.