Determination of total steroid saponins in different species of Paris using ftir combined with chemometrics

Abstract

The saponins of Paris spp. have antimicrobial, immune-stimulating, and antitumor biological properties. In this investigation, FTIR and ultra-HPLC (UHPLC) were used for the determination of total steroid saponins in different species of Paris from Yunnan Province, China. A 52-sample calibration set and a 26-sample validation set for partial least-squares regression (PLSR) and support vector machine regression (SVMR) combined with FTIR and UHPLC were investigated. The optimal parameters C and g were screened by a grid search with a sevenfold cross-validation. The results indicate that pretreatment with the combination of standard normal variate, second derivative, and orthogonal signal correction had the best performance. When comparing the SVMR and PLSR models, linear PLSR had better performance than nonlinear SVMR for the determination of total steroid saponins in different species of Paris. The highest total saponin content was found in P. axialis from Baoshan City (40.92 ± 9.06 mg/g). These results demonstrate that this approach would provide a fast and robust strategy for the QC of Paris in further analyses.