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 γ 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.