Variable Selection Method in the NIR Quantitative Analysis Model of Total Saponins in Red Ginseng Extract

Yiqi Fumai Lyophilized Injectionis a new type of freeze-dried powder injection made of red ginseng, ophiopogon japonicus and schisandrachinensis. The total saponin content of red ginseng extract is an important quality control index in the production process of Yiqi Fumai lyophilized injection. The results of traditional analysis methods lag far behind, which cannot feedback the quality information of the production process timely, it is necessary to establish a rapid method for the determination of total saponin. As a process monitoring tool, near-infrared spectroscopy (NIR) has been widely used in the quality control of traditional Chinese medicine. How to extract the effective information from the spectrum with weak absorption and serious overlapping of spectral regions is the key to improve the monitoring veracity. Model population analysis (MPA) provides a new idea for variable selection method. In this study, the near-infrared spectrum data of 55 batches red ginseng extracts were collected. Themulti scattering correction ( MSC) method was used to preprocess the spectrum data, the variable screening methods derived from MPA, such as random frog (RF) , competitive adaptive reweighted sampling (CARS) , variable combination population analysis (VCPA), VCPA combined with IRIV (iterative retaining information variables) and the variable selection method of OPUS were respectively used in the establishment of PLS quantitative analysis model. The results showed that the R-c of model established by OPUS, CARS-PLS and RF-PLS were only 0. 601 3, 0. 565 3 and 0. 644 0, respectively. The R-c of model established by VCPA-PLS was 0. 951 2, which was the highest, but this model did not present good robustness. The model established by VCPA-IRIV-PLS had the best prediction effects; its R-c was 0. 928 , RSEP% was 7. 99%.