ABSTRACT
OBJECTIVE To establish H PLC fingerprint of Rheum palmatum before and after steaming with wine ，and to determine the contents of 3 differential components. METHODS HPLC method was used to establish the fingerprints of 15 batches of R. palmatum （before wine-steaming ）and prepared rhubarb （after wine-steaming ）and the similarity evaluation was conducted. The chemical pattern recognition analysis was carried out by principal component analysis ，cluster analysis ，partial least squares- discriminant analysis and orthogonal partial least squares-discriminant analysis. The contents of gallic acid ，resveratrol-4′-O- glucoside and resveratrol- 4′-O-（6″-galloyl）-glucoside in 30 batches of samples were determined. RESULTS In the fingerprint study，48 common peaks were demarcated for R. palmatum and 47 for prepared rhubarb as well as 17 common peaks were identified by reference substance. Cluster analysis and principal component analysis showed that R. palmatum derived from Qinghai before and after steaming with wine could be distinguished from those from Sichuan and Gansu. The results of content determination showed that the contents of 3 differential components in R. palmatum derived from Qinghai before and after steaming with wine were higher than those from other two production areas ；the contents of gallic acid in prepared rhubarb derived from those production areas were higher than R. palmatum ；the contents of resveratrol- 4′-O-glucoside and resveratrol- 4′-O- （6″-galloyl）-glucoside in R. palmatum derived from those production areas were higher than prepared rhubarb. CONCLUSIONS Fingerprint and content determination method established in this study can quickly ，scientifically and accurately evaluate the quality of R. palmatum from different producing areas before and after wine steaming ，which provide a basis for the processing specification and quality control of R. palmatum .
ABSTRACT
Objective To screen the best processing technology of prepared Rhubarb by multi- component composite score combined with response surface.Methods The composite score of seven components, i.e., gallicacid, chrysophanol-8-O-β-D-glucopyranoside, aloeemodin, rhein, emodin, chrysophanol, physcion, was taken as indicators. Three factors and three levels of response surface Box-Behnken were used in experimental design. The effects of factors including rice wine volume, moistening time, and steaming time on processing technology of stewed Rhubarb were studied, and the optimized processing parameters were chosen.Results Design Expert 8.05 software was used for data analysis. Multivariate quadratic mathematical model of the sample and examine factors composite score regression equation of seven ingredients content were set up. The best processing conditions of prepared Rhubarb were as following:adding 36.6 mL rice wine into per 100 g raw material;moistening time continued for 2.16 hours;steaming time continued for 10.96 h. According to actual production, the optimized processing conditions of prepared Rhubarb are as following:adding 35 mL rice wine per into 100 g raw material;moistening time continued for 2 h;steaming time continued for 11 h.Conclusion The optimized processing technology can reasonably control the quality of prepared Rhubarb, and provide the basis for the quality standards of its decoction pieces and clinical application.