Study on the Characteristic Specturm and Color Change of Steamed Rehmanniae Radix Praeparata and Optimization of Processing Technology

  OBJECTIVE  To optimize the processing technique of Shudihuang (Rehmanniae Radix Praeparata, RRP) by Box-Behnken response surface model based on the change rule of characteristic spectrum and color.

  METHODS  Multivariate statistical methods including Pearson correlation analysis, cluster analysis, principal component analysis (PCA) and orthogonal partial least squares-discriminate analysis (OPLS-DA) were used to analyze the color changes and the peak area changes of the characteristic spectrum in the processing of RRP, and to screen key quality markers (Q-markers) for RRP. Q-markers were used to evaluate the effects of steaming time, drying temperature, and drying time on the quality of RRP, and the Box-Behnken response surface method was used to determine the optimal processing technique.

  RESULTS  The established characteristic spectrum of Shengdihuang (Rehmanniae Radix, RR) and RRP marked 18 and 20 common peaks, respectively. Among them, peak 19(5-HMF)was a new chemical component produced after the processing of RR. There was a significant difference in color (ΔE^* > 12) after 2 h of evaporation, and the peak area of each characteristic was significantly different from RR. The ΔE^* of RRP at different steaming time points was 0.28~4.76, indicating that the color difference could not be recognized by the naked eye. RRP from different processing points could be clustered into 3 groups with chromaticity values L^*, a^*, b^*, E^* as variables, and RRP from different processing points could be clustered into 4 groups with chromaticity values L^*, a^*, b^*, E^*, and iridoid glycosides, phenylethanolglycosides and 5-HMF as variables. The optimum processing technique of steamed RRP was as follows: moistening water was 0.3 times the amount of medicinal material, moistening time was 24 h, steaming time was 2.17 h, drying temperature was 61.15 ℃, and drying time was 13.73 h.

  CONCLUSION  The established response surface model is accurate and predictable, the established characteristic spectrum and the optimized processing method of RRP are stable and feasible. Combining with the color change rule of the processing process, it can provide a reference for comprehensive utilization and the quality control of RRP.