响应面法优化熟大黄炮制工艺

目的以多成分综合评分结合响应面法筛选熟大黄的最佳炮制工艺。方法以没食子酸、大黄酚-8-O-β-D葡萄糖苷、芦荟大黄素、大黄酸、大黄素、大黄酚、大黄素甲醚7种成分的综合评分为指标,采用3因素3水平的Box-Behnken响应面试验设计,考察加酒量、闷润时间、蒸制时间因素对熟大黄炮制工艺的影响,筛选最佳炮制工艺参数。结果采用Design Expert 8.05软件对数据进行分析,建立7种成分含量的综合评分与考察因素多元二次回归方程数学模型,预测熟大黄最佳炮制条件为每100 g药材加酒量36.6 mL,闷润时间2.16 h,蒸制时间10.96 h。结合生产实际,将工艺修正为每100 g药材加酒量35 mL,闷润时间2 h,蒸制时间11 h。结论优选的炮制工艺能合理控制熟大黄炮制质量,为制定其饮片的质量标准和临床应用提供了依据。

Optimization of Processing Technology of Prepared Rhubarb by Response Surface Method

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.