基于谱效关联及AHP-EWM综合赋权的Box-Behnken响应面法结合GA-BP多指标优化白芍-甘草药对提取工艺

俞炎彧; 邹纯才; 鄢海燕; 朱宝兰琪; 武于婷; 佘明慧; 叶晨星

doi:10.13748/j.cnki.issn1007-7693.20240001

基于谱效关联及AHP-EWM综合赋权的Box-Behnken响应面法结合GA-BP多指标优化白芍-甘草药对提取工艺

Optimization of Paeoniae Radix Alba-Glycyrrhizae Radix Et Rhizoma Pair Extraction Using Box-Behnken Response Surface Method and GA-BP Based on Spectrum-effect Correlation and AHP-EWM Comprehensive Weighting

摘要

摘要:
目的采用谱效关联及层次分析法-熵权法(analytic hierarchy process-entropy weight method，AHP-EWM)综合赋权的Box-Behnken响应面法结合遗传算法-反向传播(genetic algorithm-backpropagation，GA-BP)神经网络建立白芍-甘草药对的综合评价指标，确定白芍-甘草药对的最佳提取工艺。
方法采用Box-Behnken响应面法考察料液比、超声时间、乙醇浓度对白芍-甘草药对提取工艺的影响，测定白芍-甘草药对提取物干膏得率及其DPPH·清除率，建立其HPLC指纹图谱，选取没食子酸、芍药内酯苷、芍药苷、甘草苷、异甘草苷、甘草素、异甘草素、甘草酸等8种已知入血成分作为白芍-甘草药对提取物的主要质量标志物。采用灰色关联度法分析指纹图谱与DPPH·清除率间的谱效关系，计算关联度，获取关联度校正后的总峰面积和8种指标成分峰面积。采用AHP-EWM法对评价指标进行综合赋权并计算综合评价指标，获取Box-Behnken响应面优化的白芍-甘草药对最佳提取工艺，并与建立的GA-BP神经网络模型所预测的最佳提取工艺比较、验证。
结果料液比、超声时间、乙醇浓度因素下的关联度变化范围分别为0.7174~0.8654、0.6679~0.8721、0.6436~0.8511； Box-Behnken 响应面法和GA-BP神经网络优化的综合评价指标分别为0.98(RSD=3.2%)、0.93(RSD=2.2%)，经对比及验证，确定白芍-甘草药对的最佳提取工艺为料液比1∶40(g·mL⁻¹)，超声时间45 min，乙醇浓度75%。
结论基于谱效关联及AHP-EWM综合赋权的Box-Behnken响应面法结合GA-BP神经网络多指标确定了白芍-甘草药对的最佳提取工艺，也为其他中药提取工艺的优化提供了新思路。

Abstract:
OBJECTIVE To optimize the extraction process of Paeoniae Radix Alba-Glycyrrhizae Radix et Rhizoma pair by the Box-Behnken response surface method based on spectrum-effect correlation and analytic hierarchy process-entropy weight method(AHP-EWM) comprehensive weighting combined with genetic algorithm-backpropagation(GA-BP) neural network.
METHODS The effects of material-liquid ratio, ultrasound time and ethanol concentration on the extraction process of Paeoniae Radix Alba-Glycyrrhizae Radix et Rhizoma pair were investigated by using Box-Behnken response surface methodology. The dry extract yield of Paeoniae Radix Alba-Glycyrrhizae Radix et Rhizoma pair was calculated, its DPPH· clearance rate was measured and its HPLC fingerprint was established. Eight known blood-permeating components, including gallic acid, paeonilactone glucoside, paeoniflorin, glycyrrhizin, isoliquiritin, glycyrrhizin, isoliquiritigenin and glycyrrhetinic acid were selected as the main quality markers of Paeoniae Radix Alba-Glycyrrhizae Radix et Rhizoma pair extracts. The spectrum-effect relationship between fingerprint and DPPH· clearance rate was analyzed using grey correlation method, and the correlation degree was calculated. Peak area in fingerprint was proofread using correlation degree as weight coefficient, and total peak area and the peak area of 8 indicator components were obtained after proofreading. The comprehensive evaluation indicators were calculated after comprehensively weighting the evaluation indicators using AHP-EWM method to obtain the best extraction process of Paeoniae Radix Alba-Glycyrrhizae Radix et Rhizoma pair with Box-Behnken response surface optimization and GA-BP neural network model was established to predict and further validate the extraction process of Paeoniae Radix Alba-Glycyrrhizae Radix et Rhizoma pair.
RESULTS The range of correlation degree changes under the factors of material-liquid ratio, ultrasound time and ethanol concentration was 0.7174–0.8654, 0.6679–0.8721 and 0.6436–0.8511, respectively. The comprehensive evaluation indicators of Box-Behnken response surface method and GA-BP neural network optimization were 0.98(RSD=3.2%) and 0.93(RSD=2.2%), respectively. After comparison and validation, the optimal extraction process for Paeoniae Radix Alba-Glycyrrhizae Radix et Rhizoma pair was determined as follows: the solid-liquid ratio was 1∶40 (g·mL⁻¹), the ultrasound time was 45 min and the ethanol concentration was 75%.
CONCLUSION Box-Behnken response surface method based on spectrum-effect correlation and AHP-EWM comprehensive weighting combined with GA-BP neural network has optimized the extraction process of Paeoniae Radix Alba-Glycyrrhizae Radix et Rhizoma pair, which also provides new ideas for optimizing other traditional Chinese medicine extraction processes.

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