中文摘要：

目的多目标优化养阴通脑颗粒组方中3种黄酮类指标成分的提取工艺。方法以养阴通脑颗粒组方中葛根素、毛蕊异黄酮和芒柄花素的提取率为检测指标,采用4因素3水平的正交试验设计方法进行提取工艺考察。通过R语言结合熵权法赋予权值,建立BP神经网络模型,再利用遗传算法对网络进行目标寻优,从而得到养阴通脑颗粒组方中葛根素、毛蕊异黄酮和芒柄花素的最佳提取工艺。结果养阴通脑颗粒组方中葛根素、毛蕊异黄酮和芒柄花素的最优工艺条件为乙醇体积分数85%、提取时间1.5 h、提取温度80℃、乙醇用量25倍,模型综合评价预测值为0.389,而实验所得的平均综合评价值为0.394,相对误差为1.27%,表明具有良好的网络预测性。结论结合所得3个指标成分的提取率和提取工艺的可操作性、可重复性,建立的数学模型可用于对养阴通脑颗粒组方中葛根素、毛蕊异黄酮和芒柄花素的提取工艺进行分析和预测,为实现中药有效成分多目标寻优提供了新的参考。

英文摘要：

Objective Multi-objectively optimizing the extraction technology for three indicator flavonoids in the formula of Yangyin Tongnao Granules.Methods Taking the extraction yield of puerarin,calycosin,and formononetin in the formula of Yangyin Tongnao Granules as the detecting indicators,the extraction technology was investigated by 4 factors 3 levels orthogonal test design method.Using R language,combining the entropy weight method to give weight,and establishing the BP neural network model,using the genetic algorithm to target the optimization of network,so as to get the best extraction technology for puerarin,calycosin,and formononetin.Results The optimization of extraction technology was as follows：ethanol concentration was 85%,extraction time was1.5 h,extraction temperature was 80 °C,and ethanol dosage was 25 times.Under the condition,the predictive value of model comprehensive evaluation was 0.389,the predictive value of the average comprehensive evaluation obtained in the experiment was0.394,the relative error was 1.27%.So it had a better network prediction.Conclusion Combining the feasibility and repeatability of the extraction yield and extraction technology for the three index component to establish the mathematical model for analyzing and predicting the extraction technology of puerarin,calycosin,and formononetin in the formula of Yangyin Tongnao Granules and providing a new reference to realize the multi-objective optimization of the extraction technology for the active constituents in Chinese materia medica.