摘要
目的应用正交试验法、R语言结合BP神经网络和遗传算法优化益气活血方药组方丹参中水溶性成分丹酚酸B的提取工艺。方法以丹酚酸B的提取率为指标,采用正交试验设计方法进行提取考察。应用R语言结合BP神经网络及遗传算法对正交试验数据进行目标寻优,从而得到最佳提取工艺条件。结果丹酚酸B的最佳提取工艺条件为12倍体积的水,煎煮3次,每次1 h,提取液加乙醇使醇沉浓度达70%。网络预测值为110.52 mg/g,验证试验平均值为116.174 mg/g,相对误差为4.87%,具有良好的网络预测性。结论本实验建立的丹酚酸B提取工艺的数学模型可用于丹酚酸B提取工艺的分析和预测,同时为实现中药有效成分的目标寻优提供新的参考。
Objective: To optimize the extraction technology of salvianolic acid B in Yiqi Huoxue Decoction with orthogonal experiment,R language,BP neural network and genetic algorithm. Methods: Taking the extraction rate of salvianolic acid B as the index,the orthogonal experimental design method was used to extract and investigate. R language,BP neural network and genetic algorithm were used to optimize the orthogonal experimental data,so as to obtain the optimum extraction process conditions. Results: The optimization of extraction technology was as follows: 12 times of the volume of water were boiled for 3 times,each time for 1h,and the alcohol concentration reached 70%. The network predictive value was 110.52 mg/g;the experimental average value was 116.174mg/g,and the relative error was 4.87%. So it had a good network prediction. Conclusion: This mathematical model can be used to analyze and predict the extraction technology of salvianolic acid B in Yiqi Huoxue Decoction,providing a new reference for screening optimization of Chinese medicine components.
出处
《中国中医急症》
2017年第10期1700-1702,1706,共4页
Journal of Emergency in Traditional Chinese Medicine
基金
浙江省自然科学基金项目(LR16H270001)
浙江省中医药科技计划项目(2017ZB024)
浙江中医药大学校级科研基金项目(重点项目)(2017ZZ09)
关键词
R语言
丹酚酸B
正交设计
神经网络
提取工艺
R language
Salvianolic acid B
Orthogonal design
Neural network
Extraction