Optimization of Total Flavonoids from Wild Sophora Davidii(Franch.)Skeels by Response Surface Methodology and Neural Network
The study investigates the optimal extraction process of total flavonoids from Sophora davidii(Franch.)Skeels with single factor experiments,response surface methodology(RSM)analysis and genetic algorithm-neural network(GA-ANN).The extraction time,solid-liquid ratio and ethanol concentration are the variable factors,and the extraction rate of total flavonoids is the response index.The optimal results of response surface experiment are as follows:when ethanol concentration is 60％,solid-liquid ratio is 1∶30(g/mL)and extraction time is 90 min,the extraction rate of total flavonoids is 0.86％.Through using response surface data as learning data,the optimal experimental conditions obtained by genetic optimization using artificial neural network are as follows:solid-liquid ratio,ethanol concentration and extraction time are 1∶20,80％and 2.22 h,respectively.Under these conditions,the average extraction rate of total flavonoids is 0.77％.The results show that the response surface optimization technique is more effective for the extraction of total flavonoids from wild wolfsthorn.
万方数据
维普
