College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P. R. China.
J Sep Sci. 2017 May;40(9):2062-2070. doi: 10.1002/jssc.201601259. Epub 2017 Apr 24.
The extraction of linarin from Flos chrysanthemi indici by ethanol was investigated. Two modeling techniques, response surface methodology and artificial neural network, were adopted to optimize the process parameters, such as, ethanol concentration, extraction period, extraction frequency, and solvent to material ratio. We showed that both methods provided good predictions, but artificial neural network provided a better and more accurate result. The optimum process parameters include, ethanol concentration of 74%, extraction period of 2 h, extraction three times, solvent to material ratio of 12 mL/g. The experiment yield of linarin was 90.5% that deviated less than 1.6% from that obtained by predicted result.
采用乙醇从菊花中提取滨蒿内酯。采用响应面法和人工神经网络两种建模技术对提取过程参数，如乙醇浓度、提取时间、提取次数、溶剂与物料比等进行优化。结果表明，两种方法均能提供良好的预测，但人工神经网络提供了更好、更准确的结果。最佳工艺参数为乙醇浓度 74%、提取时间 2 h、提取 3 次、溶剂与物料比 12 mL/g。滨蒿内酯的实验收率为 90.5%，与预测结果相差小于 1.6%。
