基于BP神经网络的微波辅助提取无花果黄酮工艺优化

刘焕燕; 郑光耀; 王衍彬; 贺亮; 刘于; 程俊文; 李卫旗

doi:10.13386/j.issn1002-0306.2017.19.036

基于BP神经网络的微波辅助提取无花果黄酮工艺优化

1. 浙江省森林资源生物与化学利用重点实验室浙江省林业科学研究院森林食品所
2. 中国林业科学研究院南京林产化学工业研究所
3. 浙江大学生命科学学院

基金项目:

浙江省林业厅省院合作项目(2015SY03)；

详细信息

作者简介:
刘焕燕 (1991-) , 女, 硕士, 研究方向:森林食品精深加工, E-mail:lhy010129@163.com。;

贺亮 (1979-) , 男, 博士, 研究员, 研究方向:森林食品精深加工, E-mail:kite006@163.com。;

中图分类号: TQ28
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- 文章访问数: 250
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出版历程
- 收稿日期: 2017-03-05

Process parameter optimization of microwave assisted extraction of flavonoids from Ficus carica Linn based on BP neural network

Zhejiang Provincial Key Laboratory of Biological and Chemical Utilization of Forest Resources, Zhejiang Forestry Academy
Institute of Chemical Industry of Forest Products, Chinese Academy of Forestry
College of Life Science, Zhejiang University

摘要

摘要: 为优化微波辅助提取无花果黄酮成分的工艺参数,在响应面实验数据的基础上,采用神经网络与遗传算法（BP-GA）相结合的方法优化微波辅助提取无花果黄酮的工艺参数,以提取时间、微波频率、料液比和提取温度作为网络输入,黄酮提取量作为网络输出对微波辅助提取无花果黄酮工艺进行分析模拟。结果表明,利用BP-GA得到微波辅助提取无花果黄酮的最优工艺条件为提取时间22 min,微波频率609 W,料液比1∶30 g/m L,提取温度50℃,此条件下无花果黄酮提取量为14.6610 mg/g;与BP-GA神经网络预测值相对误差为0.15%,表明神经网络优化无花果黄酮提取工艺具有很好的可靠性和实用价值,为其工艺优化提供了可行的途径。
- 神经网络 /
- 微波提取 /
- 无花果 /
- 黄酮 /
- 优化
Abstract: In order to explore the optimum microwave-assisted extraction of flavonoids from the fruits of Ficus carica Linn, Back-Propagation neural network with genetic algorithm ( BP-GA) was used to optimize the process parameters of microwave assisted extraction of flavonoids from Ficus carica Linn based on the response surface experimental data.The simulation analysis of microwave assisted extraction of flavonoids from Ficus carica was carried out by using the extraction time, microwave frequency, the ratio of solid to ethanol and extraction temperature as the input of the network and flavonoids extraction amount as output.The optimized operation condition obtained by the neutral network method was extraction time of 22 min, microwave power of 609 W, the ratio of solid to ethanol of 1 ∶ 30 g/m L and extraction temperature of 50 ℃. And its maximum extraction yield climbed to 14.6610 mg/g under the optimal conditions, the deviation between verified and predicted values of yield was0.15%, which indicated the reliability and practicability in the optimized conditions.The research may provide a new method for optimizing the processing conditions for further development and utilization of the fig organization and build the foundations for better use of natural resources.
- neural network /
- microwave assisted extraction /
- Ficus carica Linn /
- flavonoids /
- optimization

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