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甘草酸提取工艺的优化研究
引用本文:李剑君,国蓉,莫晓燕.甘草酸提取工艺的优化研究[J].食品科学,2006,27(12):326-330.
作者姓名:李剑君  国蓉  莫晓燕
作者单位:西安交通大学生命科学与技术学院生物医学信息工程教育部重点实验室; 西安工业学院光电学院;
基金项目:西安交通大学自然科学基金资助项目(xjj200411)
摘    要:以甘草中主要生理活性物质甘草酸的超声提取工艺为研究对象,在传统的正交试验方法的基础上,用人工神经网络方法进行优化,获得了超声提取甘草酸的优化工艺条件,即乙醇浓度40%、超声次数4次、提取温度20℃、提取时间20min、超声频率13kHz、固液比为1:10。该优化工艺条件操作简便、能耗低、提取率高,是合理可行的。

关 键 词:甘草酸    超声辅助提取    提取工艺    神经网络  
文章编号:1002-6630(2006)12-0326-05
收稿时间:2006-08-16
修稿时间:2006-08-16

Study on Optimization of Technology for Extracting Glycyrrhizic Acid from Liquorice
LI Jian-jun,GUO Rong,MO Xiao-yan.Study on Optimization of Technology for Extracting Glycyrrhizic Acid from Liquorice[J].Food Science,2006,27(12):326-330.
Authors:LI Jian-jun  GUO Rong  MO Xiao-yan
Affiliation:1.Key Laboratory of Biomedical Information Engineering of Ministry of Education; School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China;2.School of Optoelectronical Engineering, Xi’an Institute of Technology, Xi’an 710032, China
Abstract:The supersonic-assisted extracting technology of glycyrrhizic acid from liquorice was researched. Combined artificial neural network(ANN) with traditional orthogonal design, a new method of test data analyzing, processing and optimizing was put forward. With this method the test information can be fully used, the change regularity of each factor can be analyzed and the optimum combination can be found. By using this new method, the optimum extraction condition was obtained as follows: ethanol concentration 40%, supersonic time 50min, extracting temperature 20℃, extracting time 20min, supersonic frequency 13kHz and ratio of solid-liquid 1:10. Optimizing extraction technology by ANN, the experimental information could be dig out completely. Applying this preferable extracting technology, the costs of production was reduced, the energy consuming was decreased, and the glycyrrhizic acid content was increased. The results showed that this new method was reasonable and practicable.
Keywords:glycyrrhizic acid  supersonic -assisted extraction  extracting technology  artificial neural network
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