神经网络-遗传算法优化细脚拟青霉多糖超声提取工艺  

Study on the optimization of ultrasonic assisted conditions of Paecilomyces tenuipes polysaccharide using ANN-GA

作　　者：李钰 李雅雅 王鑫玥 马巍 方明红 刘彦 侯寒进 董媛 LI Yu;LI Yaya;WANG Xinyue;MA Wei;FANG Minghong;LIU Yan;HOU Hanjin;DONG Yuan(School of Medical Laboratory,Jilin Medical University,Jilin City,Jilin Province,132013,China)

机构地区：[1]吉林医药学院检验学院,吉林吉林132013

出　　处：《吉林医药学院学报》2019年第1期15-17,共3页Journal of Jilin Medical University

摘　　要：目的优化超声波法提取细脚拟青霉胞内多糖。方法采用单因素法和基于遗传算法的神经网络法(ANN-GA)考察超声功率、超声时间和固液比与细脚拟青霉多糖提取率之间的非线性关系。结果最终最佳提取条件为:固液比1∶73(g∶m L),376 W提取385 s;多糖得率最高达2. 37%,比未优化之前提取率提高了3倍。结论 ANN-GA法优化细角拟青霉超声波法提取多糖,是有效可行的。Objective To optimize the ultrasonic extractitve conditions of Paecilomyces tenuipes polysaccharides.Methods The single-factor test,artificial neural network(ANN)and genetic algorithm(GA)were used to investigate the extracting conditions,respectively.Results The best extraction conditions were extraction power 376 W,extraction time 385 s and solid/solvent ratio 1∶73(g∶mL).The yield of polysaccharide was 2.37%,which was enhanced by three times.Conclusion Optimization of ultrasonic extraction of Paecilomyces tenuipes polysaccharide using ANN-GA is feasible.

关 键 词：神经网络 遗传算法 细脚拟青霉 多糖 

分 类 号：O657.33[理学—分析化学]