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OALib Journal期刊
ISSN: 2333-9721
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bp神经网络和遗传算法在乳酸菌发酵参数优化中的应用
DOI: 10.3724/SP.J.1145.2014.00112, PP. 112-116
Keywords: 短乳杆菌l2,γ-氨基丁酸（gaba）,plackett-burman（pb）设计,误差反向传播神经网络（bpn）,遗传算法（ga）
Abstract:
为提高短乳杆菌l2菌株γ-氨基丁酸（gaba）的产量，建立了一个反映因素与产量之间的非线性关系模型.运用plackett-burman设计、中心组合试验设计（ccd）对mrs培养基组成和培养条件进行了优化，筛选出4个影响发酵的关键因素：蛋白胨、葡萄糖、谷氨酸钠、初始ph.在此基础上，采用误差反向传播神经网络（bpn）和遗传算法（ga）确定了4个关键因素的适宜参数：蛋白胨21.185g/l，葡萄糖3.857g/l，谷氨酸钠48.948g/l，初始ph4.05.最终使短乳杆菌l2菌株的gaba产量达到了27.765g/l，比原始mrs培养基的13.452g/l提高了106.4%.研究表明利用bpn-ga方法进行发酵条件优化是一种行之有效的途径.
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