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作 者:王莹[1]
机构地区:[1]青岛农业大学食品科学与工程学院,山东青岛266109
出 处:《青岛农业大学学报(自然科学版)》2014年第1期36-40,44,共6页Journal of Qingdao Agricultural University(Natural Science)
基 金:青岛农业大学高层次人才启动基金(31347)
摘 要:利用正交试验、响应面法(RSM)、人工神经网络(ANN)与遗传算法(GA)联合等三种方法对比优化了RC2-3的发酵产酶条件。正交试验结果表明,对产酶影响显著的因素有发酵温度、pH值、摇床转速和培养时间,当发酵温度25℃,初始pH5.0,摇床转速180r/min,培养时间48h,能够获得最大酶活力186.36±6.40U/mL;RSM法结果表明,当发酵温度为28.9℃,pH值为7.8,摇床转速149.5r/min,培养时间56h时,能够获得最高酶活力195.84±5.48U/mL,所建立的方程的决定系数为0.969;ANN与GA联合的优化方法结果表明,当发酵温度为26.4℃,pH6.9,摇床转速174r/min,培养时间55h的条件下,能够获取最高酶活力200.42±6.93U/mL,ANN模型与实验数据的决定系数高达0.986,能够更好地反映发酵条件对产酶的影响,值得推广应用。Optimization of fermentation conditions for fucoidanase production by a newly isolated bacterium RC2-3 was studied using orthogonal test ,response surface methodology (RSM ) and artificial neural net-work (ANN) linked genetic algorithm (GA) .The four significant conditions for fucoidanase production found by orthogonal test were temperature ,pH ,shaking speed and culture time among six variables ,and the highest fucoidanase activity of 186 .36 ± 6.40 U/mL were obtained at the following conditions of 25℃ ,pH5.0 ,180r/min and cultivated for 48h. Further ,RSM and ANN linked GA were also used for op-timization of these four variables. The results of RSM showed that the optimal conditions for fucoidanase production were 28.9℃ ,pH7.8 ,149.5r/min ,and cultivated for 56h ,then the highest fucoidanase activity of 195.84 ± 5.48U/mL would be obtained .The determination coefficient (R2 ) was 0.969 ,which illustra-ted a good fit of the regression model with the experiment al data .The results showed that ANN linked GA was the most efficient method (R2 =0.986) among the three optimization methods ,and the maximum fucoidanase activity of 200.42 ± 6.93U/mL was obtained under the conditions of 26.4℃ ,pH6.9 ,174r/min and cultivated for 55h .ANN linked GA was valuable for the process optimization in the similar area .
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