摘要
采用响应面法对γ-聚谷氨酸发酵培养基成分进行优化。首先用Plackett-Burman(PB)设计对培养基中相关影响因素的效应进行评价,筛选出3个有显著影响效应的因素,分别为蛋白胨、谷氨酸及硫酸锰。然后进行最陡爬坡实验逼近最佳响应面区域,最后通过Box-Behnken设计及响应面分析确定了主要影响因素的最佳浓度。在优化的培养基中,γ-聚谷氨酸的产量达到28.91 g/L,比优化前的12.5 g/L提高了2.31倍。
Response surface methodology（RSM） was used to optimize fermentation medium for γ-polyglutamic acid production. Firstly, Plackett-Burman design was used to evaluate the influence of related factors. It showed that three factors playing the important roles in the medium, including peptone, monosodium glutamate and MnSO4·H2O. Secondly, steepest ascent path was adopted to approach the optimal region. Then the Box- Behnken design and response surface analysis were used to determine the optimal levels of the main factors. Under the optimal conditions, the yield of γ-polyglutamic increased 2.31 times form 12.5 g/L to 28.91 g/L.
出处
《食品科技》
CAS
北大核心
2008年第3期45-48,共4页
Food Science and Technology
基金
黑龙江省科技厅十一五重大科技攻关项目(2006G0687-00)
关键词
Γ-聚谷氨酸
响应面法
minitab软件
优化
γ-polyglutamic acid
response surface methodology
minitab software
optimization
