Optimization of Fermentation Medium for the Production of Atrazine Degrading Strain Acinetobacter sp DNS32 by Statistical Analysis System

被引:3
|
作者
Zhang, Ying [1 ]
Wang, Yang [1 ]
Wang, Zhi-Gang [1 ]
Wang, Xi [1 ]
Guo, Huo-Sheng [1 ]
Meng, Dong-Fang [1 ]
Wong, Po-keung [2 ]
机构
[1] NE Agr Univ, Sch Resources & Environm, Harbin 150030, Peoples R China
[2] Chinese Univ Hong Kong, Sch Life Sci, Shatin, Hong Kong, Peoples R China
来源
JOURNAL OF BIOMEDICINE AND BIOTECHNOLOGY | 2012年
基金
中国国家自然科学基金;
关键词
SURFACE; DEGRADATION; BACTERIA;
D O I
10.1155/2012/623062
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Statistical experimental designs provided by statistical analysis system (SAS) software were applied to optimize the fermentation medium composition for the production of atrazine-degrading Acinetobacter sp. DNS32 in shake-flask cultures. A "Plackett-Burman Design" was employed to evaluate the effects of different components in the medium. The concentrations of corn flour, soybean flour, and K2HPO4 were found to significantly influence Acinetobacter sp. DNS32 production. The steepest ascent method was employed to determine the optimal regions of these three significant factors. Then, these three factors were optimized using central composite design of "response surface methodology." The optimized fermentation medium composition was composed as follows (g/L): corn flour 39.49, soybean flour 25.64, CaCO3 3, K2HPO4 3.27, MgSO4.7H(2)O 0.2, and NaCl 0.2. The predicted and verifiable values in the medium with optimized concentration of components in shake flasks experiments were 7.079x10(8) CFU/mL and 7.194 x 10(8) CFU/mL, respectively. The validated model can precisely predict the growth of atrazine-degraing bacterium, Acinetobacter sp. DNS32.
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页数:7
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