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J Biomed Biotechnol ; 2012: 623062, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-23093851

RESUMO

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. DNS(32) 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 K(2)HPO(4) were found to significantly influence Acinetobacter sp. DNS(32) 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, CaCO(3) 3, K(2)HPO(4) 3.27, MgSO(4)·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 7.079 × 10(8) CFU/mL and 7.194 × 10(8) CFU/mL, respectively. The validated model can precisely predict the growth of atrazine-degraing bacterium, Acinetobacter sp. DNS(32).


Assuntos
Acinetobacter/metabolismo , Atrazina/metabolismo , Reatores Biológicos/microbiologia , Meios de Cultura/química , Meios de Cultura/metabolismo , Modelos Biológicos , Modelos Estatísticos , Acinetobacter/classificação , Atrazina/isolamento & purificação , Biodegradação Ambiental , Simulação por Computador , Interpretação Estatística de Dados , Especificidade da Espécie
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