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- W2371269061 abstract "In order to improve the γ-aminobutyric acid(GABA) production of Lactobacillus brevis strain L2 and establish a model refl ecting the nonlinear relationship between the factor and yield, the Plackett-Burman(PB) design and central composite design(CCD) were used to optimize the medium component and culture condition. By analyzing the statistical regression, we found peptone, glucose, MSG and initial pH were the most important factors. On this basis, error back propagation neural network(BPN) and genetic algorithm(GA) were applied to determine the optimum fermentation parameters as peptone 21.185 g/L, glucose 3.857 g/L, MSG 48.948 g/L and initial pH 4.05. Ultimately, the GABA production of strain L2 was up to 27.765 g/L, more than doubling the original yield(13.452 g/L), which indicated that using BPN-GA method to optimized fermentation conditions is an effective way." @default.
- W2371269061 created "2016-06-24" @default.
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- W2371269061 date "2014-01-01" @default.
- W2371269061 modified "2023-09-26" @default.
- W2371269061 title "Optimization of fermentation variables by using artificial neural network Optimization of fermentation variables by using articial neural network model and genetic algorithm" @default.
- W2371269061 hasPublicationYear "2014" @default.
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