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Optimization of succinic acid fermentation with Actinobacillus succinogenes by response surface methodology (RSM)

机译:响应面法(RSM)优化产琥珀酸放线杆菌对琥珀酸的发酵

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摘要

Succinic acid is considered as an important platform chemical. Succinic acid fermentation with Actinobacillus succinogenes strain BE-1 was optimized by central composite design (CCD) using a response surface methodology (RSM). The optimized production of succinic acid was predicted and the interactive effects between glucose, yeast extract, and magnesium carbonate were investigated. As a result, a model for predicting the concentration of succinic acid production was developed. The accuracy of the model was confirmed by the analysis of variance (ANOVA), and the validity was further proved by verification experiments showing that percentage errors between actual and predicted values varied from 3.02% to 6.38%. In addition, it was observed that the interactive effect between yeast extract and magnesium carbonate was statistically significant. In conclusion, RSM is an effective and useful method for optimizing the medium components and investigating the interactive effects, and can provide valuable information for succinic acid scale-up fermentation using A. succinogenes strain BE-1.
机译:琥珀酸被认为是重要的平台化学品。使用响应面方法(RSM)通过中央复合设计(CCD)优化了琥珀酸放线杆菌菌株BE-1的琥珀酸发酵。预测了琥珀酸的优化生产,并研究了葡萄糖,酵母提取物和碳酸镁之间的相互作用。结果,开发了预测琥珀酸产生浓度的模型。通过方差分析(ANOVA)确认了模型的准确性,并通过验证实验进一步证明了有效性,验证实验表明实际值和预测值之间的百分比误差在3.02%到6.38%之间变化。此外,观察到酵母提取物和碳酸镁之间的相互作用具有统计学意义。总之,RSM是一种优化培养基成分和研究相互作用效应的有效方法,它可以为使用琥珀酸曲霉菌株BE-1的琥珀酸大规模发酵提供有价值的信息。

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