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Optimum culture medium composition for lipopeptide production by Bacillus subtilis using response surface model-based ant colony optimization

机译:枯草芽孢杆菌基于响应面模型的蚁群优化生产脂肽的最佳培养基组成

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Central composite rotatable design (CCRD) of experiments was used to obtain data for Lipopeptide and Biomass concentrations from fermentation medium containing the following five components: glucose,monosodium glutamate, yeast extract,MgSO 4 ·7H 2 O, and K 2 HPO 4 . Data was used to develop a second order regression response surface model (RSM) which was coupled with ant colony optimization (ACO) to optimize the media compositions so as to enhance the productivity of lipopeptide. The optimized media by ACO was found to yield 1.501 g/L of lipopeptide concentration which was much higher compared to 1.387 g/L predicted by Nelder–Mead optimization (NMO). The optimum from ACO was validated experimentally. RSM-based ACO is thus shown to be an effective tool for medium optimization of biosurfactant production.
机译:实验的中央复合可旋转设计(CCRD)用于从含有以下五种成分的发酵培养基中获取脂肽和生物质浓度的数据:葡萄糖,谷氨酸钠,酵母提取物,MgSO 4·7H 2 O和K 2 HPO 4。数据用于建立二阶回归响应表面模型(RSM),再结合蚁群优化(ACO)来优化培养基成分,从而提高脂肽的生产率。发现通过ACO优化的培养基可产生1.501 g / L的脂肽浓度,远高于Nelder–Mead优化(NMO)预测的1.387 g / L。通过实验验证了ACO的最佳选择。因此,基于RSM的ACO被证明是用于优化生物表面活性剂生产的有效工具。

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