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Sequential optimization of culture medium composition for extracellular lipase production by Bacillus sphaericus using statistical methods

机译:使用统计方法对球形芽孢杆菌产生细胞外脂肪酶的培养基成分进行顺序优化

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A sequential optimization. strategy with the aid of statistical design of experiments was used to enhance the lipase (triacylglycerol acylhydrolases, EC 3.1.1.3) production by Bacillus sphaericus in submerged cultivation. A Plackett-Burman experimental design was used to evaluate the twelve medium components. Various vegetable oil inducers were tested for lipase production in the second step and the third step was to identify the optimal values of the significant medium components with sesame oil as the inducer using response surface methodology. A predictive model of the combined. effects of the independent variables using response surface methodology and an artificial neural[ network was proposed. Unstructured kinetic models, a logistic model and a Luedeking-Piret model, were used to describe the cell mass and lipase production respectively. The significant variables affecting lipase production were found to be glucose, olive oil, peptone, NaCl and MnSO4 center dot H2O. Sesame oil was found to be the best inducer for lipase production by Bacillus sphaericus. The maximum lipase activity of 4.45 U mL(-1), which was 1.5 times the maximum activity obtained in the Plackett-Burman experimental trials, was obtained at the optimum combination of medium constituents containing 12.695 g L-1 glucose, 13.161 mL L-1 sesame oil, 9.947 g L-1 peptone, 3.25 g L-1 NaCl, 0.5917 g L-1 MnSO4 center dot H2O and other insignificant components at the fixed level. The statistical design of experiments offers an efficient methodology to identify the significant variables and to optimize the factors with a minimum number of experiments for lipase production by Bacillus sphaericus. (c) 2007 Society of Chemical Industry.
机译:顺序优化。在实验统计设计的帮助下,该策略被用于增强芽孢杆菌在水下培养中产生的脂肪酶(三酰基甘油酰基水解酶,EC 3.1.1.3)。 Plackett-Burman实验设计用于评估十二种培养基成分。在第二步中测试了各种植物油诱导剂的脂肪酶生成,第三步是使用响应表面方法确定以芝麻油为诱导剂的重要培养基成分的最佳值。组合的预测模型。提出了利用响应面法和人工神经网络对自变量的影响。使用非结构动力学模型,逻辑模型和Luedeking-Piret模型分别描述细胞质量和脂肪酶产生。发现影响脂肪酶产生的重要变量是葡萄糖,橄榄油,蛋白p,NaCl和MnSO4中心点H2O。芝麻油被发现是球形芽孢杆菌产生脂肪酶的最佳诱导剂。在包含12.695 g L-1葡萄糖,13.161 mL L-的培养基成分的最佳组合下,获得的最大脂肪酶活性为4.45 U mL(-1),是Plackett-Burman实验中获得的最大活性的1.5倍。 1麻油,9.947 g L-1蛋白ept,3.25 g L-1 NaCl,0.5917 g L-1 MnSO4中心点H2O和其他无关紧要的成分。实验的统计设计提供了一种有效的方法,可通过最少数量的球形芽孢杆菌产脂肪酶实验来识别重要变量并优化因子。 (c)2007年化学工业协会。

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