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首页> 外文期刊>Journal of Advances in Biology & Biotechnology >Statistical Optimization of Alkaline Protease Production Using Isolated Strain by Submerged Fermentation
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Statistical Optimization of Alkaline Protease Production Using Isolated Strain by Submerged Fermentation

机译：发酵法分离菌株生产碱性蛋白酶的统计优化

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Aim: Optimization of alkaline protease production using a newly isolated strain Alternaria sp. by submerged fermentation. The production of inexpensive proteolytic enzymes not only solves environmental problems, but also promotes the economic value and utilization of waste treatment. Study Design: Response Surface Methodology (RSM) was employed to optimize the environmental parameters to enhance protease production. Place and Duration of Study: Department of Food technology and Biochemical Engineering, Jadavpur University, Kolkata, West Bengal, India between July 2014 and September 2014. Methodology: The isolated culture Alternaria sp. was grown on modified Czapek-Dox media. The statistical design RSM was utilized to optimize the parameters: Volume of medium, temperature, time, age of inoculum and agitation showed significant influence on enzyme production. The data on alkaline protease production was processed by Analysis Of Variance (ANOVA). The mathematical relationship of independent variables and second order polynomial equation was used for the analysis of protease production. Results: RSM was employed to optimize environmental factors for production of alkaline protease. The highest specific activity was obtained using 40 ml of medium, inoculated at 30°C for 9 days at 120 rpm using 7 days old culture. However the maximum biomass production was obtained with 40 ml medium, 30°C temperature, 5 days of fermentation, 140 rpm agitation using 7 days old culture and it was 7.76 mg/ml which was very close to 7.78 mg/ml predicted by Box-Behnken design (RSM). Conclusion: The specific activity which was found to be 200 U/mg optimized by one-factor at a time, was later on calculated as 615 U/mg optimizing the same with the statistical approach. Thus it can be concluded that the optimization of Alkaline protease production gave significant higher specific activity when carried out with the process parameters non-individually.
机译：目的：使用新分离的菌株Alternaria sp。优化碱性蛋白酶生产。通过深层发酵。生产廉价的蛋白水解酶不仅解决了环境问题，而且提高了废物处理的经济价值和利用率。研究设计：采用响应面法（RSM）来优化环境参数，以提高蛋白酶的产量。研究地点和时间：2014年7月至2014年9月，印度西孟加拉邦加尔各答，贾达普布尔大学食品技术与生化工程系。方法：分离培养的链格孢菌。在改良的Czapek-Dox培养基上生长。利用统计设计RSM来优化参数：培养基体积，温度，时间，接种物的年龄和搅拌对酶的产生有显着影响。通过方差分析（ANOVA）处理关于碱性蛋白酶产生的数据。使用自变量与二阶多项式方程的数学关系来分析蛋白酶的产生。结果：采用RSM优化了碱性蛋白酶生产的环境因子。使用40 ml的培养基获得最高的比活，使用7天的培养物在30℃下以120 rpm的转速接种9天。但是，使用40天的培养基，30°C的温度，发酵5天，使用7天的培养液进行140 rpm搅拌可获得最大的生物量产量，为7.76 mg / ml，非常接近Box-Box预测的7.78 mg / ml。 Behnken设计（RSM）。结论：通过一次因素一次发现200 U / mg的比活，随后通过统计学方法计算为615 U / mg的比活。因此可以得出结论，当非单独使用工艺参数进行时，碱性蛋白酶生产的最优化产生明显更高的比活性。

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