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首页> 外文期刊>International Journal of Waste Resources >Optimization of Streptomyces sp.A11 Medium Cultivation on Cyclo(Tyrosyl-Prolyl) Production Using the Response Surface Methodology
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Optimization of Streptomyces sp.A11 Medium Cultivation on Cyclo(Tyrosyl-Prolyl) Production Using the Response Surface Methodology

机译:响应面分析法优化链霉菌A.11链霉菌培养基的生产

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摘要

The Response Surface Methodology is a three factorial design which provides the relationship between one or more measured dependent response and a number of input (independent) factors. Response surface methodology was used for optimization of fermentation medium for antibacterial agent cyclo(tyr-pro) production by Streptomyces sp. A11. The optimal response region of the significant factor was predicted by using a second order polynomial model fitted to the results obtained by applying the Central Composite Design (CCD) statistical design. Determination of the best production medium of cyclo(tyr-pro) showed among 6 carbon sources used, dextrin produced the highest cyclo(tyr-pro). Among the five nitrogen sources used, peptone produced the highest cyclo(tyr-pro), and the mineral salts group I produced the highest cyclo(tyr-pro) compared with others. The results of optimization showed that three variables (dextrin as a carbon source, peptone as nitrogen source, and mixture of mineral salts) used showed significantly affected to the activity of cyclo(tyr-pro). The mathematical model used, obtained by the composition of the three variables most optimum were concentration of dextrin was 32.55 g.L-1 , peptone concentration was 11.22 g L-1 , and 8.65 mL of mineral salts. By using the composition of mathematic model, cyclo(tyr-pro) was obtained 51.54 mg L-1 (model expectations) and 50.04 mg L-1 from experiments. The differences of experiment with expectation response value was 2.91%. Using the optimized parameters, the studies demonstrated an increase in the cyclo(tyr-pro) was 2.5 fold from 20 mg L-1 to 50 mg L-1.
机译:响应表面方法是一种三因子设计,提供了一个或多个测量的相关响应与多个输入(独立)因子之间的关系。响应面法用于优化链霉菌生产抗菌剂环(tyr-pro)的发酵培养基。 A11。通过使用适合于通过应用中央复合设计(CCD)统计设计获得的结果的二阶多项式模型,可以预测重要因素的最佳响应区域。确定最佳的环(tyr-pro)生产介质表明,在使用的6种碳源中,糊精产生的环(tyr-pro)最高。在使用的五个氮源中,蛋白p产生的环(tyr-pro)最高,而无机盐I组产生的环(tyr-pro)最高。优化结果表明,所使用的三个变量(糊精为碳源,蛋白p为氮源和矿物盐混合物)显示出对环(tyr-pro)活性的显着影响。通过最优化的三个变量组成所使用的数学模型是:糊精浓度为32.55 g.L-1,蛋白concentration浓度为11.22 g L-1和8.65 mL无机盐。通过使用数学模型的组成,从实验中获得了51.54 mg L-1(模型期望值)和50.04 mg L-1。实验与期望响应值的差异为2.91%。使用优化的参数,研究表明环(tyr-pro)从20 mg L-1增加到50 mg L-1增加了2.5倍。

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