Ashengroph Morahem, Nahvi Iraj, Amini Jahanshir
Department of Biology and Biotechnology, Faculty of Sciences, University of Kurdistan, P.O. Box 416, Sanandaj, Iran.
Iran J Pharm Res. 2013 Summer;12(3):411-21.
For all industrial processes, modelling, optimisation and control are the keys to enhance productivity and ensure product quality. In the current study, the optimization of process parameters for improving the conversion of isoeugenol to vanillin by Psychrobacter sp. CSW4 was investigated by means of Taguchi approach and Box-Behnken statistical design under resting cell conditions. Taguchi design was employed for screening the significant variables in the bioconversion medium. Sequentially, Box-Behnken design experiments under Response Surface Methodology (RSM) was used for further optimization. Four factors (isoeugenol, NaCl, biomass and tween 80 initial concentrations), which have significant effects on vanillin yield, were selected from ten variables by Taguchi experimental design. With the regression coefficient analysis in the Box-Behnken design, a relationship between vanillin production and four significant variables was obtained, and the optimum levels of the four variables were as follows: initial isoeugenol concentration 6.5 g/L, initial tween 80 concentration 0.89 g/L, initial NaCl concentration 113.2 g/L and initial biomass concentration 6.27 g/L. Under these optimized conditions, the maximum predicted concentration of vanillin was 2.25 g/L. These optimized values of the factors were validated in a triplicate shaking flask study and an average of 2.19 g/L for vanillin, which corresponded to a molar yield 36.3%, after a 24 h bioconversion was obtained. The present work is the first one reporting the application of Taguchi design and Response surface methodology for optimizing bioconversion of isoeugenol into vanillin under resting cell conditions.
对于所有工业过程而言,建模、优化和控制是提高生产率和确保产品质量的关键。在本研究中,采用田口方法和Box-Behnken统计设计,在静息细胞条件下研究了嗜冷杆菌属CSW4菌株将异丁香酚转化为香草醛过程参数的优化。田口设计用于筛选生物转化培养基中的显著变量。随后,采用响应面法(RSM)下的Box-Behnken设计实验进行进一步优化。通过田口实验设计从十个变量中筛选出对香草醛产量有显著影响的四个因素(异丁香酚、氯化钠、生物量和吐温80初始浓度)。通过Box-Behnken设计中的回归系数分析,得到了香草醛产量与四个显著变量之间的关系,四个变量的最佳水平如下:异丁香酚初始浓度6.5 g/L、吐温80初始浓度0.89 g/L、氯化钠初始浓度113.2 g/L和生物量初始浓度6.27 g/L。在这些优化条件下,香草醛的最大预测浓度为2.25 g/L。在一式三份的摇瓶研究中对这些因素的优化值进行了验证,在24小时生物转化后,香草醛的平均产量为2.19 g/L,摩尔产率为36.3%。本工作是首次报道在静息细胞条件下应用田口设计和响应面法优化异丁香酚生物转化为香草醛的研究。