分批发酵动力学模型参数的估算

Estimation for Model Parameters of Batch Fermentation Kinetics

本文基于通用的发酵动力学数学模型,导出了用于描述分批发酵特征的解析解。藉助于由FORTRAN-77编写的POWELL优化算法,以赖氨酸分批发酵为例,一举估算出该解析解中所有的发酵动力学参数:μ_(max)、K_s、α、β、Y_G、Y,及m。结果表明:(1) 用模型所得到的计算值与实测值具有较好的一致性;(2) 赖氨酸合成速度取决于微生物的生长速度及浓度。

The analytical solution based on the common mathematical model of fermentation kinetics describing the feature of batch fermentation is deduced. The parameters of the fermentation kinetics in the analytical solution (ie.μ_(maax)、K_(?)、α、β、Y_G、Y_p and m) are estimated at one strike with POWELL optimization algorithm coded in FORTRAN-77. The experimental data, as an example, is quoted from batch lysine fermentation using corynebacterium glutamicum[5].The result shows that: 1) The calculated values of the mathematical model agree with the experimental data well; 2) The synthesis rate of lysine depends on both the growth rate and the concentration of the biomass.