Studies about kinetics and modeling of production parameters for biosurfactants are essential to the development of efficient processes from an economic point of view. In this sense, this work evaluated the performance of four nonstructured models to explain the experimental data for biomass growth, substrate consumption, and rhamnolipid production using glycerol as carbon source and a Pseudomonas aeruginosa strain. The kinetic parameters of each model were estimated using a global search method known as genetic algorithm and numerical discretization of differential equations by the Runge–Kutta 4th order method. The main result of this study showed that the Monod model best represented the experimental data, with μ_max values of 0.06 h⁻¹, K_S of 50.8 g L⁻¹, Y_X/S of 0.43 g g⁻¹, and Y_P/X equal to 0.017 g g⁻¹.

中文翻译：

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鼠李糖脂生物表面活性剂生产的建模：动力学参数的遗传算法估计。

从经济学的角度出发，对生物表面活性剂的动力学和生产参数建模的研究对于开发高效工艺至关重要。在这个意义上，这项工作评估了四个非结构化模型的性能，以解释使用甘油作为碳源和铜绿假单胞菌菌株的生物量增长，底物消耗和鼠李糖脂生产的实验数据。使用称为遗传算法的全局搜索方法和通过Runge–Kutta四阶方法对微分方程进行数值离散化来估计每个模型的动力学参数。本研究的主要结果表明，莫诺模型最好表示的实验数据，与μ_最大的0.06ħ值^-1，K_S为50.8 g L ^-1，Y _{X / S}为0.43 g g ^-1，Y _{P / X}等于0.017 g g ^-1。