Modeling the microbial growth and temperature profile in a fixed-bed bioreactor

Aiming to scale up and apply control and optimization strategies, currently is required the development of accurate plant models to forecast the process nonlinear dynamics. In this work, a mathematical model to predict the growth of the Kluyveromyces marxianus and temperature profile in a fixed-bed bioreactor for solid-state fermentation using sugarcane bagasse as substrate was built up. A parameter estimation technique was performed to fit the mathematical model to the experimental data. The estimated parameters and the model fitness were evaluated with statistical analyses. The results have shown the estimated parameters significance, with 95 % confidence intervals, and the good quality of process model to reproduce the experimental data.