Dynamic Modeling Application To Evaluate the Performance of Spathaspora passalidarum in Second-Generation Ethanol Production: Parametric Dynamics and the Likelihood Confidence Region

Abstract

Lignocellulosic materials and agro-industrial residues are essential in a sustainable biorefinery. The effective fermentation of renewable sugars is still an important challenge for an economically viable production of biofuels and biochemicals. This challenge involves biological aspects, such as choosing the microbial platform, and industrial aspects. These aspects can be assessed employing mathematical models to understand the complex synergies between the microorganism and processes. In this work, the performance of the yeast Spathaspora passalidarum was evaluated for the fermentation of xylose and glucose at different proportions, initial concentrations, and initial cell densities using an unstructured–unsegregated kinetic model. The likelihood confidence region, correlations between the parameters, and the convergence of the parameters through the optimization process were identified. It was also possible to identify that πXyl, max, μGlu, max, K’S, Xyl, Y’PEth/SGlu, Y’PEth/SXyl, and Y’X/SGlu were the most representative parameters, due to the high correlation (positive and negative) they have with the other model parameters. It was also possible to identify how initial substrate concentrations affected the specific uptake substrate and ethanol production rates; in this sense, the increase in the glucose concentration causes a decrease in the specific ethanol formation rate at a high concentration of xylose for S. passalidarum cultivated in the conditions proposed by this study.