Model-Based Experimental Design to Estimate Kinetic Parameters of the Enzymatic Hydrolysis of Lignocellulose

A model-based nonlinear optimum experimental design technique has been implemented to estimate the kinetic parameters of the lignocellulose enzymatic hydrolysis process, mainly focused on the calculation of reaction rate constants and activation energy parameters. Analysis of the reaction was based on the mechanism of simultaneous consecutive enzymatic reactions of cellulose and hemicellulose to produce sugar-rich syrups. A mathematical model was developed as a set of ordinary differential equations (ODEs). To enhance the parameter estimation process, a control variable that directly affects the response of the system (temperature) was included to predict the state variable profiles over a broad experimental range. To determine the optimal profiles for the temperature gradient, optimal control problems were set up and solved numerically. A comparison between model prediction profiles and experimental data was performed to adjust kinetic parameter estimation to real process features. The results show that nonlinear optimum experiments enhance the quality of the estimates because of the optimality criterion included in the objective function and because the embedded nonlinear behavior is explicitly addressed.