Use of Non-linear Empirical Models to Predict the Substrate Degradation, Enzymatic Activity and Cell Growth in a Bioreactor with Aspergillus niger and Sugarcane Bagasse

Abstract

The present study concerns to the evaluation of non-linear empirical logistic models applied to bioprocess modeling. The substrate degradation, as a function of fermentation time, enzymatic activity, as a function of substrate degradation, and cell growth, as a function of dissolved oxygen concentration were modeled using this proposed approach. Different concentrations of sugarcane bagasse (5, 10, 13, 15, and 20 g L−1) were used in a stirred tank bioreactor with Aspergillus niger. The parameter estimation, based on assays with 5, 10, 13 and 20 g L−1 of sugarcane bagasse, was performed by non-linear least square method and one assay with 15 g L−1 of sugarcane bagasse was used for models’ validation. The results obtained allow to conclude that sugarcane bagasse was efficient as carbon source for cellulases production, requiring no other carbon sources. The use of agricultural waste reduces the production costs of cellulases, making de process feasible. The non-linear empirical models proposed this work allowed to predict the variables. The use of these models could be encouraged to evaluate submerged fermentation's characteristics in new experimental works due to its mathematical simplicity and utility. Besides that, they can provide relevant information from the point of view of process control and optimization because they allow to infer about the inflection point which characterizes the maximum rate of variation of the function.