Modelling of solid‐state fermentation over wide operational range for application in process optimization

Abstract

The major drawbacks in large-scale solid-state fermentation processes are related to difficulty in controlling the medium temperature and moisture content, which are variables that directly affect microbial growth and product formation. Several mathematical models have been developed to describe these effects, although none has simultaneously considered distinct growth phases, growth restrictions caused by large temperature variations at several distinct moisture content conditions, and product formation pathways. In this manner, the objectives of this paper were to develop a mathematical model to represent the process under different operational conditions and a model-based optimization procedure to investigate the effects of varying temperature profiles to maximize a (hemi) cellulolytic enzyme production during cultivation of Aspergillus niger under solid state fermentation. The proposed model correlates fungal growth with the CO 2 production rates and with enzymatic production by the Luedeking-Piret function. It was developed with data acquired in a laboratory-scale column-type bioreactor in controlled conditions of aeration, temperature, and inlet air relative humidity. The developed model accurately predicted the respiration profile responses at all temperatures, under the most productive moisture content conditions. Incubation of the culture with the optimized temperature profile improved the enzymatic production, compared to the estimated optimum static temperature. These findings demonstrate the usefulness of this model for the optimization of larger-scale SSF processes.

The optimization of fermentation conditions for Pichia pastoris GS115 producing recombinant xylanase

“…Xylanase is widely used in industrial applications due to its potential application value. However, due to the high cost and low enzyme activity, the application of xylanase is limited . The reduction in the cost of xylanase production is mainly through increasing the expression of xylanase and finding a cheaper and convenient fermentation medium .…”

“…Therefore, only the factors that had a significant influence on the variables could be selected, and the optimal conditions could not be selected. When the p value of the test was less than 0.05, this factor had a significant influence on the variables . Therefore, the eight factors were subjected to the Plackett–Burman test.…”