Multi-Objective Optimization of Solid State Fermentation Process

Solid state fermentation is among the key processes to produce enzymes and which can serve various purposes in the food and agricultural industries, etc. Modeling of bioreactors also plays an important role in understanding the bio process, design, and development of process. The essential parameters best suited for a particular case of enzyme production were recognized in this work. The simulated mathematical model predicts the production of protease enzyme by Aspergillus niger under various operating conditions and values of parameters. Evolutionary multi-objective optimization (MOO), in this study, is used for MOO of the solid state fermentation process considering two case studies of two objectives (maximization of enzyme activity versus minimization of fermentation time and maximization of product to cell yield coefficient versus minimization of fermentation time) and variables (air flow rates, air temperature, moisture content, parameters for cooling and pressure). This paper presents the resulting optimal Pareto front and the possible effects of individual parameters on multiple objectives. To serve the same purpose, simulation runs were taken at different heights of bioreactor so as to foresee the effects of scale-up on the performance of bioreactor - and henceforth the process.