[Genetic algorithm for fermentation kinetics of submerged fermentation by Morchella].

Area of Science:

• Mycology
• Biochemical Engineering
• Mathematical Modeling

Context:

• Optimizing submerged fermentation is crucial for efficient fungal cultivation.
• Understanding fermentation kinetics aids in process control and scale-up.
• Morchella fermentation presents unique kinetic challenges.

Purpose:

• To compare the suitability of Monod and Logistic models for describing Morchella submerged fermentation kinetics.
• To evaluate kinetic parameters for Morchella growth, exopolysaccharide (EPS) production, and substrate consumption.
• To identify the best-fit model for predicting Morchella fermentation behavior.

Summary:

• Submerged fermentation kinetics of Morchella were investigated using genetic algorithms in Matlab.
• The Logistic model demonstrated a better fit to experimental data compared to the Monod model, with an average error of 5.8%.
• Key kinetic parameters for Morchella growth, EPS production, and substrate consumption were evaluated.

Impact:

• The study provides a validated kinetic model for Morchella fermentation.
• The findings facilitate improved process optimization and scale-up strategies for Morchella cultivation.
• This research contributes to the efficient industrial production of fungal biomass and products.