Fermentation Kinetics Beyond Viability: A Fitness-Based Framework for Microbial Modeling

Traditional fermentation models often oversimplify kinetics by treating microbial populations as physiologically homogeneous. To address this, we introduce a novel framework that explicitly incorporates cellular fitness by distinguishing the metabolically active subpopulation (“productive cells”) responsible for biosynthesis. This approach integrates established growth models (First Order Plus Dead Time and Logistic) with a modified Luedeking–Piret model (MALP), which introduces a new differential equation to dynamically quantify productive cells. This modeling study relies exclusively on experimental data available in the literature; no new experimental work was conducted. Validated against four diverse fermentation systems from published datasets, the MALP model demonstrated superior predictive accuracy, achieving coefficients of determination (R2 > 0.97) for metabolite kinetics. Sensitivity analysis identified time-delay and maintenance-associated parameters as dominant factors governing system behavior. The key contribution of this work is a mechanistic equation that universally captures the real-world dynamics of metabolite production, providing a more realistic and robust framework for modeling heterogeneous bioprocesses.