Metabolic heat based specific growth rate estimators: Does the choice of estimation model influence the state of bioprocesses?

Accurate and reliable estimation of specific growth rate ($\mu$) in real-time is pivotal for reliable process monitoring of a bioprocess and subsequent implementation of advanced control strategies. Gibbs free energy dissipation is imminent for any biological system, and the metabolic heat flow measurements (calorimetry) formed the basis for estimating $\mu$. However, the rationale behind selecting a suitable $\mu$ estimator model based on calorimetric perspective remains unexplored. The present investigation addresses the notion behind the selection of an appropriate estimator for $\mu$ and the assessment of the estimator models was illustrated using different types of energy metabolism, namely, high exothermic and low exothermic processes. The results indicated that the $\mu$ values from the instantaneous heat flow estimator significantly deviated (10-fold higher) from the offline values for highly exothermic process. Notably, the cumulative heat-based estimator accurately estimated $\mu$ values on both types of energy metabolism with performance metrics <0.005 h⁻¹.