Identification of microbial batch growth dynamics in Chi.Bio mini-bioreactors

Abstract

This work presents the identification of microbial batch growth dynamics using experiments performed in Chi.Bio minibioreactors. The objective is to estimate the parameters of a simple nonlinear model describing the growth of one microbial population consuming glucose as the limiting substrate. Optical density measurements are first converted into biomass concentration using a calibration based on equivalent particle counts and dry cell mass. Then, a Monod-type growth model, including an effective maximum biomass concentration, is fitted to batch experiments performed at different initial glucose concentrations.
The model parameters are estimated by minimizing the error between the measured biomass trajectories and the simulated model response. The fitted model reproduces the experimental growth curves with good accuracy, achieving an (R2) value of 0.981 and
a global RMSE of 0.045 g/L. The results show that the proposed approach can be used to obtain a compact dynamic model of microbial batch growth from Chi.Bio measurements.