Substrate Feeding Strategy Integrated with a Biomass Bayesian Estimator for a Biotechnological Process

Abstract

This work proposes a substrate feeding strategy for a bioprocess integrated with a biomass estimator based in nonlinear filtering techniques. The performance of the proposed estimator and the substrate strategy are illustrated for the δ-endotoxin production of Bacillus thuringiensis (Bt) in batch and fed batch cultures. Nonlinear filtering techniques constitutes an adequate option as estimation tool because of the strongly nonlinear dynamics of this bioprocess and also due to nature of the uncertainties and perturbations that cannot be supposed Gaussians distributed. Biomass estimation is performed from substrate and dissolved oxygen. Substrate feeding strategy is intended to obtain high product concentration. Simulations results along with their experimental verifications demonstrate the acceptable performance of the proposed biomass estimator and the substrate feeding strategy.