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

FERNANDO A. DI SCIASCIO; QUINTERO OLGA LUCÍA; ADRIANA N. AMICARELLI

INTERNATIONAL JOURNAL OF CHEMICAL REACTOR ENGINEERING

BERKELEY ELECTRONIC PRESS

Año: 2016 vol. 14 p. 1187 - 1200

1542-6580

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.