Model-based automation of baker's yeast production

Abstract

An on-line model, estimating key state variables in bioprocesses, is utilized for control of fed-batch baker's yeast production. The state estimates are produced by balances and phenomenological expressions combined with on-line measurements. The goal of the control strategy is to maintain the highest possible glucose flux that can be entirely respiratively assimilated by the cells, resulting in the highest possible yeast growth without formation of metabolic products, such as acetic acid and ethanol. Stepwise improvement of the control algorithm is carried out in order to find a strategy to avoid undesired, irreversible metabolic pathways. In the final algorithm, such undesired changes in metabolism are predicted from an estimate of intracellular storage carbohydrates. A considerable decrease in the estimate indicates future metabolic changes at a time early enough to avoid them. At maximal yield, a growth rate near the highest possible is obtained in laboratory-scale Saccharomyces cerevisiae cultivations with the control strategy developed.