Abstract

The oxygen mass transfer coefficient often serves compare the efficiency of bioreactors and their mixing devices as well as being an important scale-up factor. In submerged fermentation, four methods are available to estimate the overall oxygen mass transfer coefficient (K(L)a): the dynamic method, the stationary method based on a previous determination of the oxygen uptake rate (Q(O2)X), the gaseous oxygen balance and the carbon dioxide balance. Each method provides a distinct estimation of the value of K(L)a. Data reconciliation was used to obtain a more probable value of K(L)a during the production of Saccharomyces cerevisiae, performed in 22.5-l fed-batch bioreactor. The estimate of K(L)a is obtained by minimising an objective function that includes measurement terms and oxygen conservation models, each being weighted according to their level of confidence. Weighting factors of measurement terms were taken as their respective inverse variance whereas weighting factors of oxygen conservation models were obtained using Monte Carlo simulations. Results show that more coherent and precise estimations of K(L)a are obtained.