Predicting by-product gradients of baker’s yeast production at industrial scale

A practical simulation approach

Journal Article (2020)
Author(s)

Christopher Sarkizi Shams Hajian (University of Stuttgart)

C. Haringa (DSM)

Henk J. Noorman (DSM, TU Delft - BT/Bioprocess Engineering)

Ralf Takors (University of Stuttgart)

Research Group
BT/Bioprocess Engineering
Copyright
© 2020 Christopher Sarkizi Shams Hajian, C. Haringa, H.J. Noorman, Ralf Takors
DOI related publication
https://doi.org/10.3390/pr8121554
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Christopher Sarkizi Shams Hajian, C. Haringa, H.J. Noorman, Ralf Takors
Research Group
BT/Bioprocess Engineering
Issue number
12
Volume number
8
Pages (from-to)
1-19
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Abstract

Scaling up bioprocesses is one of the most crucial steps in the commercialization of bioproducts. While it is known that concentration and shear rate gradients occur at larger scales, it is often too risky, if feasible at all, to conduct validation experiments at such scales. Using computational fluid dynamics equipped with mechanistic biochemical engineering knowledge of the process, it is possible to simulate such gradients. In this work, concentration profiles for the by-products of baker’s yeast production are investigated. By applying a mechanistic black-box model, concentration heterogeneities for oxygen, glucose, ethanol, and carbon dioxide are evaluated. The results suggest that, although at low concentrations, ethanol is consumed in more than 90% of the tank volume, which prevents cell starvation, even when glucose is virtually depleted. Moreover, long exposure to high dissolved carbon dioxide levels is predicted. Two biomass concentrations, i.e., 10 and 25 g/L, are considered where, in the former, ethanol production is solely because of overflow metabolism while, in the latter, 10% of the ethanol formation is due to dissolved oxygen limitation. This method facilitates the prediction of the living conditions of the microorganism and its utilization to address the limitations via change of strain or bioreactor design or operation conditions. The outcome can also be of value to design a representative scale-down reactor to facilitate strain studies.