TY - JOUR

T1 - Evaluation of the energy efficiency of enzyme fermentation by mechanistic modeling

A1 - Albaek,Mads O.

A1 - Gernaey,Krist V.

A1 - Hansen,Morten S.

A1 - Stocks,Stuart M.

AU - Albaek,Mads O.

AU - Gernaey,Krist V.

AU - Hansen,Morten S.

AU - Stocks,Stuart M.

PB - John/Wiley & Sons, Inc. John/Wiley & Sons Ltd.

PY - 2012

Y1 - 2012

N2 - Modeling biotechnological processes is key to obtaining increased productivity and efficiency. Particularly crucial to successful modeling of such systems is the coupling of the physical transport phenomena and the biological activity in one model. We have applied a model for the expression of cellulosic enzymes by the filamentous fungus Trichoderma reesei and found excellent agreement with experimental data. The most influential factor was demonstrated to be viscosity and its influence on mass transfer. Not surprisingly, the biological model is also shown to have high influence on the model prediction. At different rates of agitation and aeration as well as headspace pressure, we can predict the energy efficiency of oxygen transfer, a key process parameter for economical production of industrial enzymes. An inverse relationship between the productivity and energy efficiency of the process was found. This modeling approach can be used by manufacturers to evaluate the enzyme fermentation process for a range of different process conditions with regard to energy efficiency.

AB - Modeling biotechnological processes is key to obtaining increased productivity and efficiency. Particularly crucial to successful modeling of such systems is the coupling of the physical transport phenomena and the biological activity in one model. We have applied a model for the expression of cellulosic enzymes by the filamentous fungus Trichoderma reesei and found excellent agreement with experimental data. The most influential factor was demonstrated to be viscosity and its influence on mass transfer. Not surprisingly, the biological model is also shown to have high influence on the model prediction. At different rates of agitation and aeration as well as headspace pressure, we can predict the energy efficiency of oxygen transfer, a key process parameter for economical production of industrial enzymes. An inverse relationship between the productivity and energy efficiency of the process was found. This modeling approach can be used by manufacturers to evaluate the enzyme fermentation process for a range of different process conditions with regard to energy efficiency.

KW - Trichoderma

KW - Cellulases

KW - Energy efficiency

KW - Mass transfer correlatio

KW - Process modeling

U2 - 10.1002/bit.24364

DO - 10.1002/bit.24364

JO - Biotechnology and Bioengineering (Print)

JF - Biotechnology and Bioengineering (Print)

SN - 0006-3592

IS - 4

VL - 109

SP - 950

EP - 961

ER -