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Coupling kinetic expressions and metabolic networks for predicting wine fermentations
Author(s) -
Pizarro Francisco,
Varela Cristian,
Martabit Cecilia,
Bruno Claudio,
PérezCorrea J. Ricardo,
Agosin Eduardo
Publication year - 2007
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.21494
Subject(s) - winemaking , wine , fermentation , yeast , fermentation in winemaking , yeast in winemaking , fructose , ethanol fermentation , free amino nitrogen , malolactic fermentation , biochemical engineering , biomass (ecology) , zymomonas mobilis , chemistry , food science , sugar , glycerol , biochemistry , saccharomyces cerevisiae , ethanol fuel , biology , bacteria , lactic acid , agronomy , genetics , engineering
Problematic fermentations are commonplace and cause wine industry producers substantial economic losses through wasted tank capacity and low value final products. Being able to predict such fermentations would enable enologists to take preventive actions. In this study we modeled sugar uptake kinetics and coupled them to a previously developed stoichiometric model, which describes the anaerobic metabolism of Saccharomyces cerevisiae . The resulting model was used to predict normal and slow fermentations under winemaking conditions. The effects of fermentation temperature and initial nitrogen concentration were modeled through an efficiency factor incorporated into the sugar uptake expressions. The model required few initial parameters to successfully reproduce glucose, fructose, and ethanol profiles of laboratory and industrial fermentations. Glycerol and biomass profiles were successfully predicted in nitrogen rich cultures. The time normal or slow wine fermentations needed to complete the process was predicted accurately, at different temperatures. Simulations with a model representing a genetically modified yeast fermentation, reproduced qualitatively well literature results regarding the formation of minor compounds involved in wine complexity and aroma. Therefore, the model also proves useful to explore the effects of genetic modifications on fermentation profiles. Biotechnol. Bioeng. 2007;98: 986–998. © 2007 Wiley Periodicals, Inc.