Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/70308
Type: Conference paper
Title: Models for predicting wine fermentation kinetics
Author: O'Neill, B.
Van Heeswijck, T.
Muhlack, R.
Citation: Proceedings of CHEMECA 2011, held in Sydney, Australia, 18-21 September 2011
Publisher: Engineers Australia
Publisher Place: online
Issue Date: 2011
ISBN: 9780858259225
Conference Name: CHEMECA (39th : 2011 : Sydney, Australia)
Statement of
Responsibility: 
Brian O'Neill, Torbjorn van Heeswijck and Richard Muhlack
Abstract: Fermentation of grape juice by yeast is a critical stage in industrial wine production. However, the kinetics of the process are poorly understood due to the extreme conditions present during such fermentations. Problematic fermentations occur regularly and result in significant cost as a result of wasted tank capacity and low value of the final degraded product. Control of the fermentation process is important to avoid 'stuck fermentations' (a stuck fermentation is a fermentation that has stopped before all the available sugar in the wine has been converted to alcohol and CO2) and clearly, the fermentation unit operation strongly influences the aesthetic endcharacteristics of the wine. A variety of models have been proposed to predict the dynamic behaviour (kinetics) of the process. Two traditional and simple biochemical models (Monod kinetics and the Gompertz model) are predominantly employed and these were investigated in this work. The primary aim of this study was to determine the ability of both models to predict fermentation behaviour when fitted to data from early stages of fermentation. Initially, the Monod and Gompertz models were fitted to sugar consumption data for laboratory scale wine fermentations using least squares regression. The model produced a reasonable qualitative fit for the kinetic (growth and production) data with a root-mean-squared error (RMS) of 21 g/L or less in each case. Both models were then fitted to sugar consumption data from twenty two industrial fermentations over a varying number of time steps following the initial measurement in each data set. The number of time steps required to produce an RMS error less than 20 g/L was 8 days in 19 cases using the Monod model. However, the Gompertz model (successful in 18 cases) generally required 2 – 4 fewer time steps (days). No correlation was found between the number of time steps required or the regressed parameters and the volume of fermentation. The values of the regressed Monod parameters maximum growth rate (μm), the Monod constant (KS) and the yield coefficient (YX/S) lay between 0.1 – 1.0 day-1, 200 – 1000 g/L and 0.01 – 0.10 g cell X/g substrate (assumed to be sugar content) S in most cases, with deviations loosely correlated to the use of Semillon grapes. Both models exhibited promise for use in industry alongside traditional winemaking techniques, depending upon the specific goals and requirements of each individual winery. Rigorous error analysis was not possible due to a lack of supplied experimental uncertainty data and this will be investigated in future work.
Rights: Copyright status unknown
RMID: 0020116355
Description (link): http://www.chemeca2011.com/
Appears in Collections:Chemical Engineering publications

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