Modeling Of Alcohol Fermentation In Brewing - Integrated Approch For Control Of Continuous Alcohol Fermentation
An integrated approach for the management of continuous beer fermentation with immobilized cells was developed. Experimental results for continuous fermentation were used for the development of dependencies for the calculation of real extract and ethanol at different degrees of fermentation and dilution rates. For this purpose, mathematical relationships describing the fermentation with high accuracy were used.
Modeling Of Alcohol Fermentation In Brewing - Comparative Assessment Of Flavor Profile Of Beers Produced With Free And Immobilized Cells
A detailed investigation of bioengineering constants for the accumulation of major yeast metabolites in beer produced by free and immobilized cells was carried out. The kinetic constants were used to determine the effect of immobilization on yeast metabolism. The esters synthesis dynamics was similar for the free and the immobilized cell which was confirmed by the kinetic model. The dynamics of the higher alcohol synthesis was comparable for the free and immobilized cell, but there were some differences. The dynamics of the higher alcohols accumulation for the free and immobilized cells was similar, but there were some differences between the two used strains. These differences were due to the influence of mass transfer between the liquid and the capsules, which reflected mostly in the metabolism of some amino acids. There were significant differences in the aldehyde synthesis and reduction by immobilized and free cells. The free cells of both yeast strains showed distinct maximum of aldehydes, where after the aldehydes reduction started. On the other hand, the aldehyde peaks were not so distinct for the immobilized cells and the aldehydes concentration was relatively constant during fermentation. The explanation for this difference can be found in the kinetic parameters. The model described with high accuracy the beer fermentations with immobilized and free cells and confirmed the experimental data. The obtained data would be used for developing of control strategy fermentation process to obtain beverages with different organoleptic profile. INTRODUCTION The main stages in the brewing process are: wort production; alcoholic fermentation and maturation; processing and stabilization of the beer (Kunze 2003; Handbook of brewing: Processes, Technology, Markets 2009). The wort transforms into beer during alcoholic fermentation and maturation. The ethanol fermentation occurs as a result of enzymatic activity of the yeast at Embden-Meyerhof Parnas pathway, which leads to glucose conversion to pyruvate. Under anaerobic conditions the yeasts convert pyruvate to ethanol and CO2. In aerobic conditions, yeasts consume sugars, mainly for biomass accumulation and CO2 production (Boulton and Quain, 2001). Yeast metabolism during fermentation and maturation affects significantly on beer flavor. Ethanol, CO2, esters and fusel alcohols have positive contributions to beer flavor. Dimethyl sulphide and hydrogen sulphide, diacetyl, and aldehydes contribute to flavor defects of beer (Meilgaard, 1975). Therefore, the synthesis and reduction of yeast metabolites on the microbiological and bioengineering levels have to be studied for the purpose of yeast by-products optimization in certain limits. Fermentation and maturation are the longest processes in brewing. The primary fermentation lasts between 3-6 days and the maturation up to 2 weeks depending on the fermentation type and the used equipment. In such a competitive market, the potential time savings, proposed by immobilized cell technology (ICT) have to be taken into account. Immobilized yeast cell technology allows the production of beer to be accomplished in as little as 2-3 days (Branyik et al, 2005). Immobilized cell systems are heterogeneous systems in which considerable mass transfer limitations can occur, resulting in a changed yeast metabolism (Willaert, 2007). Consequently, the main challenge for ICT is to reproduce the traditional beer flavor. Proceedings 27th European Conference on Modelling and Simulation ©ECMS Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang (Editors) ISBN: 978-0-9564944-6-7 / ISBN: 978-0-9564944-7-4 (CD) The aim of this work is to determine the influence of immobilization on the yeast metabolism using mathematical models. The dynamics of the main yeast metabolites ethanol and CO2, the biomass concentration and some of secondary yeast metabolites esters, aldehydes and higher alcohols were studied. The differences between fermentations with immobilized and free cells were determined by the developed mathematical models for yeast metabolites. MICROORGANISMS AND FERMENTATION CONDITIONS The fermentations were carried out with top-fermenting yeast strain Saccharomyces cerevisiae S-33 and bottomfermenting yeast strain Saccharomyces pastorianus S23. Wort with 3 different original extracts – 9, 11 and 13% was used for fermentations. All media were sterilized at 121 °С for 20 min before fermentations. Immobilization procedure and fermentation conditions were previously reported in (Parcunev et.al. 2012). In this study the fermentations with free and immobilized cells were investigated for the same intervals of time (10 days) to determine the impact of immobilization on the yeast metabolism. Although the fermentation with immobilized cells was faster than the one with free cells, the metabolites accumulation in the fermenting medium was influenced by diffusion limitations. Biomass concentration of immobilized cells was determined according to mathematical model proposed in (Parcunev et.al. 2012). The concentrations of yeast metabolites – aldehydes, esters and higher alcohols were measured according to (Marinov, 2010). Because of the limited volume of wort, the analyzes were performed on the 1, 3, 5, 7 and 9 day for the fermentation with top-fermenting yeast and on the 2, 4, 6, 8 and 10 day for the fermentation with bottom fermenting yeast. MATHEMATICAL MODELS AND THEIR EXPLANATION Equation of fermentation The fermentation with immobilized cells can be described with the equations for batch fermentation with free cells as previously reported (Parcunev et.al. 2012):
A model for predicting heat transfer through gypsum‐board/wood‐stud walls exposed to fire
To facilitate the development of cost-effective and flexible design options there is a need to develop models to predict the fire resistance of wood-frame building assemblies. Such assemblies often derive much of their fire resistance from a protective membrane composed of gypsum board. A simple two-dimensional computer model is presented to predict heat transfer through gypsum-board/wood-stud walls exposed to fire. Input data for the thermophysical properties of gypsum board were measured exploying standard bench-scale tests. Input data for wood were selected from the literature. Small-and full-scale fire resistance tests were conducted on gypsum-board/wood-stud wall assemblies to provide data for the validation of the model. The model is shown to predict heat transfer through these walls rather well.