A kinetic model for beer production under industrial operational conditions |
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| Affiliation: | 1. Dept. Informática y Automática, Universidad Complutense de Madrid28040 MadridSpain;2. Dept. Microbiologı́a III, Universidad Complutense de Madrid28040 MadridSpain;3. Dept. Ingenierı́a Quı́mica, Universidad Complutense de Madrid28040 MadridSpain;1. Department of Chemistry and Biochemistry, The University of Texas at Arlington, 700 Planetarium Place, Arlington, TX, 76019, USA;2. Affiliate of Collaborative Laboratories for Environmental Analysis and Remediation, The University of Texas at Arlington, Arlington, TX, 76019, USA;3. Inform Environmental, LLC, 6060 N. Central Expressway, Suite 500, Dallas, TX, 75206, USA;1. School of Microbiology/Centre for Synthetic Biology and Biotechnology/Environmental Research Institute/APC Microbiome Institute, University College Cork, Cork T12 YN60, Ireland;2. The Australian Wine Research Institute, P.O. Box 197, Glen Osmond, Adelaide, SA 5064, Australia;1. School of Agricultural, Forestry, Food and Environmental Sciences (SAFE), University of Basilicata, Viale Dell’Ateneo Lucano 10, 85100 Potenza, Italy;2. Italian Brewing Research Centre, Department of Agricultural, Food and Environmental Science, University of Perugia, 06126 Perugia, Italy;3. Department of Biotechnology, University of Verona, Strada Le Grazie 15, 37134 Verona, Italy |
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| Abstract: | A kinetic model for beer production is proposed. The model takes into account five responses: biomass, sugar, ethanol, diacetyl and ethyl acetate. In contrast with previously published models, this model segregates biomass into three components: lag, active and dead cells and considers the active cells as the only fermentation agent. Experiments were first performed at laboratory scale and isothermal runs were carried out at five temperatures (8°C, 12°C, 16°C, 20°C and 24°C). Fitting of experimental data was made by non-linear regression. Parameter values calculated were similar to those given in the literature. The kinetic model was able to fit experimental data with a very good agreement. Afterwards, experiments were conducted at pilot plant scale and runs were now carried out changing temperature with time, in the industrial way. The kinetic model, with the parameter values calculated as a function of temperature, was able to predict with a very high accuracy the non-isothermal experimental data achieved. This model can be used for simulation of the industrial process under different operational conditions and for faults detection. It can also be utilized for the optimization and even for the supervised control of the process and its automatization. |
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