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Modeling of the Beer Fermentation Process

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Bioreaction Engineering
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Abstract

Over the last decades, huge, centrally located breweries with factory-style production and considerable brewing capacities were built At the same time the beer consumption has been decreasing in central Europe. Thus, the breweries fight over market shares. Consequently, optimization of the benefit/cost ratio becomes decisive for breweries to keep themselves at the competitive edge. As the beer quality is not extremely different between breweries in a given area, the beer price and hence the production cost becomes an overwriting criterion. Cost must be cut wherever possible, but labor and energy costs are the primary targets of process optimization.

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References

  1. NarzißL (1990) Üpber einige Faktoren, die den Biergeschmack beeinflussen. Brauwelt 130:1554–1556, 1558–1562

    Google Scholar 

  2. Mitsui S, Shimazu T, Abe I, Kishi S (1991) Simulation and optimization of aeration in beer fermentation. MBAA Techn Quart 28: 119–122

    CAS  Google Scholar 

  3. Dymond G (1991) The brewer in control: modern brewery automation. Brewers Guardian 120 /3: 17–21

    Google Scholar 

  4. Havlik I, Dors M, Beil S, Simutis R, Lübbert A (1992) State prediction in production scale beer fermentation using fuzzy aided Extended Kalman Filters. Dechema Conferences 5b: 623–626

    Google Scholar 

  5. Simutis R, Havlik I, Lübbert A (1993) Fuzzy aided neural network for real time state estimation and process prediction in a production scale beer fermentation. J Biotechnol 27: 203–215

    Article  CAS  Google Scholar 

  6. Simutis R, Havlik I, Schneider F, Dors M, Lübbert A (1995) Artificial neural networks of improved reliability for industrial process supervision. In: Munack A, Schügerl K (eds) Proceedings of the 6th International Conference Computer Appl in Biotechnology. Elsevier, Oxford

    Google Scholar 

  7. Manikowski M (1996) Modellgestützte Überwachung und Steuerung des Garprozesses in einer Bierbrauerei, Doctoral Dissertation, University of Hannover

    Google Scholar 

  8. Manikowski M, Havlik I, Simutis R, Lübbert A (1999) Model–supported estimation of the diacetyl concentration during a production–scale beer fermentation. J Inst Brew (submitted )

    Google Scholar 

  9. Daoud IS, Searle BA (1990) On–line monitoring of brewery fermentation by measurement of C02 evolution rate. J Inst Brew 96: 297–302

    CAS  Google Scholar 

  10. Austin GD, Watson RWJ, Nordstrom PA, DÁmore T (1994) An on–line capacitance bio– mass monitor and its correlation with viable biomass. MBAA Techn Quarterly 31: 85–89

    Google Scholar 

  11. Schubert J, Simutis R, Dors M, Havlik I, Lübbert A (1994) Bioprocess optimization and control: Application of hybrid modelling. J Biotechn 35: 51–68

    Article  CAS  Google Scholar 

  12. Landaud S, Lieben P, Picque D (1998) Quantitative analysis of diacetyl, pentanedione, and their precursors during beer fermentation by an accurate GC/MS method. J Inst Brew 104: 93–99

    CAS  Google Scholar 

  13. Nakatani K, Takahasho T, Nagami K, Kumada J (1984) Kinetic study of vicinal diketones in brewing (I): Formation of total vicinal diketones. MBAA Technical Quarterly 21: 73–78

    CAS  Google Scholar 

  14. Nakatani K, Takahasho T, Nagami K, Kumada J (1984) Kinetic study of vicinal diketones in brewing (II): Theoretical aspect for the formation of total vicinal diketones. MBAA Technical Quarterly 21: 175–183

    CAS  Google Scholar 

  15. Masschelein CA (1997) A realistic view on the role of research in the brewing industry today. J Inst Brew 103: 103–113

    Google Scholar 

  16. Dellweg H (1985) Diacetyl und Bierreifung, Monatsschr Brauwiss 6:262–266

    Google Scholar 

  17. Inoue T (1977) Forecasting the vicinal diketone of finished beer. Rept Res Lab Kir in Brewery 20: 19–24

    CAS  Google Scholar 

  18. Rice JF, Helbert JR (1973) The kinetics of diacetyl formation and assimilation during fermentation. Proc Annual Meeting ASBC, pp 11–17

    Google Scholar 

  19. Yamauchi Y, Okamoto T, Murayama H, Kajino K, Amikura T, Hiratsu H, Nagara A, Kamiya T, Inoue T (1995) Rapid maturation of beer using an immobilized yeast bioreactor. 1. Heat conversion of a–acetolactate. I Biotechnol 38: 101–108

    Article  CAS  Google Scholar 

  20. Garcia Al, Garcia LA, Diaz, M (1994) Modeling of diacetyl during beer fermentation. J Inst Brew 100: 179–183

    Google Scholar 

  21. Pandiella SS, Garcia LA, Diaz M, Daoud IS (1995) Monitoring the production of carbon dioxide during beer fermentation. MBAA Technical Quarterly 32: 126–131

    CAS  Google Scholar 

  22. Doelle HW, Kirk L, Crittenden R, Toh H (1993)Zymomonas mobilis–science and industrial applications. Crit Rev Biotechnol 13:57–98

    Article  CAS  Google Scholar 

  23. Kempe E, Schallenberger W (1983)Measuring and control of fermentation processes, part I. Proc Biochem 18:7–12

    Google Scholar 

  24. DeClerk J (1965) Lehrbuch der Brauerei, Bd II Analysenmethoden und Betriebskontrolle. Versuchs und Lehranstalt fur Brauerei, Berlin

    Google Scholar 

  25. Gmehling I, Onken U, Arlt W (1977) Vapor–liquid equilibrium data collection, vol 1, pt la, pp 116–155

    Google Scholar 

  26. Werbos P (1990) Backpropagation through time: what it does and how to do it? Proc IEEE 78: 1550–1560

    Article  Google Scholar 

  27. Jazwinski AH (1970) Stochastic process and filtering theory. Academic Press, New York

    Google Scholar 

  28. Simutis R, Havlik I, Lübbert A (1992) A fuzzy–supported extended Kalman filter: a new approach to state estimation and prediction exemplified by alcohol formation in beer brewing. J Biotechnol 24: 211–234

    Article  CAS  Google Scholar 

  29. Stephanopoulos G, Park S (1992) Bioreactor state estimation. In: K Schügerl (ed) Biotechnology, measuring, modelling, and control, vol 4. VCH, Weinheim, pp 225–249

    Google Scholar 

  30. Shioya S (1992) Optimization and control in fed–batch bioreactors. Adv Biochem Eng Biotechnol 46: 111–142

    CAS  Google Scholar 

  31. Schuch C (1996) Temperaturverteilung in zylindrokonischen Tanks, Brauwelt 13: 594–597

    Google Scholar 

  32. Lapin A, Lübbert A (1994) Dynamic simulation of the gas–liquid flows in bubble columns, demonstrated at the example of industrial–scale beer fermenters; paper presented at the 13th International Symposium on Chemical Reaction Engineering, Baltimore

    Google Scholar 

  33. Lapin A, Lübbert A (1999) Fluid dynamics in industrial–scale cylindroconical beer fermenters (to be published)

    Google Scholar 

  34. Gvazdaitis G, Beil S, Kreibaum U, Simutis R, Havlik I, Dors M, Schneider F, Lübbert A (1994) Temperature control in fermenters: application of neural nets and feedback control in breweries. J Inst Brew UK, 100: 99–104

    CAS  Google Scholar 

  35. Asahi K, Kinoshita M (1992) Asahi’s new high–tech and energy efficient ″Ibaraki″ brewery, Technical Quarterly of the Master Brewer’s Association of the Americas 29: 48–52

    Google Scholar 

  36. O’Shea JA (1990) Ice–banks at Guinness Dublin. The Brewer 76: 478–480

    Google Scholar 

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© 2000 Springer-Verlag Berlin Heidelberg

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Lübbert, A. (2000). Modeling of the Beer Fermentation Process. In: Schügerl, K., Bellgardt, KH. (eds) Bioreaction Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59735-0_11

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  • DOI: https://doi.org/10.1007/978-3-642-59735-0_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-64103-9

  • Online ISBN: 978-3-642-59735-0

  • eBook Packages: Springer Book Archive

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