| Summary: | In order to study the kinetic model of changes in microbial cells and substances during fermentation process of lager beer, the reducing sugars, α-amino acid nitrogen, yeast count, diacetyl content and fermentation degree were detected every 24 h over 15 d during the beer fermentation, and the data were nonlinear fitted using typical models including Logistic, Boltzmann, DoseResp, and Farazdaghi-Harris. The results showed that the diacetyl, reducing sugars and α-amino acid nitrogen contents decreased during the beer fermentation, the yeast count initially increased and then decreased, and the fermentation degree initially increased and then stabilized. The Logistic model could reflect the consumption of reducing sugars well, with a fitting coefficient R<sup>2</sup> of 0.999 8. The Boltzmann model was suitable for describing changes in α-amino acid nitrogen contents, with a fitting coefficient R<sup>2</sup> of 0.998 1. The DoseResp model, used for the kinetic model of yeast count changes, had a fitting coefficient R<sup>2</sup> of 0.991 0 and was effective in predicting yeast count trends during the beer fermentation. The optimized diacetyl kinetic model had a fitting coefficient R<sup>2</sup> of 0.997 0. The change in fermentation degree was accurately described using DoseResp model, with a fitting coefficient R<sup>2</sup> of 0.999 2. Compared to different batches of the same type of beer, the established models demonstrated good fitting effects and were deemed suitable for describing the kinetic changes in the beer fermentation process in actual production.
|
|---|
