(12d) Modelling and Dynamic Optimization of Lager Beer Fermentation for Optimal Flavor Profile and Operation

Beer production is an intricate chemical process. From the same critical ingredients (a starch source, yeast, hops and water), a highly complex mixture of chemical species is obtained. The fluctuating combinations of these compounds, also called off- and on-flavors, are responsible for the unique taste of each beer. Thus, the ability to improve any stage of production will have a significant effect on profitability and the ultimate success or failure of a brewery.

Therefore, it is important to carefully describe the different stages of the beer production process, in order to optimize process conditions and beer flavour. To do so, in this study, a comprehensive fermentation model and optimization problem were formulated. This model includes a complete yeast growth model, production of ethanol and flavor related desirable and undesirable chemical species, including temperature dependency of such processes as well.

Beer flavor reflects the combination of a large number of chemical species, mostly resulting from the yeast metabolism. Therefore, in this work, the goal is to determine how an up-to-date industrial beer production should optimally operate. To achieve this, a two-step procedure is applied: (i) a comprehensive fermentation model is developed, including a yeast growth model, ethanol and by-products production (fusel alcohols, esters, VDKs, acetaldehyde and sulfidic compounds); and, (ii) a dynamic optimization problem is formulated and implemented with the objective of maximizing the conversion of substrate to ethanol, while dealing with the final allowable concentrations of the by-products as strict constraints.

Preliminary results show that each by-product flavor threshold affects process performance and beer flavor in a distinctive manner, which is also supported by published literature. Results indicate that the maximum acceptable concentrations of off- and on- flavors, like diacetyl and ethyl acetate, have considerable impact on the flavor profile, as well as on batch duration.

A comprehensive fermentation model was developed based upon kinetic models. Furthermore, in order to optimize the flavor profile and process conditions, a dynamic optimization was formulated and solved. Thus, we believe, that this work contributes to a comprehensive understanding of the impact of different chemical species (off- and on-flavors) on the optimal beer flavor profile, as well as in the optimization of process conditions.