MODELING AND OPTIMIZATION OF MASHING PROCESS IN BEER PRODUCTION WITH RICE ADJUNCT

Abstract

Adjuncts like rice, wheat and sorghum are used by beer manufacturers worldwide to reduce the cost of production by replacing malt as a starch source. Rice is the most widely used adjunct in Asian countries. Understanding the enzyme kinetics in mashing process is vitally important to maximize sugar yield at a minimum cost. In this research, a semi-empirical model was developed for the mashing process, based on enzyme kinetic equations and experimental results; and this model was used to optimize the operating conditions when enzymes are not added externally. As predicted by the model, when 30% (w/w) of rice was used as an adjunct the maximum sugar yield can be obtained at 56° C and 6.5 pH, and the optimum temperature for mashing process increases with acidity. Since the acidity of solution increases during the mashing process due to the formation of organic acids, use of an increasing temperature profile is recommended to get the maximum output from the mashing process.