Seventeen designed experiments were conducted in three steps(malting,brewing and fermentation)to produce beer from barley,finger millet and the combination of both.Effects of independent variables with three levels fo...Seventeen designed experiments were conducted in three steps(malting,brewing and fermentation)to produce beer from barley,finger millet and the combination of both.Effects of independent variables with three levels for each i.e.blend ratios of grains(100:0,50:50,0:100),kilning temperature(50℃,70℃,90℃)and malted grain to water ratios(1:3,1:5,1:7)were investigated on product quality.The results of the study indicated that all the independent parameters i.e.blend ratio,kilning temperature and slurry ratio affected the responses(pH,colour,bitterness and alcohol content)significantly.Optimum values of parameters,from the simultaneous optimization done using Design Expert 8.0.6.1 software,for beer production,were found to be 68:32 blend ratio,50℃ kilning temperature and 1:7 slurry ratio.The model F-value was found to be highly significant at 1% level of significance for all the responses.All the responses could be predicted by fitting the second order mathematical model and adequacy checked by R^(2).展开更多
文摘Seventeen designed experiments were conducted in three steps(malting,brewing and fermentation)to produce beer from barley,finger millet and the combination of both.Effects of independent variables with three levels for each i.e.blend ratios of grains(100:0,50:50,0:100),kilning temperature(50℃,70℃,90℃)and malted grain to water ratios(1:3,1:5,1:7)were investigated on product quality.The results of the study indicated that all the independent parameters i.e.blend ratio,kilning temperature and slurry ratio affected the responses(pH,colour,bitterness and alcohol content)significantly.Optimum values of parameters,from the simultaneous optimization done using Design Expert 8.0.6.1 software,for beer production,were found to be 68:32 blend ratio,50℃ kilning temperature and 1:7 slurry ratio.The model F-value was found to be highly significant at 1% level of significance for all the responses.All the responses could be predicted by fitting the second order mathematical model and adequacy checked by R^(2).
