啤酒糖化生产过程预测统计数学模型的研究

A Study on The Predictve Statistical Mathematical Model of The Mashing Process of Beer

本文对啤酒生产糖化过程预测统计数学模型的建立进行了研究。首先采用正交拟因子试验设计法,对不同质量的麦芽确定对麦芽汁质量具有显著影响的因素,并得出了二次煮出糖化法最佳工艺条件。在此基础上建立了麦芽汁主要质量指标与不同质量的麦芽和其它影响因素之间关系的预测统计数学模型。通过实验验证,模型的预测精度较高。

In this paper, a study was made en the predictive mathematical model of the mashing process of beer. Orthogonal experiment was performed to determine the significant influence of affecting factors on wort quality and the optimal technological conditions of the double-mash decoction mashing with malt of different quality was then given. Using the experimental results, a statistical model which described the quantitative relationship among wort quality and its affecting factors was established. Experiment verification showed that the model had a significnt linear correlation and a higher prediction accuracy.