Liu Chunfeng, Dong Jianjun, Yin Xiangsheng, Li Qi, Gu Guoxian
National Key Laboratory of Beer Biological Fermentation Engineering, Tsingtao Brewery Co. LTD, Qingdao, 266101 Shandong Province People's Republic of China ; Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122 Jiangsu Province People's Republic of China ; Laboratory of Brewing Science and Engineering, Jiangnan University, Wuxi, 214122 Jiangsu Province People's Republic of China.
National Key Laboratory of Beer Biological Fermentation Engineering, Tsingtao Brewery Co. LTD, Qingdao, 266101 Shandong Province People's Republic of China.
J Food Sci Technol. 2014 Nov;51(11):2964-76. doi: 10.1007/s13197-012-0824-7. Epub 2012 Sep 19.
The hydrogen bonding was prone to be formed by many components in beer. Different sorts of flavor substances can affect the Chemical Shift due to their different concentrations in beer. Several key factors including 4 alcohols, 2 esters, 6 ions, 9 acids, 7 polyphenols, and 2 gravity indexes (OG and RG) were determined in this research. They could be used to investigate the relationship between hydrogen bonding intensity and the flavor components in bottled larger beers through the Correlation Analysis, Principal Component Analysis and Multiple Regression Analysis. Results showed that ethanol content was the primary influencing factor, and its correlation coefficient was 0.629 for Correlation Analysis. Some factors had a positive correlation with hydrogen bonding intensity, including the content of original gravity, ethanol, isobutanol, Cl(-), K(+), pyruvic acid, lactic acid, gallic acid, vanillic acid, and Catechin in beer. A mathematic model of hydrogen bonding Chemical Shift and the content of ethanol, pyruvic acid, K(+), and gallic acid was obtained through the Principal Component Analysis and Multiple Regression Analysis , with the adjusted R(2) being 0.779 (P = 0.001). Ethanol content was proved to be the most important factor which could impact on hydrogen bonding association in beer by Principal Component Analysis. And then, a multiple non-linearity model could be obtained as follows: [Formula: see text]. The average error was 1.23 % in the validated experiment.
啤酒中的许多成分易于形成氢键。不同种类的风味物质因其在啤酒中的浓度不同而会影响化学位移。本研究确定了几个关键因素,包括4种醇类、2种酯类、6种离子、9种酸类、7种多酚类以及2个比重指标(原麦汁浓度和真正发酵度)。通过相关性分析、主成分分析和多元回归分析,这些因素可用于研究瓶装拉格啤酒中氢键强度与风味成分之间的关系。结果表明,乙醇含量是主要影响因素,在相关性分析中其相关系数为0.629。一些因素与氢键强度呈正相关,包括啤酒中原麦汁浓度、乙醇、异丁醇、Cl⁻、K⁺、丙酮酸、乳酸、没食子酸、香草酸和儿茶素的含量。通过主成分分析和多元回归分析得到了氢键化学位移与乙醇、丙酮酸、K⁺和没食子酸含量的数学模型,调整后的R²为0.779(P = 0.001)。主成分分析证明乙醇含量是影响啤酒中氢键缔合的最重要因素。然后,可以得到如下多元非线性模型:[公式:见原文]。在验证实验中平均误差为1.23%。