Modeling the flavor thresholds of organic acids in beer as a function of their molecular properties

被引:78
作者
Siebert, KJ [1 ]
机构
[1] Cornell Univ, Dept Food Sci & Technol, Geneva, NY 14456 USA
关键词
partial least squares regression; principal components analysis; quantitative structure activity relationships; olfaction; taste;
D O I
10.1016/S0950-3293(98)00059-7
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
A mathematical model of the flavor thresholds of organic acids in beer as a function of their physical and chemical properties was constructed. Principal components analysis (PCA) was applied to 11 properties for 17 acids; this resulted in four significant principal components (PCs), which accounted for 93% of the variance in the property data. The PCs were dominated by the number of polar groups, the number of double bonds, molecular size, and solubility in non-polar solvents, respectively. PC scores indicating each acid's location along each of four scales were obtained. Literature data for acid flavor thresholds in beer were modeled as a function of the principal components using multiple linear regression and partial least squares (PLS) regression. The best-fit and best prediction equations were identical, with an R-2 Of 0.905. (C) 1999 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:129 / 137
页数:9
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