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

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 acidʹs 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 R2 of 0·905.