Chemometric modeling of palate fullness in lager beers

Abstract

Palate fullness and mouthfeel of beer are key attributes of sensory beer quality. Non-volatile substances and molar mass fractions influence sensory perceptions of palate fullness and mouthfeel. However, systematic correlations between sensory attributes and native beer compounds have not been evaluated within the concentration range found in lager beer. This article reports a chemometric analysis of 41 lager beers by evaluating analytical data of beer compositions, palate fullness, and mouthfeel descriptors. AF4-MALS-dRI indicated high variability in the macromolecular compositions of classical lager beers. Screened beers were clustered into groups differing significantly in palate fullness intensity and macromolecular distribution. Significant correlations were found between palate fullness and macromolecular fractions and beer composition parameters: original gravity, viscosity, indices of macromolecular distribution, total nitrogen (p < 0.001), and β-glucan (p < 0.01). Thus, a model was built using partial least square regression (PLS) analysis to predict the palate fullness intensity in beers (R2C = 0.7993). This model can be used as a guideline by brewers to control palate fullness and mouthfeel.