Abstract
Astringency elicited by tannins is usually assessed by tasting. Alternative methods involving tannin precipitation have been proposed, but they remain time-consuming. Our goal was to propose a faster method and investigate the links between wine composition and astringency. Red wines covering a wide range of astringency intensities, assessed by sensory analysis, were selected. Prediction models based on multiple linear regression (MLR) were built using spectrophotometry (190-400nm) and chemical analysis (enological analysis, polyphenols, oligosaccharides and polysaccharides). Astringency intensity was strongly correlated (R2=0.825) with tannin preicpitation by bovine serum albumine (BSA). Wine absorbances at 230nm (A230) proved more suitable for astringency prediction (R2=0,705) than A280 (R2=0.56) or tannin concentration estimated by phlorogucinolysis (R2=0.59). Three variables models built with A230, oligosaccharides and polysaccharides presented high R2 and low errors of cross-validation. These models confirmed that polysaccharides decrease astringency perception and indicated a positive relationship between oligosaccharides and astringency.