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• Taste and mouthfeel properties of 42 red wines were described by rate-k methodology. • Wines were characterised by un-targeted and targeted UPLC‐QTOF-MS methods. • Suitable PLS-R models calculated for dry, sour, oily, prickly, and unctuous. This study aimed to establish relationships between wine composition and in-mouth sensory properties using a sensometabolomic approach. Forty-two red wines were sensorially assessed and chemically characterised using UPLC‐QTOF-MS for targeted and untargeted analyses. Suitable partial least squares regression models were obtained for "dry", "sour", "oily", "prickly", and "unctuous". "Dry" was positively contributed by flavan-3-ols, anthocyanin derivatives (AntD), valine, gallic acid and its ethyl ester, and peptides, and negatively by sulfonated flavan-3-ols, anthocyanin-ethyl-flavan-3-ols, tartaric acid, flavonols (FOL), hydroxycinnamic acids (HA), protocatechuic ethyl ester, and proline. The "sour" model included molecules involved in "dry" and "bitter", ostensibly as a result of cognitive interactions. Derivatives of FOLs, epicatechin gallate, and N -acetyl-glucosamine phosphate contributed positively to "oily", as did vanillic acid, HAs, pyranoanthocyanins, and malvidin-flavan-3-ol derivatives for "prickly", and sugars, glutathione disulfide, AntD, FOL, and one HA for "unctuous". The presented approach offers an interesting tool for deciphering the sensory-active compounds involved in mouthfeel perception. [ABSTRACT FROM AUTHOR]

• Mouthfeel and taste of polyphenolic fractions of grapes were characterized. • PLS models predicting sensory properties from chemical composition were obtained. • Dryness could be satisfactory modeled from tannin and anthocyanin parameters. • Stickiness is well predicted from the level of large polymeric anthocyanins. • Bitterness can be predicted from flavonol concentration. This research aims at predicting sensory properties generated by the phenolic fraction (PF) of grapes from chemical composition. Thirty-one grape extracts of different grape lots were obtained by maceration of grapes in hydroalcoholic solution; afterward they were submitted to solid phase extraction. The recovered PFs were reconstituted in a wine model. Subsequently the wine models, containing the PFs, were sensory (taste, mouthfeel) and chemically characterized. Significant sensory differences among the 31 PFs were identified. Sensory variables were predicted from chemical parameters by PLS-regression. Tannin activity and concentration along with mean degree of polymerization were found to be good predictors of dryness, while the concentration of large polymeric pigments seems to be involved in the "sticky" percept and flavonols in the "bitter" taste. Four fully validated PLS-models predicting sensory properties from chemical variables were obtained. Two out of the three sensory dimensions could be satisfactorily modeled. These results increase knowledge about grape properties and proposes the measurement of chemical variables to infer grape quality. [ABSTRACT FROM AUTHOR]

The present work seeks to define the “green character” of red wines and characterise the groups of molecules potentially involved in that perception. Fifty-four wines were screened by wine experts for different levels of green character. Six different phenolic fractions were obtained by liquid chromatography (LC) and further submitted to sensory and chemical characterisation. The volatile fraction was screened by semipreparative LC, Gas Chromatography-Olfactometry (GC-O) and quantitative analysis. The green character was linked to vegetal aroma, astringency, green and dry tannins according to experts of the Somontano region. Non-volatile fractions containing tannins with mean degree of polymerisation of ten and smaller anthocyanin-derivative pigments (