18 research outputs found

    Analysis of polymeric phenolics in red wines using different techniques combined with gel permeation chromatography fractionation

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    A multiple-step analytical method was developed to improve the analysis of polymeric phenolics in red wines. With a common initial step based on the fractionation of wine phenolics by gel permeation chromatography (GPC), different analytical techniques were used: high-performance liquid chromatography-diode array detection (HPLC-DAD), HPLC-mass spectrometry (MS), capillary zone electrophoresis (CZE) and spectrophotometry. This method proved to be valid for analyzing different families of phenolic compounds, such as monomeric phenolics and their derivatives, polymeric pigments and proanthocyanidins. The analytical characteristics of fractionation by GPC were studied and the method was fully validated, yielding satisfactory statistical results. GPC fractionation substantially improved the analysis of polymeric pigments by CZE, in terms of response, repeatability and reproducibility. It also represented an improvement in the traditional vanillin assay used for proanthocyanidin (PA) quantification. Astringent proanthocyanidins were also analyzed using a simple combined method that allowed these compounds, for which only general indexes were available, to be quantified. © 2005 Elsevier B.V. All rights reserved

    Modelling wine astringency from its chemical composition using machine learning algorithms

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    Aims: The present work aims to predict sensory astringency from wine chemical composition using machine learning algorithms. Material and results: Moristel grapes from different vineblocks and at different stages of ripening were collected. Eleven different wines were produced in 75 L tanks in triplicate, and further sensory factors were described by the rate-all-that-apply method with a trained panel of participants. The polyphenolic composition was characterised in wines by measuring the concentration and activity of tannins using UHPLC-UV/VIS, the mean degree of polymerisation (mDP. and the composition of tannins using thiolysis followed by UHPLC-MS. Conventional oenological parameters were analysed using FTIR and UV-Vis. Machine learning was applied to build models for predicting a wines astringency from its chemical composition. The best model was obtained using the support vector regressor (radial kernel) algorithm presenting a root-mean-square error (RMSE) value of 0.190. Conclusions: The main variables of the astringency model were the % of procyanidins constituting tannins and ethanol content, followed by other eight variables related to tannin structure and acidity. Significance of the study: These results increase the knowledge of chemical variables related to the perception of wine astringency and provide tools to control and optimise grape and wine production stages to modulate astringency and maximise quality and the consumer appeal of wines

    Perspectives on wines of provenance: Sensory typicality, quality, and authenticity

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    Published: June 18, 2021Wine is revered throughout the world and comes in many varieties and styles. Factors influencing wine chemical composition and sensory properties are complex but can be related to product origin. Wine provenance also invokes notions of typicality and quality that underpin the reputation of wines and their regions. This perspective outlines current aspects related to sensory typicality, quality control, and authenticity for wines from delimited regions. It covers the influence of terroir, links between typicality and quality, control of quality through sensory assessment, the relationship with authenticity, and rapid methods for classification of wines according to origin, variety, or vintage.María-Pilar Sáenz-Navajas and David W. Jeffer

    Study of hydroxycinnamic acids and malvidin 3-monoglucoside derivatives using capillary zone electrophoresis and ultra-performance liquid chromatography

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    Model solutions (pH = 3.5, 12% ethanol) of malvidin 3-O-glucoside (Mv3glc), the most common free anthocyanin in grapes and red wines from Vitis vinifera, and three free hydroxycinnamic acids present in wines (caffeic, ferulic and p-coumaric acids) were studied. The stability of the precursors and their derivatives was studied during a storage period of six months at 20 °C. Capillary zone electrophoresis with UV–vis detection (CZE/UV–vis) was used to monitor changes in sample composition. Ultra-performance liquid chromatography coupled to mass detection (UPLC/MS) was used to confirm the presence of the compounds formed. Discussion on the migration times of the new pigments as well as on their UV–vis and mass spectra is reported. Six derivatives were detected in model wine solutions containing Mv3glc and caffeic acid. The six derivatives were identified as three condensation products of caffeic acid, 4-vinylcatechol, 4-vinylsyringol and a compound with a molecular ion at m/z 803, whose structure has been tentatively assigned to a caffeic acid linked to Pinotin A. The derivatives 4-vinylphenol and 4-vinylguaiacol pyranoanthocyanins were detected in solutions containing malvidin 3-O-glucoside together with p-coumaric and ferulic acid, respectively. The malvidin 3-O-glucoside derivative, 4-vinylsyringol was also detected in all solutions containing the anthocyanin regardless of the presence of hydroxycinnamic acid.The authors thank the Consejería de Educación, Cultura y Deportes delGobierno de La Rioja for its financial support (ANGI 2004/10). MPSN thanks the INEM for her contract of employment: mujer-primer empleo and the University of La Rioja for her F.P.I. grant, as well as the MEC/FEDER for the AGL2005-02313/ALI project.Peer reviewe

    Sensory properties of extra-premium Spanish red wines and their implication in wine quality perception

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    Background and Aims: Little is known about the link between quality and the sensory space of premium commercial Spanish red wines. The major aims of the present study were to define the sensory space of these wines and determine the implication of their sensory properties (aroma and in-mouth attributes) in the quality perception of wine professionals. Methods and Results: Evaluation of wine quality was first studied by a categorisation task. Then, sensory descriptive analysis based on citation frequencies for aroma attributes and conventional intensity scores for taste and mouth-feel properties was performed on individual samples. The general sensory quality was highly positively correlated to astringency and, to a lesser extent, to acidity as well as to fruity, spicy and roasted/woody attributes, and especially highly negatively correlated to aromatic attributes belonging to the animal family. Conclusions: Categorisation tasks based on quality perception coupled to sensory analysis based on citation frequencies for aroma properties and on classical descriptive analysis for taste and mouth-feel properties could be suitable tools to finely determine sensory quality. The results highlight the importance of in-mouth properties, especially of astringency and acidity, in general quality as well as the relevance of the aromatic profile. Significance of the Study: This study increases the information on the sensory properties of premium Spanish red wines and the implication of concrete sensory attributes in sensory quality perception. This work provides winemakers information to be considered when elaborating high quality red wines. © 2010 Australian Society of Viticulture and Oenology Inc

    Orthonasal aroma characteristics of spanish red wines from different price categories and their relationship to expert quality judgements

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    Background and Aims: Research aimed to define the olfactory sensory spaces of Spanish red wines from different price segments and to determine relationships between sensory descriptors and quality as evaluated by experts. Methods and Results: A trained panel using a frequency of citation method assessed the orthonasal sensory characteristics of 96 Spanish wines belonging to three price segments (premium; high standard; low standard). Eleven robust sensory terms were built by combining similar terms using statistical criteria. A panel of experts consistently assessed quality. Negative aroma profiles, some of them very skewed, were identified in the different sets with 'animal', 'undergrowth', 'vegetal', 'dried fruit' or 'evolved/oxidized' notes. While skewed aroma profiles were not necessary for achieving low quality, the role of some terms was highly dependent on the category. 'Dried fruit' was positive in premium wines and negative in the other categories, in which its role was played by 'berry'. The low standard wines had to be segmented into wooded and unwooded samples to find clear relationships with quality. Satisfactory models for quality could be built in all segments. Conclusions: Orthonasal aroma can explain wine quality. The sensory pair 'woody/animal' was confirmed as the most relevant and influential for wine quality. The role of the other terms depended on the category. Oxidation-related attributes are particularly detrimental to younger wines. Significance of the Study: The results provide a reliable and complete sensory database. They identified aroma profiles related to quality, provided an insight into the hierarchies of terms and provided information that will assist in the identification of the aroma chemicals potentially involved. © 2012 Australian Society of Viticulture and Oenology Inc

    Sensory changes during bottle storage of Spanish red wines under different initial oxygen doses

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    © 2014 Elsevier Ltd. Sixteen commercial Spanish red wines selected to cover a wide range of sensory properties were stored at 25°C for 6months in air-tight containers under different oxygen doses (0-30mgL-1) mimicking real and extreme bottling situations. The 16 initial samples (before storage) and the 80 stored samples (16 wines×5 oxygen doses) were submitted to sensory analysis. Sensory changes related to post-bottling storage and initial oxygen dose were evaluated by means of discriminant and characterisation sensory strategies.Significant increases in black fruits, dried fruits, woody, lactic and stronger increases in cooked vegetables and spicy notes reveal a general pattern of aroma evolution. Remarkable departures to this general pattern have been observed, which can be related to the initial sensory properties of the wines and to their basic polyphenolic composition. The effect of post-bottling storage in bitterness is wine dependent, while global decreases in both global intensity and persistence evaluated in mouth are observed. Discrete increases in astringency are observed for wines with the lowest initial astringent scores. Important sensory interactions between aroma attributes (herbal and spicy) and bitterness and between roasted and astringency perception are shown. Little impact of the initial oxygen dose in the in-mouth sensory properties is reported. These results are relevant for wine experts in that they help understanding the evolution of wine sensory properties in the bottling stage. This study may help them to develop strategies for managing this winemaking stage with objective criteria.Peer Reviewe

    Sensory interactions between six common aroma vectors explain four main red wine aroma nuances

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    This work aims at assessing the aromatic sensory dimensions linked to 6 common wine aroma vectors (N, norisoprenoids; A, branched acids; F, enolones; E, branched ethyl esters; L, fusel alcohols, M, wood compounds) varying in their natural range of occurrence. Wine models were built by adding the vectors at two levels (fractional factorial design 2(VI)) to a de-aromatised aged red wine. Twenty other different models were evaluated by descriptive analysis. Red, black and dried fruits and woody notes were satisfactorily reproduced. Individual vectors explained just 15% of the sensory space, mostly dependent on perceptual interactions. N influences dried and black fruits and suppresses red fruits. A suppresses black fruits and enhances red and dried fruits. F exerts a major role on red fruits. E suppresses dried fruits and modulates black fruits. L is revealed as a strong suppressor of red fruits and particularly of woody notes.Funded by the Spanish MINECO (projects AGL2010-22355 and AGL2014-59840). E.C. and M.P.S.N. got postdoctoral fellowships (Juan de la Cierva and Ayudas postdoctorales 2013, respectively) also from MINECO. Funding from Diputación General de Aragón (T53) and Fondo Social Europeo is acknowledged.Peer Reviewe

    Modelling wine astringency from its chemical composition using machine learning algorithms

    No full text
    Aims: The present work aims to predict sensory astringency from wine chemical composition using machine learning algorithms. Material and results: Moristel grapes from different vineblocks and at different stages of ripening were collected. Eleven different wines were produced in 75 L tanks in triplicate, and further sensory factors were described by the rate-all-that-apply method with a trained panel of participants. The polyphenolic composition was characterised in wines by measuring the concentration and activity of tannins using UHPLC-UV/VIS, the mean degree of polymerisation (mDP. and the composition of tannins using thiolysis followed by UHPLC-MS. Conventional oenological parameters were analysed using FTIR and UV-Vis. Machine learning was applied to build models for predicting a wines astringency from its chemical composition. The best model was obtained using the support vector regressor (radial kernel) algorithm presenting a root-mean-square error (RMSE) value of 0.190. Conclusions: The main variables of the astringency model were the % of procyanidins constituting tannins and ethanol content, followed by other eight variables related to tannin structure and acidity. Significance of the study: These results increase the knowledge of chemical variables related to the perception of wine astringency and provide tools to control and optimise grape and wine production stages to modulate astringency and maximise quality and the consumer appeal of wines
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