Sensory transfer between handfeel touch and mouthfeel: A guide for developing a tool to describe mouthfeel properties of red wines

This study examined the influence of pectinase-producing non-Saccharomyces yeasts on the chemical and sensory attributes of red and white wines with added pectin. Merlot and Chardonnay wines were produced with or without a mixture of pectinase-producing non-Saccharomyces yeasts (Cryptococcus adeliensis, Issatchenkia orientalis, and Pichia kluyveri) added to the must prior to alcoholic fermentation conducted by a commercial strain of Saccharomyces cerevisiae. To ensure sufficient substrate was present, varying concentrations of apple pectin (up to 1.25 g/L for red wines and 1.00 g/L for white wine) were added at the start of fermentation. After bottling, trained panelists (n = 10) analyzed these wines for aroma, flavor, taste, and mouthfeel attributes. For both wines, significant interactions were noted between the presence of non-Saccharomyces yeasts and pectin addition which affected pH, titratable acidity, and concentrations of D-galacturonic acid. While no significant sensory differences were observed among the red wines, limited changes were noted for white wines. However, a strong positive correlation was found between the D-galacturonic acid and buttery aroma for Chardonnay and with flavor for Merlot. Increasing D-galacturonic acid concentrations, through utilization of non-Saccharomyces yeasts, may improve the wine quality as a buttery aroma is often associated with high-quality Chardonnay. For both red and white wines, the utilization of these particular non-Saccharomyces yeasts significantly influenced chemical properties but yielded minor sensory changes without any faults. PRACTICAL APPLICATION: With the recent trend to reduce alcohol content in commercial wines, the interest in non-Saccharomyces yeasts has grown. This study showed that the addition of non-Saccharomyces yeasts, perhaps due to their pectinase activity, influenced the chemical characteristics of red and white wines with limited sensory differences, making these yeasts a useful tool for winemakers to modify wine properties.

Red wine grapes have an important impact on the economy of many regions, both for wine quality and for their richness in phenolic compounds, which have many health benefits. Climate has been changing substantially in the last years, which affects greatly grape polyphenolic composition and wine quality. In this review, we will unveil the importance of climate in grape development, both physically and chemically, the different methodologies used to evaluate grape quality, the interesting new approaches using NIR spectroscopy, and the functional properties of grapes and red wine, due to their high phenolic content. Climate has an impact in the development of phenolic compounds in grapes, namely in the anthocyanins biosynthesis. The phenolic chemical composition changes during maturation, therefore, it is essential to keep on track the accumulation of these key compounds. This information is crucial to help producers choose the best harvest date since specific compounds like polyphenols are responsible for the color, taste, and mouthfeel of wines, which directly affects wine quality. The usage of different methodologies to assess quality parameters in grapes and wine, can be used to provide essential information to create the chemical profile of each variety to develop calibration methods. NIR spectroscopy seems to be a reliable method to be used in vineyards during grape maturation to provide real time information on quality parameters to producers since many reliable calibration models have been developed over time.

Due to the rapid development of modern society, red wine has gradually become popular. Research on the quality of red wine has turn into an important topic. Red wine contains more than 600 kinds of ingredients, in terms of alcohol, minerals, tannic acid, citric acid, chloride and other substances. This paper analyzes 12 factors affecting red wine quality in the data set and studies the influence of each ingredient on the quality of red wine through data mining algorithm. Based on the data visualization of Python processing, classical visualization tools such as histogram, heat map, box-plot and Pearson correlation coefficient algorithm are used for data mining. The histogram is adopted for univariate analysis and the heat map composed of Pearson coefficient is used for multivariate analysis. Then, the box-plot is used for cross-verification. Finally, it is concluded that alcohol, sulfate, citric acid and volatile acidity are the decisive factors affecting the quality of red wine. This conclusion can not only be used as a reference for consumers to buy, but also provide suggestions for wine manufacturers to improve the quality of red wine.

Red wine quality is determined greatly by phenolic substances whose presence relies on extraction of grape skins and seeds during fermentation. Monitoring phenolic behaviour is beneficial for fermentation management because of the importance of maceration during red winemaking and its influence on phenolics that contribute to predominant red wine characteristics, such as colour, flavour and mouthfeel. Properly quantifying the kinetics associated, however, with red grape and wine phenolics is an intricate process. This review focuses on the extraction and ensuing reactions of principal phenolic substances during various stages of red winemaking as described by dynamic and spatial mathematical models. The extraction and reaction phenomena are concurrently influenced by several environmental and technological factors during fermentation, such as temperature, oxidation and mixing regimes, resulting in complex phenolic behaviour over time. As such, employing mathematical modelling is extremely useful for ascertaining the kinetic and spatial basis for phenolic behaviour, and the models significantly enhance the existing understanding of the extraction and reaction mechanisms of phenolic substances that are critical to red wine quality. Ultimately, this knowledge will allow for the development of predictive tools for phenolic extraction based on fruit composition and can potentially contribute to increased wine quality with optimised and sustainable production practices.

The aim of the present study was characterisation of selected varieties of still wines produced in Slovak Republic in vintage year 2013 and one 2012. There were tested ten samples of nine varieties of wines originated from Malokarpatská "Lesser Carpathian" and Južnoslovenská "Southern Slovakia" wine regions of Slovak Republic, Dornfelder, Frankovka modrá, Svätovarinecké, Zweigeltrebe, Müller Thurgau, Veltlínské zelené, Rizling rýnsky, Rizling vlašský and Sauvignon wines. There were studied selected physico-chemical properties of tested wines as a total contents of anthocyanins and polyphenols by means of spectrophotometry, titratable acidity, density and chromatic characteristics. The highest content of anthocyanins (TAC) was found in red wine Frankovka modrá, 183 mg.L-1 and the lowest for sample rose wine St. Laurent 19 mg.L-1. The content of total phenolic compounds as a gallic acid was in range 2833 to 1961 mg.L-1 for red wines, 1016 and 1013 mg.L-1 for rose wines, 1085 to 549 mg.L-1for white wines. Total acidy was average 6.3 ±0.3 g.L-1 only for Ryzling rýnský, 8.2 g.L-1 and Sauvignon rose 8.0 g.L-1 and was expressed as the amount of tartaric acid. Quality of wines can be expressed by colour intensity too. Was evaluated and compared intensity of colour in wines by CIE Lab method and the total differences between red, rose and white wine DE* was calculated. The most differences was found for Svätovarinecké a Frankovka modrá (2.5) - red wines ("clearly perceptible") and 4.9 for Veltlýnské zelené and Müller Thurgau - white wine ("moderating effect").

Chapter 4 - Microoxidation in Wine Production

Oxygen contribution to phenolic evolution during aging of red wines

The impact of elevated carbon dioxide concentration ([CO2]) on the quality of berries, must, and red wine (with special reference to volatile composition, phenolic content, and antioxidant activity) made from Touriga Franca, a native grape variety of Vitis vinifera L. for Port and Douro wine manufacturing grown in the Demarcated Region of Douro, was investigated during 2005 and 2006. Grapevines were grown either in open-top chambers (OTC) with ambient (365 +/- 10 ppm) or elevated (500 +/-16 ppm) [CO2] or in an outside plot. In general, the increase of [CO2] did not affect berry characteristics, especially the total anthocyan and tannin concentrations. However, the total anthocyan and polyphenol concentrations of the red wine were inhibited under elevated [CO2]. The antioxidant capacity of the wines was determined by DPPH, ABTS, and TBARS assays and, despite the low concentrations of phenolics, the elevated [CO2] did not significantly change the total antioxidant capacity of the red wines. Thirty-five volatile compounds belonging to seven chemical groups were identified: C6 alcohols, higher alcohols, esters, terpenols, carbonyl compounds, acids, volatile phenols, and C13 norisoprenoids. Generally, the same volatile compounds were present in all of the wines, but the relative levels varied among the treatments. The effect of elevated [CO2] was significant because it was detected as an increase in ethyl 2-methylbutyrate, isoamyl acetate, ethyl hexanoate, ethyl octanoate, butyric acid, and isovaleric acid concentrations and a decrease in ethyl acetate concentration when compared to wines produced in ambient [CO2] in 2005. In elevated [CO2], wines from 2006 had lower methionol, 1-octanol, and 4-ethylguaiacol and higher ethyl lactate and linalool concentrations. The increase in [CO2] did not significantly affect C6 alcohols, citronellol, carbonyl compounds, and beta-damascenone concentrations. This study showed that the predicted rise in [CO2] did not produce negative effects on the quality of grapes and red wine. Although some of the compounds were slightly affected, the red wine quality remained almost unaffected.

Effect of β-lactoglobulin on perception of astringency in red wine as measured by sequential profiling

Contribution of non-volatile and aroma fractions to in-mouth sensory properties of red wines: Wine reconstitution strategies and sensory sorting task

An international collaborative study was conducted of an HPLC-refractive index (RI) detector method for the determination of the combined amounts of sugars, glycerol, organic acids, and phenolic compounds in wines and wine-like beverages. Nine collaborating laboratories representing major winery, contract laboratories, and government laboratories tested eight different materials as blind duplicates using the proposed method. Sample materials included red and white wines, port, wine cooler, and nonalcoholic wine. One material was a negative control, and one material was a reference material. Samples were either treated with an ion-exchange resin to remove interfering organic acids prior to analysis or left untreated to include organic acids and phenolics. Red wine samples were treated with polyvinylpolypyrrolidone to remove potential interferences from phenolics prior to analysis. The HPLC analyses were performed on a Bio-Rad Fast Acid Analysis Column using RI detection. Reproducibility (RSD(R)) for untreated samples (sugars + phenolics + organic acids) ranged from 6.6% for Titrivin AA4 reference material to 11.0% for dry red wine. RSD(R) for treated samples (sugars only) ranged from 6.8% for white zinfandel to 18.9% for dry white wine. RSD(R) for treated samples (sugars only) + glycerol ranged from 6.4% for white zinfandel to 19.8% for dry red wine. Based on these results, the method was adopted as Official First Action status for determination of total carbohydrates in wine and wine-like beverages.

Distribution of crown hexameric procyanidin and its tetrameric and pentameric congeners in red and white wines

Although the benefits of moderate intake of red wine in decreasing incidence of cardiovascular diseases associated to hypercholesterolemia are well recognized, there are still widespread misconceptions about its effects on the hypercholesterolemia-related cognitive impairments. Herein we investigated the putative benefits of regular red wine consumption on cognitive performance of low-density lipoprotein receptor knockout (LDLr−/−) mice, an animal model of familial hypercholesterolemia, which display cognitive impairments since early ages. The red wine was diluted into the drinking water to a final concentration of 6% ethanol and was available for 60 days for LDLr−/− mice fed a normal or high-cholesterol diet. The results indicated that moderate red wine consumption did not alter locomotor parameters and liver toxicity. Across multiple cognitive tasks evaluating spatial learning/reference memory and recognition/identification memory, hypercholesterolemic mice drinking red wine performed significantly better than water group, regardless of diet. Additionally, immunofluorescence assays indicated a reduction of astrocyte activation and lectin stain in the hippocampus of LDLr−/− mice under consumption of red wine. These findings demonstrate that the moderate consumption of red wine attenuates short- and long-term memory decline associated with hypercholesterolemia in mice and suggest that it could be through a neurovascular action.

Australian wine drinkers' (n = 310) questionnaire responses measured consumption dimensions, product involvement, subjective knowledge, personality traits and socio-demographics to predict red wine consumption and perceived quality. Total red wine consumed/week was predicted by wine involvement (product involvement); being male and self-monitoring (ability); the number of days/week drinking red wine was predicted by age and wine involvement (product sign) and higher income. Higher self-monitoring predicted buying more expensive wine. Wine involvement was predicted by wine subjective knowledge, reward responsiveness, need for cognition and, negatively, by impulsivity (non-planning). Perceived quality was predicted by sensitivity to reward and older wine company and, negatively, by higher expenditure.

Cross-flow microfiltration and membrane plate filtration are the main filtration processes used in wineries. However, the inherent compositional variability of red wines could affect the impact of these two filtration techniques on the final wine quality. Thus, this work aims to study, under winery-scale conditions, the impact of these two filtration processes on the turbidity level, phenolic composition, chromatic characteristics and sensory profile of red wine. For this purpose, three different Portuguese red wines with different initial phenolic contents were used. In this context, several methodologies were used to quantify the total phenolic composition, chromatic characteristics, individual anthocyanins and proanthocyanidins before and after filtration. The sensory profiles of the different red wines were also considered. The results indicated that each filtration process produced a substantial reduction in turbidity values and, consequently, an increase in wine clarification. In addition, the data obtained also indicated that both filtration techniques reduced the phenolic content of the different red wines that were studied. However, the impact of these two filtration options on wine characteristics (phenolic composition and sensory profile) was heterogenous, without a clear trend of differentiation between the wines depending on the type of filtration. Thus, this research points out evidence that the impact of the two filtration techniques that were studied is very dependent on the initial wine composition.