Macrowine 2021
IVES 9 IVES Conference Series 9 Mouthfeel effects due to oligosaccharides within a wine matrix

Mouthfeel effects due to oligosaccharides within a wine matrix

Abstract

The mouthfeel of wine is one of the most important aspects of the organoleptic experience of tasting wine. In wine a great deal is known about certain compositional components and how they impact mouthfeel perception, such as phenolics. But there are other components where little is understood, such as oligosaccharides. Saccharides in general are found in very low concentrations with wine, especially compared to conventional foods. There is very little information about how oligosaccharides influence the mouthfeel perception of wine. Given the large variance in types and concentrations of oligosaccharides present within the wine system this study aimed to understand their effects with as little variables as possible. This study utilized two different types of oligosaccharides at two different concentration levels to identify and quantify differences in mouthfeel perception within a model wine system. The two oligosaccharides in question, Fructooligosaccharide (FOS) and Glactooligosaccharide (GOS), were added to a basic wine model (14% ethanol, 4 g/L tartaric acid, pH 3.5) at a rate of 450ppm and 900ppm. Concentrations that have been measured in wine, resulting in four treatment groups, FOS450, FOS900, GOS450, GOS900, and one control group consisting of untreated model wine. All four treatment groups underwent triangle testing against the untreated control, and one additional triangle test between the low and high concentrations of the respective oligosaccharide. After triangle tests, all four treatments, and the untreated control underwent descriptive analysis via 100mm visual analog scales. Panelists for the descriptive analysis panel underwent training on sweetness, bitterness, viscosity, acidity, and astringency prior to the beginning of the panel. The results of the triangle tests showed a significant different between the FOS450 and FOS900 samples. However, interestingly neither the FOS450 nor FOS900 samples were found to be significantly different from the untreated control sample. Additionally, neither of the GOS samples were found to be significant from either each other or the control sample. Descriptive analysis found no significant difference in any of the five attributes tested. This indicates that the difference between the FOS450 and FOS900 samples may be above a detection threshold but may not be above a perception threshold. This would mean that a difference can be noticed, but not quantified. Future work will investigate differing levels of oligosaccharides and implement more training to better differentiate during descriptive analysis.

DOI:

Publication date: September 24, 2021

Issue: Macrowine 2021

Type: Article

Authors

Samuel Hoffman, Elizabeth Tomasino, Quynh Phan,

Graduate Research Assistant and MS Candidate, Oregon State University, Associate Professor, Oregon State University Graduate Research Assistant and PhD Candidate, Oregon State University

Contact the author

Keywords

mouthfeel, wine, oligosaccharides, descriptive analysis

Citation

Related articles…

Grapevine sugar concentration model in the Douro Superior, Portugal

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

Effect of one-year cover crop and arbuscular mycorrhiza inocululation in the microbial soil community of a vineyard

The microbial composition of the soil is an important factor to consider in viticulture, since its influence on the “terroir” and on the organoleptic properties of the wine have been demonstrated. Different agronomic techniques have the potential to modify the composition and functionality of the soil microbial community. Maintaining green covers is known to increase soil microbial diversity. The direct application of inoculum of beneficial microorganisms to the soil has also been used to increase their abundance. However, the environmental conditions of each site seem to have a determining weight in the result of these practices. In this study, we compared the effect on the microbial community of a cover crop with legumes in autumn and the inoculation of grapevines with commercial inoculum bases on Rhizophagus irregularis and Funeliformis mosseae in the previous spring. The study has been carried out in a vineyard in Binissalem, Mallorca, Spain. After applying the treatments, we will analyze the soil microbial communities using the data obtained from Illumina amplification of soil DNA from the 16S and ITS regions to analyze bacteria and fungi community, respectively. In addition, we will record the physicochemical characteristics of the soil at each sampling point. The result showed that agronomic management, in the short term, has less influence than soil characteristics on the composition of the soil microbiome. With these results, we can conclude that in a vineyard, agricultural techniques should focus on improving the characteristics of the soil to improve the biodiversity of the soil microbiota.

A predictive model of spatial Eca variability in the vineyard to support the monitoring of plant status

[lwp_divi_breadcrumbs home_text="IVES" use_before_icon="on" before_icon="||divi||400" module_id="publication-ariane" _builder_version="4.19.4" _module_preset="default" module_text_align="center" module_font_size="16px" text_orientation="center"...

Updating the Winkler index: An analysis of Cabernet sauvignon in Napa Valley’s varied and changing climate

This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.

austrianvineyards.com: online viewer of all designations of Austrian wine

To digitally record and present all the origins of Austrian wines in the same perfect and clear way was the motivation for the Austrian Wine Marketing Board (Austrian Wine) to start with the project in 2018. In June 2021 the results were presented to the public in an online viewer showing all the designations of Austrian wine, available at https://austrianvineyards.com in a largely barrier-free manner. The online viewer provides tailored individual maps fitted to the respective zoom level. The smallest unit of wine-origins in Austria is called Ried and is displayed in a plot-specific manner highlighting areas under vine. Information on the Ried include administrative district, winegrowing municipality, cadastral municipality, large collective vineyard site, specific winegrowing region, generic winegrowing region, winegrowing area and, in many cases, an illustrative picture. Complementary data on the size, elevation (minimum-maximum), orientation (in 8 sectors plus flat) and gradient (minimum, maximum, average) are based on the area under vine according to the EU’s Integrated Administration and Control System. Additional information covers climate data. The diagrams are taken from the monthly breakdown of data in the annals of the Central Institute for Meteorology and Geodynamics, Austria provide a display of values for air temperature, precipitation, and sunshine hours for the reference year and the long-term average. Seasonal aggregated data on temperature, precipitation, and sunshine hours complete the display. Short descriptions with emphasis on geology and soil, field name in historical maps, etymology of the denomination, and main planted variety complements the available information for the main designations in the online viewer. These descriptions are compiled by winegrowers, geologists, historians, and journalists. All the information and data can be extracted to a pdf-file. Printed vineyard maps are also available. Missing content regarding wine origins in Styria will be completed in winter 2021/22.