Macrowine 2021
IVES 9 IVES Conference Series 9 Influence of berry maturity, maceration time and wine maturation on the polyphenols and sensory characteristics of pinot noir and Cabernet-Sauvignon

Influence of berry maturity, maceration time and wine maturation on the polyphenols and sensory characteristics of pinot noir and Cabernet-Sauvignon

Abstract

AIM: Combined investigation of the influence of berry maturity, maceration time and wine maturation on the changes in polyphenols and sensory characteristics of Pinot noir and Cabernet-Sauvignon. This comparative approach was chosen to assess the importance of the term “phenolic maturity” and its impact on polyphenols and sensory characteristics in the context of well-known effects observed during winemaking. Pinot noir and Cabernet-Sauvignon were used due to the huge differences in the climatic growing conditions, in phenolic profiles in grapes and wines and their high international relevance.

METHODS: Pinot noir and Cabernet-Sauvignon grapes of the vintage 2018 were harvested at three different stages of ripening. The grapes were macerated for 6 days or 13 days. Wines were analyzed immediately after pressing and three months after bottling to investigate the influence of wine maturation. Vinification was conducted in 100 L fermenters. All wines were fermented < 1g/L residual sugar and MLF was done after alcoholic fermentation. The phenolic composition was analyzed using HPLC-DAD/FD, LC-QToF-MS and different spectrophotometric assays. The descriptive sensory analysis has been conducted using 19 trained judges.

RESULTS: The sensory analysis showed a higher variance between the wines due to berry maturity than due to maceration time. The sensory perception of wines made out of berries at different stages of ripening could not be influenced towards another stage by extending maceration time. Wine maturation was responsible for the highest variance in phenolic composition. Berry maturity had the lowest impact of the three factors. These observations were made for both grape varieties.

CONCLUSIONS: 

The analytical methods are well suited to identify and explain the differences of the wines due to maceration time and wine maturation. The strong influence of berry maturity on sensory perception cannot be explained solely by the phenolic composition of the wines. Further research is needed to identify other parameters that contribute to berry maturity and their interactions with polyphenols to improve the understanding of the term “phenolic maturity”. This study shows that the oenological tool of extended maceration cannot compensate insufficient berry maturity in regard to sensory perception.

DOI:

Publication date: September 10, 2021

Issue: Macrowine 2021

Type: Article

Authors

Sandra Feifel

Weincampus Neustadt (Germany),Dominik DURNER, Weincampus Neustadt (Germany) Pascal WEGMANN-HERR, Weincampus Neustadt (Germany)

Contact the author

Keywords

phenolic maturity, berry maturity, extended maceration, pinot noir, Cabernet-Sauvignon

Citation

Related articles…

Impact of climate variability and change on grape yield in Italy

Viticulture is entangled with weather and climate. Therefore, areas currently suitable for grape production can be challenged by climate change. Winegrowers in Italy already experiences the effect of climate change, especially in the form of warmer growing season, more frequent drought periods, and increased frequency of weather extremes.
The aim of this study is to investigate the impact of climate variability and change on grape yield in Italy to provide winegrowers the information needed to make their business more sustainable and resilient to climate change. We computed a specific range of bioclimatic indices, selected by the International Organisation of Vine and Wine (OIV), and correlated them to grape yield data. We have worked in collaboration with some wine consortiums in northern and central Italy, which provided grape yield data for our analysis.
Using climate variables from the E-OBS dataset we investigate how the bioclimatic indices changed in the past, and the impact of this change on grape productivity in the study areas. The climate impact on productivity is also investigated by using high-resolution convection-permitting models (CPMs – 2.2 horizontal resolution), with the purpose of estimating productivity in future emission scenarios. The CPMs are likely the best available option for this kind of impact studies since they allow a better representation of small-scale processes and features, explicitly resolve deep convection, and show an improved representation of extremes. In our study, we also compare CPMs with regional climate models (RCMs – 12 km horizontal resolution) to assess the added value of high-resolution models for impact studies. Further development of our study will lead to assessing the future suitability for vine cultivation and could lead to the construction of a statistical model for future projection of grape yield.

Short-term relationships between climate and grapevine trunk diseases in southern French vineyards

[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"...

δ13C : A still underused indicator in precision viticulture  

The first demonstration of the interest of carbon isotope composition of sugars in grapevine, as an integrated indicator of vineyard water status, dates back to 2000 (Gaudillère et al., 1999; Van Leeuwen et al., 2001). Thanks to the isotopic discrimination of Carbon that takes place during plant photosynthesis, under hydric stress conditions, it is possible to accurately estimate the photosynthetic activity. Ever since, δ13C has been widely applied with success to zonation, terroir studies and vine physiology research, but is still not widely used by viticulturists. This is quite astonishing by considering the impact of global warming on viticulture and the need to improve water management, that would justify a widespread use of δ13C.
The lack of private laboratories proposing the analysis, the cost of the technology, as well as the long analytical delays, have been detrimental to its development. Some laboratories tried to overcome the analytical difficulties of isotopic analysis by using fourier transformed infrared spectroscopy, as a fast and cheap alternative to the official OIV method (IRMS). These claimed FTIR models have never been published or peer reviewed and cannot be considered robust. In this work, thanks to the recent acquisition of IRMS technology, new modern and robust applications of δ13C for viticulture are proposed. This includes the use of the analysis to make parcel separations at harvesting, the possibility to increase the precision of hydric stress cartography and the potential cost reduction when compared with Scholander pressure bomb analysis.

Grape must quality and mesoclimatic variability in Fruška Gora wine-growing region, Serbia

The Fruška Gora mountain is a traditional wine-growing region in Serbia situated in the Pannonian Basin. Due to such a position, the vicinity of the Danube River and the presence of concave configuration, it is suitable for grape production. This paper provides analyses of spatial variations in meteorological parameters and grape juice quality within Fruška Gora wine region over three consecutive vintages (2018-2020). The examined period can be defined as warm with cool nights during September (AVG 18,9°C; GDD 1918°C; CI 12°CF) and with the presence of mesoclimatic variability. The East part of the study area was somewhat drier and hotter compared to other parts of the region. The analyses of grape must samples (190 in total) of five cultivars (Cabernet-Sauvignon, Merlot, Chardonnay, Sauvignon blanc and Grašac (Welschriesling)) commonly grown across the region (19 sites), were performed using Fourier Transform Infrared Technology (FTIR). Among all cultivars, Sauvignon blanc was harvested first in the East area (DOY=246±5, GDD at harvest=1552±74, 22.2±0.7 °Brix), while the latest harvest was recorded for Cabernet-Sauvignon in the West (DOY=283±5, GDD at harvest=1936±187, 23.4±1.0 °Brix ). Both the red and white cultivars had higher acidity and YAN in the grape must if the vines were grown in the North and East compared to South and West areas. According to PCA analysis, Grašac showed the lowest variation in grape must chemical composition. Thus, the results confirm that Grašac is the most stable cultivar in Fruška Gora. All monitored cultivars reached technological fruit ripeness by the end of the growing season. However, it was difficult to reach full ripeness of red cultivars, mostly beacuse of uncoupling of technolocical and phenolic ripeness. Thus, Cabernet-Sauvignon had higher variations in GDD sums at harvest compared to other cultivars, which probably increased variations in grape must quality.

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