Macrowine 2021
IVES 9 IVES Conference Series 9 Enzyme treatments during pre-fermentative maceration of white winegrapes: effect on volatile organic compounds and chromatic traits

Enzyme treatments during pre-fermentative maceration of white winegrapes: effect on volatile organic compounds and chromatic traits

Abstract

AIM: Volatile organic compounds (VOCs) are very important for the characterisation and quality of the final white wine. An oenological practice to increase the extraction of aroma compounds is the cold pre-fermentative maceration [1,2], although it may also release phenolic compounds that confer darker chromatic traits to white wines, not appreciated by consumers. This practice could be improved by the use of enzymes in order to facilitate the release of the odorous molecules. In this study, the effect of different enzyme treatments during skin contact on the chromatic characteristics and volatile composition of white musts from four winegrape varieties was evaluated.

METHODS: Different enzymes presenting distinct single activities (pectolytic and non pectolytic) were added to the must of four white winegrape varieties (Arneis, Greco, Falanghina and Chardonnay) and then subjected to cold pre-fermentative maceration. For each enzyme and variety tested, three berry replicates of 500 g each were randomly selected, added with 10 mg/kg of potassium metabisulphite and crushed. Enzymes were added at a dose of 10 mg/kg. Then, the must was left in contact with the skins for 13 h at 12 °C. Furthermore, other three berry replicates of 500 g each were used as control following the same procedure without enzyme addition. At the end, the musts obtained were separated from the skins and analysed for total polyphenolic index (TPI), chromatic parameters (absorbance at 420 nm and CIELab coordinates), as well as free and glycosylated VOCs. Volatile composition was determined by solid-phase extraction followed by GC-MS analysis [3].

RESULTS: The use of enzymes during cold pre-fermentative maceration resulted in musts having different technological parameters, such as must yield, pH and organic acids content. The chromatic characteristics related to yellow/brown colour (absorbance at 420 nm and CIELab coordinates) and TPI values were dependent on the enzyme used. Indeed, pectin lyase, polygalacturonase and arabinase reduced the yellow colour component of the must obtained when compared to the control sample. Regarding VOCs, different enzymes modulated the release of free forms differently, which are olfactively perceptible, but also they increased the extraction of glycosylated compounds into the grape must. Particularly, most of enzymes tested had a positive effect on the release of terpenes, however the release of norisoprenoids, C6 compounds, alcohols and benzenoids was influenced by both the enzyme used and the variety treated

CONCLUSIONS: The use of different enzymes influenced technological parameters, chromatic characteristics and VOCs contents but some effects were variety dependent. This study may aid oenologists to better understand the action of these enzymes and thus to manage cold pre-fermentative maceration according to the oenological objective.

DOI:

Publication date: September 27, 2021

Issue: Macrowine 2021

Type: Article

Authors

Mattia Malabaila, Stefano BOZ, Maria Alessandra PAISSONI, Carlo MONTANINI, Simone GIACOSA, Luca ROLLE, Susana RÍO SEGADE,

University of Torino, Italy.

Contact the author

Keywords

enzymes, pre-fermentative maceration, volatile organic compounds, chromatic characteristics, white winegrapes

Citation

Related articles…

Different soil types and relief influence the quality of Merlot grapes in a relatively small area in the Vipava Valley (Slovenia) in relation to the vine water status

Besides location and microclimatic conditions, soil plays an important role in the quality of grapes and wine. Soil properties influence…

Extreme canopy management for vineyard adaptation to climate change: is it a good idea?

Climate change constitutes an enormous challenge for humankind and for all human activities, viticulture not being an exception. Long-term strategic changes are probably needed the most, but growers also need to deal with short-term changes: summers that are getting progressively warmer, earlier harvest dates and higher pH in musts and wines. In the last 10-15 years, a relevant corpus of research is being developed worldwide in order to evaluate to which extent extreme canopy management operations, aimed at reducing leaf area and, thus, limiting the source to sink ratio, could be useful to delay ripening. Although extreme canopy management can result in relevant delays in harvest dates, longer term studies, as well as detailed analysis of their implications on carbohydrate reserves, bud fertility and future yield are desirable before these practices can be recommended.

Protected Designation of Origin (D.P.O.) Valdepeñas: classification and map of soils

The objective of the work described here is the elaboration of a map of the different types of vineyard soils that to guide the famers in the choice of the most productive vine rootstocks and varieties. 90 vineyard soils profiles were analysed in the entire territory of the Origen Denominations of Valdepeñas. The sampling was carried out in 2018 (June to October) by making a sampling grid, followed by photointerpretation and control in the field. The studied soils can be grouped into 9 different soil types (according to FAO 2006 classification): Leptosols, Regosols, Fluvisols, Gleysols, Cambisols, Calcisols, Luvisols and Anthrosols. A map showing the soil distribution with different type of soils has been made with the ArcGIS program. Regarding to the choice of rootstock, Calcisoles are soils with a high active limestone content, so the rootstocks used in these soils must be resistant to this parameter; Luvisols are deep soils with high clay content, so they will support vigorous rootstocks. Because the cartographic units are composed of two or more subgroups, with are associated in variable proportions, 9 different soil associations have been established; Unit 1: Leptosols, Cambisols and Luvisols (80%, 15% and 5% respectively); Unit 2: Cambisols with Regosols and Luvisols (40%, 30% and 30% respectively); Unit 3: Cambisols and Gleysols with Regosols (40%, 40% and 20% respectively); Unit 4: Regosols with Cambisols, Leptosols and Calcisols (40%, 30%, 15% and 15% respectively); Unit 5: Cambisols, Leptosols, Calcisols and Regosols (25% each of them); Unit 6: Luvisols with Cambisol and Calcisols (80%, 10% and 10% respectively); Unit 7: Luvisols and Calcisols with Cambisols (40%, 40% and 20% respectively); Unit 8: Calcisols with, Cambisols and Luvisols (80%, 10% and 10% respectively); Unit 9: Anthrosols. These study allow to elaborate the first map of vineyard soils of this Protected Designation of Origin in Castilla-La Mancha.

Revealing the Barossa zone sub-divisions through sensory and chemical analysis of Shiraz wine

The Barossa zone is arguably one of the most well-recognised wine producing regions in Australia and internationally; known mainly for the production of its distinct Shiraz wines. However, within the broad Barossa geographical delimitation, a variation in terroir can be perceived and is expressed as sensorial and chemical profile differences between wines. This study aimed to explore the sub-division classification across the Barossa region using chemical and sensory measurements. Shiraz grapes from 4 different vintages and different vineyards across the Barossa (2018, n = 69; 2019, n = 72; 2020, n = 79; 2021, n = 64) were harvested and made using a standardised small lot winemaking procedure. The analysis involved a sensory descriptive analysis with a highly trained panel and chemical measurement including basic chemistry (e.g. pH, TA, alcohol content, total SO2), phenolic composition, volatile compounds, metals, proline, and polysaccharides. The datasets were combined and analysed through an unsupervised, clustering analysis. Firstly, each vintage was considered separately to investigate any vintage to vintage variation. The datasets were then combined and analysed as a whole. The number of sub-divisions based on the measurements were identified and characterised with their sensory and chemical profile and some consistencies were seen between the vintages. Preliminary analysis of the sensory results showed that in most vintages, two major groups could be identified characterised with one group showing a fruit-forward profile and another displaying savoury and cooked vegetables characters. The exploration of distinct profiles arising from the Barossa wine producing region will provide producers with valuable information about the regional potential of their wine assisting with tools to increase their target market and reputation. This study will also provide a robust and comprehensive basis to determine the distinctive terroir characteristics which exist within the Barossa wine producing region.

Phenological characterization of a wide range of Vitis Vinifera varieties

In order to study the impact of climate change on Bordeaux grape varieties and to assess the adaptation capacities of candidates to the grape varieties of this wine region to the new climatic conditions, an experimental block design composed of 52 grape varieties was set up in 2009 at the INRAE Bordeaux Aquitaine center. Among the many parameters studied, the three main phenological stages of the vine (budburst, flowering and veraison) have been closely monitored since 2012. Observations for each year, stage and variety were carried out on four independent replicates. Precocity indices have been calculated from the data obtained over the 2012-2021 period (Barbeau et al. 1998). This work allowed to group the phenological behaviour of the grapevine varieties, not only based on the timing of the subsequent developmental stages, but also on the overall precocity of the cycle and the total length of the cycle between budburst and veraison. Results regarding the variability observed among the different grape varieties for these phenological stages are presented as heat maps.