 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

Adaptability of grapevines to climate change: characterization of phenology and sugar accumulation of 50 varieties, under hot climate conditions

Climate is the major factor influencing the dynamics of the vegetative cycle and can determine the timing of phenological periods. Knowledge of the phenology of varieties, their chronological duration, and thermal requirements, allows not only for the better management of interventions in the vineyard, but also to predict the varieties’ behaviour in a scenario of climate change, giving the wine producer the possibility of selecting the grape varieties that are best adapted to the climatic conditions of a certain terroir. In 2014, Symington Family Estates, Vinhos, established two grape variety libraries in two different places with distinctive climate conditions (Douro Superior, and Cima Corgo), with the commitment of contributing to a deeper agronomic and oenological understanding of some grape varieties, in hot climate conditions. In these research vineyards are represented local varieties that are important in the regional and national viticulture, but also others that have over time been forgotten — as well as five international reference cultivars. From 2017 to 2021, phenological observations have been made three times a week, following a defined protocol, to determine the average dates of budbreak, flowering and veraison. With the climate data of each location, the thermal requirements of each variety and the chronological duration of each phase have been calculated. During maturation, berry samples have been gathered weekly to study the dynamics of sugar accumulation, between other parameters. The data was analysed applying phenological and sugar accumulation models available in literature. The results obtained show significant differences between the varieties over several parameters, from the chronological duration and thermal requirements to complete the various stages of development, to the differences between the two locations, confirming the influence of the climate on phenology and the stages of maturation, in these specific conditions.

Effect of multi-level and multi-scale spectral data source on vineyard state assessment

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Climate modeling at local scale in the Waipara winegrowing region in the climate change context

In viticulture, a warming climate can have a very significant impact on grapevine development and therefore on the quality and characteristics of wines across different spatial scales, ranging from global to local. In order to adapt wine-growing to climate change, global climate models can be used to define future scenarios, but only at the scale of major wine regions. Despite the huge progress made over the last ten years in terms of the spatial resolution of climate models (now downscaled to a few square kilometres), they are not yet sufficiently precise to account for the local climate variability associated with such parameters as local topography, in spite of these parameters being decisive for vine and wine characteristics. This study describes a method to downscale future climate scenarios to vineyard scale. Networks of data loggers have been used to collect air temperature at canopy level in the Waipara winegrowing region (New Zealand) over five growing seasons. These measurements allow the creation of fine-scale geostatistical models and maps of temperature (at 100 m resolution) for the growing season. In order to model climate change at pilot site scale, these geostatistical models have been combined with regional climate change predictions for the periods 2031-2050 and 2081-2100 based on the RCP8.5 climate change scenario. The integration of local climate variability with regionalized climate change simulations allows assessment of the impacts of climate change at the vineyard scale. The improved knowledge gained using this methodology results from the increased horizontal resolution that better addresses the concerns of winegrowers. The results provide the local winegrowers with information necessary to understand current processes, as well as historical and future viticulture trends at the scale of their site, thereby facilitating decisions about future response strategies.

Use of a new, miniaturized, low-cost spectral sensor to estimate and map the vineyard water status from a mobile

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

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.