Controlling Wine Oxidation: Effects of pH on Key Reaction Rates

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

In the study of terroir, a separate analysis of its many component factors can be of great help in accurately identifying a vineyard’s natural elements that impact wine quality and typicity. This research used a dedicated pluri-disciplinary approach to investigate the ecological characteristics, including geology and geographical features, of 14 vineyards that produce Gewürztraminer and Sauvignon Blanc cultivars in the alpine Alto Adige DOC wine region. Both the geopedological method using Vineyards Geological Identity (VGI) and the new Solar Radiaton Identity (SRI) topoclimatic classification method were used to provide analytical measurements and qualitative/quantitative characterisations. In addition, wide-ranging targeted and untargeted oenological and chemical analyses were carried out on grapes, musts and wines to correlate the soils’ geomineral and physical conditions with the biochemical properties of their fruits and wines. The research identified strong correlations between vineyard geo-identity and wine biofingerprint, confirming a mineral traceability of strontium rubidium ratio and some minerals distinctive to the local geology, such as K, Ca, Ag, Ba and Mn.  The study also discovered that particular geomineral and physical soil conditions of the studied vineyards are related to the different amount of amino acids, primary varietal aromas and polyphenols found in grapes, musts and wines. The research confirmed that winemaking technologies support oenological quality, although in some cases, human practices can overpower certain characteristic elements in wine, erasing the typical imprint left by the vineyards’ natural terroir, which becomes less traceable. Terroir abiotic ecological factors and vineyard identity can be classified in detail using the new VGI and SRI analysis methods to discover interrelationships between geo-pedological and topoclimatic conditions that impact wine quality. These methods are also helpful in identifying which ecological elements are exclusive to a particular vineyard or wine sub-region.

A gradual decline in vineyards has been observed over the past twenty years worldwide. This might be explained by the climate change, practices change or the increase of dieback diseases. To increase the longevity of vines, we studied the impact of different pruning strategies in four adult and four young vineyards located in France and Spain. In France, vineyards were planted with Cabernet franc on 3309C while Spanish trials were planted with Tempranillo grafted on 110R. Vegetative expression, yield, quality of berries and wood vessels conductivity were measured. The distribution of vegetative expression, yield and berry composition between primary and secondary vegetation were quantified. Finally, tomography was used to evaluate the implication of the treatments on sap flows.
First results show that i) the respectful pruning leads to an increase of 30 to 50% more secondary shoots than the aggressive pruning in France and between 15 and 20% in Spain, ii) there is no major effect on the yield over the first two years following the implementation of the new pruning practices, although the proportion of clusters from suckers is higher on the respectful pruning method. On young vines, the development of the trunk according to a respectful pruning leads to a loss of harvest 2 years after planting. This is due to the removal, on the future trunk, of the green suckers which carrying bunches. This operation carried out in spring rather than during winter pruning, would promote a better leaf / fruit balance when the plant comes into production, and could lead to better hydraulic conduction in the vessels of the trunk. Maintaining these trials for several years will provide more robust data to assess the impact of these practices on the vines over the long term.

The aim of this work was to analyze the variability in grape composition of the Tempranillo cultivar related to climatic conditions, in La Mancha Designation of Origin. Grape composition (sugar content, total acidity, pH, malic acid, and total and extractable anthocyanins) recorded during ripening, were analysed for the period 2000-2019. The weather conditions at daily time scale, recorded during the same period, were also evaluated. The relationships between grape parameters with climatic variables related to temperature and to water deficits, referring different periods between phenological events along the growing cycle, were evaluated using regression analysis. High variability in grape composition was observed in the period analysed. Total acidity varied between 3.7 and 7.3 gL-1 while malic acid varied between 1.2 and 4 gL-1. The extractable anthocyanins ranged between 526 and 972 mgL-1, and total anthocyanins ranged between 922 and 1388 mgL-1, being the lowest values recorded in the hottest year (2017). Total acidity decreased 0.77 gL-1 for an increase of 100 GDD, while malic acid decrease in 0.42 gL-1 for the same GDD increase, being the period between veraison and harvest the one that seemed to have higher influence on acidity. In addition, it was confirmed that increasing water deficits decreased acidity. Total and extractable anthocyanins increased in about 210 and 105 mgL-1, respectively, with an increase of 100 GDD from veraison to harvest, and the increase in water deficits favour the increase of anthocyanins, both total and extractable anthocyanins. Total and extractable anthocyanins concentration increased in 35 and 22 mgL-1 per an increase of 10 mm in the water deficit. These results can be of interest to understand the potential changes that grapes composition may suffer under future warmer climates.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.