Influence of nitrogen supply on colorimetric parameters of Lugana wines

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.

Global warming is one of the biggest environmental, social and economic threats in several viticultural regions. In the Douro Valley, changes are expected in the coming years, namely an increase in temperature and a decrease in precipitation. These changes are likely to have consequences for the production and quality of wine.
The aim of this study was to explore the effects of different soil characteristics combined with several deficit irrigation strategies, managed throughout ETc references and predawn leaf water potentials thresholds, on physiology, yield, and qualitative attributes on the Touriga Nacional variety under years of mild to severe water and heat stress.
The studies were conducted over seven years (2015 to 2021) in two plots of a commercial vineyard located at Quinta do Ataíde (Symington Family Estates) planted in 2011 and 2014 at 170 meters elevation, growing under three water regimes: non-irrigated (NI) and two deficit irrigation strategies (30% and 60% ETc) assessed weekly by Ψpd. The site has an annual rainfall below 500 mm, with high atmospheric demand. Climate data was collected from a weather station, located on site. Berry ripening was followed weekly for fruit analysis. At harvest, yield, vigour and pruning weight per vine were determined from 90 vines by treatment. Each season at veraison the NDVI Index was accessed by a drone. The soils physic-chemistry in the experimental blocs were analysed and grouped by SWHC. Delta C-13 analyses were also performed per treatment in two years.Irrigation had a positive effect on yield per vine, mostly due to an increase in berry and cluster weight, and fertility index through the years. A significant increase in sugar content, colour and phenols was observed with deficit irrigation in some years, but vine vigour related to soil characteristics had by far the greatest impact on quality.

The effects of climate change are seriously affecting the quality of wine grapes. High temperatures and drought cause imbalances in the chemical composition of grapes. The result is overripe grapes with low acidity and high sugar content, which produce wines with excessive alcohol content, lacking in freshness and not very aromatic. As a consequence, the search of varieties with capacity of produce quality grapes in adverse climate conditions is a good alternative to preserve the sustainability of vineyards. In this work, quality parameters of seven Vitis vinifera L. cultivars (five whites and two reds) recently recovered from extinction and grown under two different hydric regimes (rainfed and irrigated) were analyzed during the 2020 vintage. At harvest time, weight of 100 berries, must physicochemical parameters (brix degree, total acidity, malic acid, pH), and carbon and oxygen isotope ratios (δ13C, δ18O) were determined. Subsequently, varietal aroma potential index (IPAv) and total polyphenol index (TPI) were analyzed. Quality parameters, IPAv and TPI, showed significant differences between varieties and water regimes. Both red varieties, Moribel and Tinto Fragoso, stood out for their high aromatic and phenolic potential, which was higher under rainfed regime. Regarding to white varieties, Montonera del Casar and Jarrosuelto stood out in terms of varietal aroma potential. Montonera del Casar high acidity in its musts and Jarrosuelto showed the highest berry weights.

Agriculture, natural resource management and the production and sale of products such as wine are increasingly data-driven activities. Thus, the use of remote and proximal crop and soil sensors to aid management decisions is becoming commonplace and ‘Agtech’ is proliferating commercially; mapping, underpinned by geographical information systems and complex methods of spatial analysis, is widely used. Likewise, the chemical and sensory analysis of wines draws on multivariate statistics; the efficient winery intake of grapes, subsequent production of wines and their delivery to markets relies on logistics; whilst the sales and marketing of wines is increasingly driven by artificial intelligence linked to the recorded purchasing behaviour of consumers. In brief, there is data everywhere!

Opinions will vary on whether these developments are a good thing. Those concerned with the ‘mystique’ of wine, or the historical aspects of terroir and its preservation, may find them confronting. In contrast, they offer an opportunity to those interested in the biophysical elements of terroir, and efforts aimed at better understanding how these impact on vineyard performance and the sensory attributes of resultant wines. At the previous Terroir Congress, we demonstrated the potential of analytical methods used at the within-vineyard scale in the development of Precision Viticulture, in contributing to a quantitative understanding of regional terroir. For this conference, we take this approach forward with examples from contrasting locations in both the northern and southern hemispheres. We show how, by focussing on the vineyards within winegrowing regions, as opposed to all of the land within those regions, we might move towards a more robust terroir zoning than one derived from a mixture of history, thematic mapping, heuristics and the whims of marketers. Aside from providing improved understanding by underpinning terroir with data, such methods should also promote improved management of the entire wine value chain.

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.