Diversity in grape composition for sugars and acidity opens options to mitigate the effect of warming during ripening

Grapevine breeding is part of the research program of Agroscope in Switzerland since 1965. From 1965 to 1995, the aim of the Vitis vinifera crosses was to obtain a high resistance to grey rot (Botrytis cinerea), one of the most virulent fungal pathogens in the Swiss vineyard. In 2021, the grape varieties released from this first breeding program covered 936 ha of the 15’000 ha of the Swiss vineyard.
In 1996, a second breeding program aimed at obtaining, by classical interspecific hybridization, grape varieties resistant to downy mildew (Plasmopara viticola) and powdery mildew (Erisyphe necator) and less sensitive to grey rot (Botrytis cinerea). In order to accelerate and make the selection process more reliable, an early biochemical test was developed based on the natural defense mechanisms of the vine against downy mildew (stilbene phytoalexins). The synthesis of stilbenes (i.e., resveratrol and its oxidized dimers - and -viniférine) and pterostilbenes (methylated derivative) is among the most efficient induced defense mechanisms of grapevine against fungal pathogens on both the leaves and the clusters.

Climate change has led to increased extreme weather events, such as severe droughts and intense rainfall, with regions like Alentejo and Algarve in Portugal, being particularly affected.

Wine production with non-Saccharomyces yeasts is getting larger application due to the positive impact of these yeasts on wine composition. Previous studies showed notably differences in chemical composition of Merlot wines obtained with Torulaspora delbrueckii.

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.

Drought stress has a profound impact on grapevine productivity and significantly alters key quality-related traits of berries. Although research has been conducted on the effects of individual drought events, there is still a knowledge gap regarding the cumulative consequences of repeated exposure to water scarcity and the influence of the timing of stress imposition. To address this gap, a field experiment was conducted to investigate the impacts of repeated drought stress on yield, berry composition, and the phenolic profile of grape berries. The results indicate that yield is primarily influenced by pre-veraison water deficit. Although the number of clusters was only slightly reduced, a substantial decrease in berry size was observed, resulting in a notable reduction in overall yield.