Study of wine-growing land (“terroir”) characteristics in the canton of Vaud (Switzerland): ecophysiological behaviour of the vine (cv. Chasselas)

Trichoderma is a microorganism present in many agricultural soils and some of its species could be used as natural biological control agents. In this work, the presence of natural populations of Trichoderma was estimated in soil vineyard and its biocontrol capacity against Phaeoacremonium minimum, one of the main agent causals of grapevine trunk diseases instead of using pesticides. Moreover, physicochemical variables in soil such as pH, organic matter and nutrients were evaluated to determine a possible correlation to natural populations of Trichoderma.

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.

Nowadays, the rapid growth of vineyards with organic practices and the use of copper as the only fun-gicide against downy mildew raises again the question of the effect of copper on varietal thiols in wine, especially 3-sulfanylhexan-1-ol (3SH) and its acetate (3SHA). A few decades ago, several works indicated that the use of copper in the vineyard had a negative effect on the content of varietal thiols in Sauvignon blanc wines [1, 2]. However, these studies only considered the concentration of the reduced form (RSH) of varietal thiols, without quantifying the oxidised ones. For this purpose, we proposed to monitor both reduced and oxidised forms of varietal thiols in wine under copper stress during alcoholic fermentation to have a more complete picture of the biological and chemical mechanisms.

In this video recording of the IVES science meeting 2023, Jordi Ballester (Centre des sciences du goût et de l’alimentation, CNRS, INRAE, Institut Agro, Université Bourgogne Franche-Comté, Dijon, France) speaks on how to make a mineral wine, producers’ representations vs. scientific data. This presentation is based on an original article accessible for free on OENO One.

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.