Veraison as determinant for wine quality and its potential for climate adapted breeding

The quality of a wine is largely related to the balance between its sourness, bitterness and sweetness. Recently, molecules coming from grapes have been showed to notably contribute to sweet taste of dry wines. To study the viticultural and oenological parameters likely to affect their concentration, their quantification appears of high interest and subsequently requires powerful analytical techniques. Therefore, a new method using liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) was developed and validated to quantify epi-DPA-3′-O-β-glucopyranoside acid (epi-DPA-G) and astilbin, sweet molecules identified in wine. Three gradients were tested on five different C18 columns (Hypersil Gold, HSS T3, BEH, Syncronis and Kinetex).

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.

In this audio recording of the IVES science meeting 2022, Florence Fontaine (Université de Reims Champagne Ardenne) speaks about grapevine trunk disease. This presentation is based on an original article accessible for free on OENO One.

The utilization of non-Saccharomyces yeasts in the wine industry has increased significantly in recent years. Alternative species need commonly be employed in combination with Saccharomyces cerevisiae to avoid stuck fermentation, or microbial spoilage. The employment of more than one yeast starter can lead to interactions between different species with an impact on the outcome of wine fermentation. Previous studies[1] demonstrated that S. cerevisiae elicits transcriptional responses with both shared and species-specific features in co-culture with other yeast species.

Phenolic ripening represents a major interest for quality wine producers. Nevertheless, climatic or genotypical limitations can often prevent optimal maturation process. During winemaking seeds can be easily separated and technologically processed to improve their quality.