Leaf vine content in nutrients and trace elements in La Mancha (Spain) soils: influence of the rootstock

This study examines, from the perspective of the employees at Bosque de Matasnos—a demonstrative winery participating in the LIFE Climawin project—the socioeconomic impact and potential contributions of the initiative to the wine sector and the sustainable development of the Ribera del Duero region in Spain.

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.

Grape phenolic content is an important quality factor that influences the appearance and mouthfeel of premium red wines.

From the chemical angle, Champagne wines are complex hydro-alcoholic mixtures supersaturated with dissolved carbon dioxide (CO₂). During the pouring process and throughout the several minutes of tasting, the headspace of a champagne glass is progressively invaded by many chemical species, including gas-phase CO₂ in large majority. CO₂ bubbles nucleated in the glass and collapsing at the champagne surface act indeed as a continuous paternoster lift for aromas throughout champagne or sparkling wine tasting [1]. Nevertheless, inhaling a gas space with a concentration of gaseous CO₂ close to 30% and higher triggers a very unpleasant tingling sensation, the so-called “carbonic bite”, which might completely perturb the perception of the wine’s bouquet.

In this video recording of the IVES science meeting 2023, Hans Reiner Schultz (Hochschule Geisenheim University, Germany) speaks about soil carbon changes and greenhouse gas emissions in vineyards – is the 4 per 1000 goal realistic?. This presentation is based on an original article accessible for free on OENO One.