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.

For a long time, cool climate grapevine breeding has striven for early ripening cultivars to adapt to the former climate conditions.

In this video recording of the IVES science meeting 2021, Benjamin Bois (Institut Universitaire de la Vigne et du Vin – IUVV, Université de Bourgogne, Dijon, France) speaks about zoning the climatic potentialities and risk of vineyards & wine production regions. This presentation is based on an original article accessible for free on OENO One

The winegrowing sector consumes a lot of pesticides. Changes in vineyard are necessary in order to reduce or even stop using pesticides, and thus limit their harmful impacts on health and on environment. To answer these issues, the VITAE project (2021-2026) aims at designing pesticide free grapevine systems in France. For that, we take an interest in the vineyards using solutions to strongly reduce chemicals but also biopesticides. We assume that such vineyards exist and that they are implementing solutions that could inspire the design of free- pesticide system.

Une variable composite, dénommée Indice de Site (SI), intégrant les propriétés physiques du sol et le mésoclimat, avait été proposée pour caractériser les terroirs dans le cadre d’une étude des vignobles de Cabernet Sauvignon de Hawke’s Bay en Nouvelle Zélande.