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.

Terroir zoning studies have to manage the heterogeneity and complexity of the landscape properties and processes. The varying geology is one of the main landscape properties conditioning the spatial variability of terroirs.

l Veneto, come è noto, rappresenta una delle estensioni di superfici a vigneto più importanti in Italia e nell’Europa stessa. Il paesaggio viticolo fino ad oggi è stato ampiamente letto nelle sue componenti

In this video recording of the IVES science meeting 2021, Fulvio Mattivi (Fondazione Edmund Mach, Centro Ricerca ed Innovazione, San Michele all’Adige, Italy) speaks about the effects of water deficit on secondary metabolites in grapes and wines. This presentation is based on an original article accessible for free on OENO One.

Currently, to consistently ensure the maintenance of a wine-style while benefiting from the utmost rigor made possible by the winemaking process, the composition of the wine blend is made using sensory control. This is performed after the wine is made with no real possibility of deterministic intervention.