The viticulture aiming at the production of high quality wine is very important for the landscape conservation, because it allows to combine high farmer income with soil conservation

La topographie du vignoble de Côte Rôtie, la prédominance de la non culture ainsi que la structure très légère des sols amènent les vignerons à s’interroger sur l’entretien du sol, la conduite de la fertilisation de leurs parcelles ainsi que sur le développement racinaire de la vigne.

One of the main aspects of Climate Change is the increase of temperatures during summer and grape maturity period. Physiological processes are influenced by these high temperatures and result in grapes with higher sugar concentration, less acidity and less anthocyanin content among other quality changes. One strategy to deal with the climate change effects is the implementation of late winter pruning to alter the effect of high temperatures during key periods by delays in maturity time.

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.

[English version below]

A tre anni dal suo inizio, nel 1997 si è conclusa la prima fase della ricerca “Caratterizzazione della produzione DOC Soave”. Lo studio ha basato il suo percorso sperimentale su alcuni punti fondamentali tra i quali:
• Recupero di tutte le informazioni storico-colturali sul vino Soave e sul suo territorio di produzione.