Tolerance to sunburn: a variable to consider in the context of climate change

In recent years, sustainability has become a key focus in agriculture, including viticulture.

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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.

La diffusion récente et “explosive” du Chardonnay dans pratiquement toutes les zones de culture viticole du monde a fait penser, à tort, que cette variété s’adapte facilement à toutes les conditions pédo-climatiques ou presque. Cette thèse a été confirmée par la grande faculté d’adaptation dont a fait preuve le vignoble et par la popularité dont jouit le vin auprès des consommateur du monde entier.

Wine varietal aroma is the result of a mixture of compounds formed or liberated from specific grape-aroma precursors. Their liberation/formation from their specific precursors can occur spontaneously by acid catalyzed rearrangements or hydrolysis or by the action of the yeast enzymatic activities. The influence of yeast during fermentation on the production of these volatile compounds has been widely studied however, the effect of this influence during aging is not fully understood. In order to evaluate these processes several indirect strategies have been used to study aroma precursors although they are not useful to understand the chemistry of the process.