Landscapes of Vines and Wines Patrimony – Stakes – Valorisation

Aging process is an essential stage in the improvement of wine quality. This process is usually performed by contact with oak wood whose compounds are released and transferred to wine, acquiring typical aging bouquet. Although the use of oak chips is a practice generally accepted as alternative to barrels to shorten aging process, the application of emerging technologies is being unfolded to accelerate this stage.

AIM: Since 2012 the Veneto Region regulation (north-east Italy) allowed wine production using 20 hybrid grapevine varieties selected for their high tolerance to downy mildew and powdery mildew. Characterized by vigour, high grape productivity and low pesticide use, these varieties are suitable to develop sustainable viticulture in mountain areas located at medium altitudes.

Nitrogen and temperature are two important factors that influence wine fermentation and volatile compounds production. Among the different compounds present in the must, nitrogen is an essential nutrient for the management of the fermentation kinetics but it also plays an important role in the synthesis of fermentative aromas. To address the problems related to nitrogen deficiencies, nitrogen additions during alcoholic fermentation have been developed.

Deciphering grapevine dormancy is crucial in the current context of climatic challenges: advancing budburst phenology and increased late frost probabilities, observed in the last decades and expected to further increase, require deeper understanding. Beyond higher mean temperatures, abiotic stresses such as water deficit have also been emphasized as actors. In this framework, we aimed at exploring new methodologies for tracking dormancy cycle and testing the interplay on its regulation of temperature dynamics and drought.
In a first experiment, twenty-one Vitis vinifera varieties were monitored during ecodormancy and budburst over three years.

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.