La sémantique liée à la notion de terroir : une objectivité pluridisciplinaire

AIM: ‘Nebbiolo’ (Vitis vinifera L.) is one of the most ancient and prestigious Italian grape cultivars. It is renowned for its use in producing monovarietal high-quality red wines, such Barolo and Barbaresco. Wine quality and value can be heavily modified if cultivars other than those allowed are employed.

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.

High resolution soil maps (scale : 1/3000) were created for seven of the most prestigious red wine producing estates in Bordeaux, covering in total approximately 400 ha.

Bioprotection, leveraging beneficial microorganisms, has emerged as a sustainable approach to modern winemaking, minimizing reliance on chemical preservatives like as sulfur dioxide (SO₂).

‘Cabernet sauvignon’ and ‘Merlot’ are among the most recognized red wine grape cultivars. This work is aimed at investigating the proanthocyanidin composition of skins and seeds to determine the grape variety and the vintage effects on the phenolic composition of Bordeaux grapes.