Research on the origin and the side effects of chitosan stabilizing properties in wine

Due to ongoing climate change, managing vineyard diseases has become increasingly challenging in the Republic of Moldova.

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.

L’étude des relations Terroir – Vigne – Raisin est complexe. La recherche et le développement des facteurs qualitatifs qui influencent le caractère des vins sont multiples. Divers travaux mettent en évidence la relation entre l’alimentation en eau de la plante, son développement végétatif et les caractéristiques de ses raisins.

Sémillon is a cultivated grape variety known for contributing to dry and sweet white wine production. However, only seven approved clones have been officially recognized in France[1]. In this study, we aimed to characterize the genetic diversity and metabolomic profiles of a Sémillon clonal population, shedding light on the potential variations within this important grape variety.

Ultrafiltration is a process that fractionates mixtures using semipermeable membranes, primarily on the basis of molecular weight. Depending on the nominal molecular weight cut-off (MWCO) specifications of the membrane, smaller molecules pass through the membrane into the ‘permeate’, while larger molecules are retained and concentrated in the ‘retentate’. This study investigated applications of ultrafiltration technology for enhanced wine quality and profitability. The key objective was to establish to what extent ultrafiltration could be used to manage phenolic compounds (associated with astringency or bitterness) and proteins (associated with haze formation) in white wine.