Wine aging : a bottleneck Story ?

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In classic red wine-making process, grapes are usually destemmed between harvest and the filling of the vat. However, some winemakers choose to let all or a part of the stems in contact with the juice during vatting, this is called whole bunch vinification. For instance, this practice is traditionally used in some French wine regions, notably in Burgundy, Beaujolais and the Rhone Valley. The choice to keep this part of the grape is likely to affect the sensory properties of wine, as its gustatory perception1,2.

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.

Extracellular substances (ECS) represent all molecules outside the cytoplasmic membrane, which are not directly anchored to the cell wall of microorganisms living through a planktonic or biofilm phenotype. They are the high-biomolecular-weight secretions from microorganisms (i.e. extracellular polymeric substances – EPS – proteins, polysaccharides, humic acid, nucleic acid), and the products of cellular lysis and hydrolysis of macromolecules. In addition, some high- and low-molecular-weight organic and inorganic matters from environment can also be adsorbed to the EPS. All can be firmly bound to the cell surface, associated with the EPS matrix of biofilm, or released as being freely diffusing throughout the medium.

The combination of a non-parametric dissimilarity index with auger boring recordings was tested in a project of soil suitability evaluation for quality wine production in a 2000-ha hill slope portion of the “Colli Orientali del Friuli” AOC district (Italy).