Production and technological characteristics of some French clones of the Chardonnay variety in Yugoslavia

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.

Presentknowledge about grape development is mainly driven by the premise that a typical berry would follow the same kinetics as the population average

The work aims to characterise the colour features of the wines of two new resistant varieties breeeded at the Edmund Mach Foundation (Italy) and recently inscribed in the Italian National Registriy of Vine Varieties.

In winemaking, several antimicrobial peptides (AMPs) produced by different strains of Saccharomyces cerevisiae were found to be responsible for the inhibition of malolactic fermentation (MLF) carried out by some strains of Oenococcus oeni. However, only two AMPs produced by one of the yeast strains studied were totally identified and their mechanism of action was described. In an attempt to identify new AMPs, a 5-10 kDa peptidic fraction produced by an oenological strain of S. cerevisiae and previously shown to strongly inhibit MLF carried out by a strain of O. oeni was further purified.

Hanseniaspora vineae (Hv) is a fermenting non-Saccharomyces yeast that compared to Saccharomyces cerevisiae (Sc) present some peculiar features on its metabolism that make it attractive for its use in wine production. Among them, it has been reported a faster yeast lysis and release of polysaccharides, as well as increased ß-glucosidase activity. Hv also produces distinctive aroma compounds, including elevated levels of fermentative compounds such as ß-phenylethyl acetate and norisoprenoids like safranal. However, it is known for its high nutritional requirements, resulting in prolonged and sluggish fermentations, even when complemented with Sc strain and nutrients.