Effects of major enological variables on the evolution of the chemical profile in Schiava over the vinification: an experimental design approach

In the Champagne’s region, a complete press cycle is a series of pressure increases (squeezes) and decreases (returns). After alcoholic fermentation, the two wines (the “cuvee” and the “tailles”) obtained from grape juice fractions exhibit strong differences for numerous characteristics. Nevertheless, there is no study of the impact of the press cycle, followed after each pressure increase (22-28 steps), on wine colour, current analyses and phenolic composition. So, the aim of this study (vintage 2020) was to investigate the composition changes of Pinot noir and Pinot meunier wines, produced from 22-28 grape juices isolated for each complete pressing cycle.

‘Tempranillo Tinto’ is one of the most relevant grapevine cultivars worldwide. Despite its early ripening and relatively short vegetative cycle, which may not be ideal for high-quality grape and wine production in warming conditions, its long-standing cultivation has led to an intense multiplication by cuttings, which originated the high level of clonal variation currently available. Now, this intra-varietal diversity provides an interesting opportunity for cultivar improvement by identifying genotypes with better adaptation potential.

The yeast residue left over after wine-making, known as wine yeast lees, is a source of various compounds that are of interest for wine and food industry. In winemaking, yeast-derived glycocompounds and proteins represent an example of circular economy approach since they have been proven to reduce the need for bentonite and animal-based fining agents. This leads to a reduced environmental impact in the stabilization and fining processes in winemaking. (de Iseppi et al., 2020, 2021).

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.

In red wine production, phenolic maturity is becoming increasingly important. Anthocyanins, flavonoids and total polyphenols content and availability significantly influence the harvest time of wine grapes while, during vinification process, their extraction strongly affects wine body, color and texture