«Observatoire Mourvèdre»: statistical modelling of quality for Cv. Mourvèdre

Research is focused on the increase of the field of obtaining the wine yeast, under physical and chemical conditions. Study of different influences on yeast production is very important for the promotion

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.

Trebbiano di Lugana (TdL) is a white variety of Vitis vinifera mainly cultivated in an Italian area located south near Garda lake (Verona, north of Italy). This grape cultivar, also known as “Turbiana,” is used for the production of TdL wine with recognized Protected Designation of Origin whose volatile profile was recently determined [1]. The presence of varietal thiols in TdL, namely 3-mercaptohexan-1-ol and its acetate form, conferring the tropical and citrus notes, has been documented. Winemaking strategies were also described with the purpose of protecting and maintain these desired aromas [2]. To the best of our knowledge, the varietal thiol precursors (VTPs) were not previously determined in TdL grape and must. This study aimed to quantify VTPs in both grape during the ripening and must during the pressing. Volatile C6 compounds were also measured in the must fractions.

In the next years the territorial environmental certification could become realistic if the following conditions will be fully satisfied:
– the enhancement of the environmental awareness among the industries, the public administration, the authorization bodies, the living people of that territory as well as the tourists and visitors.

Grape volatile compounds are mainly responsible for wine aroma, so it is important to know the va-rietal aromatic composition throughout ripening process. Currently, there are no tools that allow mea-suring the aromatic composition of grapes, in intact berries and periodically, throughout ripening, in the vineyard or in the winery. For this reason, this work evaluated the use of near infrared spectroscopy (NIR) to estimate the aromatic composition and total soluble solids (TSS) of Tempranillo Blanco berries during ripening. For this purpose, NIR spectra (1100-2100 nm) were acquired from 240 samples of in-tact berries, collected at different dates, from veraison to overripening.