On sample preparation methods for fermentative beverage VOCs profiling by GCxGC-TOFMS

Grapevine breeding is part of the research program of Agroscope in Switzerland since 1965. From 1965 to 1995, the aim of the Vitis vinifera crosses was to obtain a high resistance to grey rot (Botrytis cinerea), one of the most virulent fungal pathogens in the Swiss vineyard. In 2021, the grape varieties released from this first breeding program covered 936 ha of the 15’000 ha of the Swiss vineyard.
In 1996, a second breeding program aimed at obtaining, by classical interspecific hybridization, grape varieties resistant to downy mildew (Plasmopara viticola) and powdery mildew (Erisyphe necator) and less sensitive to grey rot (Botrytis cinerea). In order to accelerate and make the selection process more reliable, an early biochemical test was developed based on the natural defense mechanisms of the vine against downy mildew (stilbene phytoalexins). The synthesis of stilbenes (i.e., resveratrol and its oxidized dimers - and -viniférine) and pterostilbenes (methylated derivative) is among the most efficient induced defense mechanisms of grapevine against fungal pathogens on both the leaves and the clusters.

SO2 is an additive widely used as antimicrobial in winemaking industry. However, this compound can negatively affect health, so the search for alternatives is currently a line of research of great interest. One of the proposed alternatives to SO2 as an antimicrobial is the use of bioprotection yeasts, which colonize the medium preventing the proliferation of undesirable microorganisms.

To assess the relationship between the reported low-stability of Tannat colour during wine storage and its pigment composition and evolution

In recent studies, several grapevine trunk pathogen complexes have been identified from grapevines in South Africa. These pathogens include Eutypa lata, Phaeomoniella chlamydospora, Phaeoacremonium sp., Botryosphaeria sp. and Phomopsis sp. Trunk diseases lead to reduced yield, and grape quality as well as a decline

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.