Genetic determinism of grapevine development stages as a tool for the adaptation to climate change

Amino acids are crucial nitrogen sources in yeast metabolism, influencing both biomass production and fermentation rate. The breakdown byproducts of amino acids contribute to the aroma of the wine and wine’s health benefit compounds. This study focused on the yeast’s extracellular metabolic profile of tryptophan, tyrosine, and phenylalanine belonging to the group of aromatic amino acids in experimental Maraština wines. Alcoholic fermentations were conducted on sterile grape Maraština must using seven autochthonous non-Saccharomyces yeasts in sequential fermentation with commercial Saccharomyces cerevisiae.

In white wines, Verdejo wine stands out because of its high content in total amino acids. The total content in biogenic amines was low in all wines analyzed and putrescine was the predominant biogenic amine.

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.

Plant roots fulfil important functions as they are responsible for the acquisition of water and nutrients, for anchorage and stability, for interaction with symbionts and, in some cases, for the storage of carbohydrates. These functions are associated with the Root System Architecture (RSA, i.e. the form and the spatial arrangement of the roots in the soil). The RSA results from several biological processes (elongation, ramification, mortality…) genetically determined but with high structural plasticity.

Erysiphe necator Schwein is a fungus that causes grapevine powdery mildew. It is one of the most problematic pathogens attacking Vitis vinifera L. The pathogen infects all green parts of the plant and reduces grape yield and quality. The suppression on mildew-susceptible cultivars requires intensive use of fungicides against pathogen, which has negative impact on the environment and human health.