Yeast mannoprotein characterization and their effect on Oenococcus oeni and malolactic fermentation

Botrytis cinerea has more than 1200 host plants and is one of the most important plant pathogens in viticulture. Under certain environmental conditions, it can lead to the development of a noble rot, which results in a specific metabolic profile, altering physical texture and chemical composition. The other microbes involved in this process and their functional genes are poorly characterised. We have generated metatranscriptomic [1,2] and DNA metabarcoding data from three months of the Furmint grape variety, representing the four phases of noble rot, from healthy berries to completely dried berries.

Brettanomyces is a world-renowned yeast that negatively impacts the chemical composition of wines through the production of metabolites that negatively impact the sensory properties of the final product. Its resilience in wine conditions and ability to produce off-flavors make it a challenge for winemakers. Currently, the primary control technique involves adding sulfur dioxide (SO2); however, some Brettanomyces strains are developing resistance to this preservative agent. [1] Therefore, new management strategies are necessary to control this spoilage yeast.

Several studies have tried to develop different methods to study the photodegradation of wine in an accelerated way, trying to elucidate the effect of light on the wine compounds[1]. In a previous study, our team developed a chamber that speeds up the photodegradation of rosé wine[2]. In the present work we have tried to establish a correlation between irradiation times in accelerated conditions and the natural exposure to the cycles of light that usually exist in markets or at home.

In grapevine, phenology from bud break to berry maturation, depends on temperature and water availability. Increases in average temperatures accelerates initiation of bud break, exposing newly formed shoots to detrimental environmental stresses. It is therefore essential to identify genotypes that could delay phenology in order to adapt to the environment. The use of different rootstocks has been applied to change scion’s characteristics, to adapt and resist to abiotic and biotic stresses[1].

The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.