Long-lasting flavour perception of wines treated with oenological additives considering the individual PROP taste-phenotype

SO2 play a major role in wine stability and evolution during its aging and storage. Winemaking without SO2 is a big challenge for the winemakers since the lack of SO2 affects directly the wine chemical evolution such as the aromas compounds as well as the phenolic compounds. During the red wine aging, phenolic compounds such as anthocyanin, responsible of the red wine colour, and tannins, responsible of the mouthfeel organoleptic properties of wine, evolved quickly from the winemaking process to aging [1]. A lot of new interaction and molecules occurred lead by oxygen[2] thus the lack of SO2 will induce wine properties changes. Nowadays, the phenolic composition of the wine without added SO2 have not been clearly reported.

Biostimulants and biofertilizers are considered environmentally friendly and cost-effective alternatives to synthetic fertilizers, plant growth regulators and crop improvement products. Broadly, plant biostimulants are expected to improve nutrient use efficiency, tolerance to abiotic stress, quality traits and availability of nutrients in the soil or rhizosphere. Currently, seaweed extracts account for more than 33% of the total plant biostimulant market. Within this category, Ascophyllum nodosum (AN), is the most widely studied and applied in biostimulant formulations.

Granxa D’Outeiro is a recovered ancient vineyard located in the heart of DOP Ribeiro, where traditional white grapevine varieties are growing under sustainable management. Spontaneous fermentations using grape must from Treixadura, Albariño, Lado, Godello, and Loureira varieties were carried out at experimental winery of Evega. Yeasts were isolated from must and at different stages of fermentation. Those colonies belonging to Saccharomyces cerevisiae were characterized at strain level by mDNA-RFLPs.

By dissecting the root system architecture (RSA) into its underpinning components (e.g. root emission, axial growth, radial growth, branching, root direction or tropism) and identifying the relationships between them, functional-structural 3D root models are promising tools for analyzing the diversity and complexity of root system phenotypes with Genotype × Environment interactions. The model parameters are assumed to be synthetic traits, less influenced by the environment, and consequently with less polygenic architectures than the integrative RSA traits they drive. Root models can serve as a basis for in silico development of root system ideotypes by highlighting the developmental processes and parameters that most likely influence RSA fitness.

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