Integrative study of Vitis biodiversity for next-generation breeding of grapevine rootstocks 

Brandy is a spirit drink made from “wine spirit” (<86% Alcohol by Volume – ABV; high levels of congeners and they are mainly less volatile than ethanol), it may be blended with a “wine distillate” (<94.8%ABV; low levels of congeners and these are mainly more volatile than ethanol), as long as that distillate does not exceed a maximum of 50% of the alcoholic content of the finished product[1]. Brandy must be aged for at least 6 months in oak casks with <1000L of capacity. During ageing, changes occur in colour, flavour, and aroma that improve the quality of the original distillate.

Reducing sugar accumulation in grape (Vitis vinifera L.) berries may be a way to mitigate the effect of climate change. Managing canopy and crop load is an effective way to do so, however, reducing canopy size has been demonstrated to induce undesirable effects on anthocyanins. The aim of this study was to test if an application of exogenous ABA on the grape berries of defoliated vines (⅔ of the leaves removed) can result in slower sugar accumulation while maintaining grape and wine quality. An experiment with defoliation and exogenous ABA application on directly on clusters (factorial design 2×2) was performed with ‘Tempranillo’ fruit-bearing cuttings.

Measuring the effect of oxygen consumption on the color of wines as the level of dissolved oxygen decreases over time is very useful to know how much oxygen a wine can consume without significantly altering its color. The changes produced in wine after being exposed to high oxygen concentrations have been studied by different authors, but in all cases the wine has been analyzed once the oxygen consumption process has been completed. This work presents the results obtained with the use of an equipment designed and made to measure simultaneously the level of dissolved oxygen and the spectrum of the wine, during the oxygen consumption process from saturation levels with air to very low levels, which indicate the total consumption of the dosed oxygen[1,2].

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.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).