Identification of a stable epi-allele associated with flower development and low bunch compactness in a somatic variant of Tempranillo Tinto

In order to study the impact of climate change on Bordeaux grape varieties and to assess the behavior of candidate grape varieties potentially better adapted to the new climatic conditions, an experimental vineyard composed of 52 grape varieties was planted in 2009 at the INRAE Bordeaux Aquitaine center[1]. Among the many parameters studied since 2012, berry weight for each variety was measured weekly from mid-veraison to maturity, with four independent replicates. The kinetics obtained allowed to study berry growth, a key parameter in grape composition and yield.

Grapevine vigour, defined as the propensity to assimilate, store and/or use non-structural sugars for allowing fast growth of shoots and producing large canopies[1], is crucial to optimize vineyard management. Recently, a model has been proposed for predicting the vigor of young grapevines through the measurement of the vegetative growth and physiological parameters, such as water status and gas exchange[2]. Our objectives were (1) to explore the influence of the association of two grapevine varieties (Tempranillo and Cabernet Sauvignon, grafted onto R110 rootstocks) with arbuscular mycorrhizal fungi (AMF) on the vegetative vigour of young plants; and (2) to assess the effect of environmental factors linked to climate change on the vegetative vigour of Cabernet Sauvignon.

One of the main aspects of Climate Change is the increase of temperatures during summer and grape maturity period. Physiological processes are influenced by these high temperatures and result in grapes with higher sugar concentration, less acidity and less anthocyanin content among other quality changes. One strategy to deal with the climate change effects is the implementation of late winter pruning to alter the effect of high temperatures during key periods by delays in maturity time.

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).

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].