New varieties descendant from Monastrell with lower sugar and high phenolic content adapted to warm climates

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.

Due to climate change, the occurrence of heatwaves and drought events is increasing, with significant impact on viticulture. Common ways to adapt viticulture to a changing climate include site selection, genotype selection, irrigation management and canopy management. The latter mentioned being for instance source-sink manipulations, such as leaf removal, with the aim to delay ripening.

The plant rhizosphere microbial communities are an essential component of plant microbiota, which is crucial for sustaining the production of healthy crops. The main drivers of the composition of such communities are the growing environment and the planted genotype. Recent viticulture studies focus on understanding the effects of these factors on soil microbial composition since microbial biodiversity is an important determinant of plant phenotype, and of wine’s organoleptic properties. Microbial biodiversity of different wine regions, for instance, is an important determinant of wine terroir.

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 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).