Impact of temperature and solar radiation on grape composition variability in the Saint-Emilion winegrowing area 

Ultra High-Pressure Homogenization (UHPH) is a high-pressure pumping at 300 MPa (>200 MPa) with a subsequent depressurization against a highly resistant valve made of tungsten carbide covered by ceramic materials or carbon nanoparticles. The intense impact and shear efforts produce the nano-fragmentation of colloidal biopolymers including the elimination of microorganism (pasteurization or sterilization depending on in-valve temperature) and the inactivation of enzymes.

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.

Condensed grape tannins play a major role in the organoleptic properties and quality of red wine. Recently, a new sub-family of macrocyclic condensed tannins has been identified in red wine and named “crown tannins”. Indeed, the first compound of the family identified and characterised by NMR was the crown procyanidin tetramer which is composed of a macrocyclic structure composed of four (-)-epicatechins link together by B-type interflavanoid linkage in the following an alternative sequences of C4-C8 and C4-C6 linkage. The 3D structure of this unusual crown procyanidin family reveals a central cavity in the molecule [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).

Vine growth circumstances are becoming warmer and drier because of climate change. Higher temperatures advance ripening to a point in the season less conducive to the production of fine wine, while drought reduces yields (Van Leeuwen et al., 2019). Several wine-producing regions around the world have already recognized threats to their viticultural viability (Santos et al., 2020). An economical and cost-effective strategy for adaptation is the employment of late-ripening, drought-resistant plant material (varieties, clones, and rootstocks).