Volatile composition of Cabernet Sauvignon wines from Argentina, Portugal and Spain

Grapevine leaves are known to contain different polyphenols such as flavonols, catechins and stilbenes, which are known to act as main contributors for plant defense against pathogens (1). While the composition for some major cultivars has been studied, there is lack of systematic comparison about the content of these compounds in the wide ecodiversity of Vitis vinifera cv. Recent advances in Mass Spectrometry-based Metabolomics allow a wider and more sensitive description of these polyphenols, as instance of those present in leaves (2). Such information could help to better explain leaf traits regarding the development of the leaf or to the plant tolerance to a pathogen. Moreover, these compounds offer appealing applications for human health due to their antioxidant activities.

The actual climate changes, together with the strong regulation of the European Union and Spanish government, in search of sustainable viticulture, have forced the recovery of minority varieties, expanding the range of grape varieties, as well as the possible development of wines with unique profiles. In the Ribeira Sacra DO (Spain), a comparative study of the agronomic and qualitative behavior of the ‘Branco lexítimo’ variety has been carried out, compared to the majority white variety in the DO: ‘Godello’, located in the same study plot, with identic soil and climatic conditions. The study contemplated the analysis of phenology and leaf water potential, as well as the productive results and the analysis of the must quality, during four seasons: 2018 – 2021.

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).

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.

This study aimed to validate a protocol and compare metrics for evaluating drought tolerance in two Vitis vinifera grapevine cultivars under field conditions. Various metrics were calculated to represent the physiological responses of plants to progressive water deficit. Data were collected from Sauvignon Blanc and Chardonnay plants subjected to three irrigation levels during the 2022-2023 season, along with data from three previous seasons. Hydro-escape areas were used to assess the plant’s ability to reduce water potential with decreasing soil water availability.