Effect of foliar application of Ca, Si and their combination on grape volatile composition

Remote sensing technology captures spectral data beyond the visible range, making it useful for monitoring plant stress. Vis-NIR (Visible-Near Infrared) spectroscopy (400-1000 nm) is commonly used to indirectly assess plant status during drought. One example is the widespread use of normalized difference vegetation index (NDVI) that is strongly linked to green biomass. However, a knowledge gap exists regarding the applicability of this method to all the drought conditions and if it is a direct correlation to the water status of the plant.

One of the limitations of vineyards in warm areas is the loss of wine quality due to higher temperatures during the grape ripening period. In order to adapt the vineyards to these new climatic conditions, a possible solution is to delay the ripening process of the grapes towards periods with milder temperatures, by means of management practices and thus improve the quality of the fruit and the wine produced. The technique of severe shoot pruning (SSP) has proven useful in achieving this objective.

Grape and wine phenolic compounds have been shown to be highly related to both wine quality (color, flavor, and taste) and health-promoting properties (antioxidant and cardioprotective, among others). The aim of this work was to evaluate and compare the phenolic contents of Cabernet Sauvignon wines from different geographical areas and climatic conditions, namely from Argentina, Portugal and Spain vintage 2022. In addition, the phenolic profiles of the Portuguese wines from three vintages (2020, 2021, 2022) was compared.

For sustainable viticulture, the substitution of chemical inputs with biocontrol products has become one of the most considered strategies. This strategy is based on elicitor-triggered immunity that requires a deep understanding of the molecular mechanisms involved in plant defense activation. Plant immune responses are triggered through the perception of conserved microbe-associated molecular patterns (MAMPs) which are recognized by pattern recognition receptors (PRRs) at the plasma membrane.

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.