Effect of abiotic stress and grape variety on amino acid and polyamine composition of red grape berries

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.

The sustainability of viticulture in response to climate change has been addressed mainly considering agronomic impacts, such as water management and diseases, either separately or together.
In grapevines, there is strong evidence that different genotypes respond differently to biotic and abiotic stresses. A screening was conducted on various local cultivars in response to drought and Neofusicoum parvum infection aiming to evaluate their susceptibility to abiotic stress and resistance to fungal diseases.

The odors of wines are diverse, complex and dynamic and much research has been devoted to the understanding of their chemical bases. However, while the “basic” chemical part of the problem, namely the identity of the chemicals responsible for the different odor nuances, was satisfactorily solved years ago, there are some relevant questions precluding a clear understanding. These questions are related to the physicochemical interactions determining the effective volatilities of the odorants and, particularly, to the perceptual interactions between different odor molecules affecting in different ways to the final sensory outputs.

The utilization of non-Saccharomyces yeasts in the wine industry has increased significantly in recent years. Alternative species need commonly be employed in combination with Saccharomyces cerevisiae to avoid stuck fermentation, or microbial spoilage. The employment of more than one yeast starter can lead to interactions between different species with an impact on the outcome of wine fermentation. Previous studies[1] demonstrated that S. cerevisiae elicits transcriptional responses with both shared and species-specific features in co-culture with other yeast species.

Wine is one of the most representative components of Mediterranean diet. Moderate wine intake together with food, has been positively correlated with reduced risk of many chronic diseases. This beneficial effect seems to be ascribed to elevated polyphenolic content of wine [1]. Traditional approaches for the identification of wine biomarkers consumption include targeted metabolomics that focuses on the quantification of well-defined metabolites, losing a valuable information about a massive number of compounds. On the other hand, untargeted metabolomics can disclose a large quantity of signals corresponding to potential biomarkers in a single analysis with high sensitivity and resolution.