Response to powdery and downy mildew of varieties with disease resistance genes (PIWI)

Acidity is often touted as a predictor of wine ageability, though surprisingly few studies have systematically investigated the chemical basis for this claim.

Must oxidation is a complex process involving multiple enzymatic transformations, including the oxidation of phenolics containing an ortho-diphenol function. The latter process has a primary influence on wine aroma characteristics and stability, due to the central role of ortho-diphenols in the non-enzymatic oxidative reactions taking place during winemaking and in finished wine. Although oxidation of must is traditionally avoided, in recent years its contribution to wine quality has been revisited, and in some cases improvements to wine aroma have been observed with the application of controlled must oxidation. Nowadays there is a great interest in the wine industry towards the identification of specific markers or patterns to characterize and classify the response of grape must to oxidation.

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.

Aroma fraction of musts from grapes ‘Pedro Ximenez’ traditionally sun-dried and chamber-dried at 40 ºC and at 50 ºC during 8, 5 and 4 days respectively, destined for the production of sweet wines in Montilla-Moriles region (southern Spain) was studied.

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.