Changes in flavonol profile are a reliable indicator to assess the exposure of red grape berries to solar radiation and canopy architecture

The application of remote and proximal sensing in viticulture have been demonstrated as a fast and efficient method to monitor vegetative and physiological parameters of grapevines. The collection of these parameters could be highly valuable to derive information on associated yield and quality traits in the vineyard. However, to leverage the informative potential of the sensing systems, a series of preliminary evaluations should be carried out to standardize working protocols for the specific features of a winegrowing area (e.g., pedoclimate, topography, cultivar, training system). This work aims at evaluating remote and proximal sensing systems for their performance and suitability to provide information on the vegetative, physiological, yield and qualitative aspects of vines and grapes as a function of different training systems in the Valpolicella wine region (Verona, Italy).

Climate change and harvest date decisions have led to the evolution of must quality over the last decades. Increases in must sugar concentrations are among the most obvious consequences, quantitatively. Saccharomyces cerevisiae is a robust and acid tolerant organism. These properties, its sugar to ethanol conversion rate and ethanol tolerance make it the ideal production organism for wine fermentations. Unfortunately, high sugar concentrations may affect S. cerevisiae and lead to growth inhibition or yeast lysis, and cause sluggish or stuck fermentations. Even sublethal conditions cause a hyperosmotic stress response in S. cerevisiae which leads to increased formation of fermentation by-products, including acetic acid, which may exceed legal limits in some wines.

A novel and efficient Dispersive Liquid-Liquid Microextraction (DLLME) method coupled with gas chromatography–mass spectrometry (GC–MS) was developed to determine 33 key aroma compounds (esters, alcohols, aldehydes, terpenes, norisoprenoids, fatty acids and phenols) present in Pinot noir (PN) wine. Four critical parameters including extraction solvent type, disperse solvent type, extraction solvent volume and disperse solvent volume were optimised with the aid of D-optimal design.

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Several trunk diseases cause decline and premature dieback of grapevines. In vineyards, these pathogens gain entry into plants through unprotected wounds. Wounds are also frequently infected during the propagation stages. The pathogens survive in infected plants in a latent form and cause disease in older grapevines or in plants that are