La zonazione della valle d’Illasi (Verona)

The article analyzes current developments in European pesticide regulation.

Application of municipal solid waste (MSW)-compost as a mulching material in vineyards supports sustainable practices and aligns with both circular economy and zero-waste principles.

Aim: Many processes or reactions that occur in plants involved isotopic discrimination. Water availability, for example, affects the isotopic ratio of carbon (δ13C) and oxygen (δ18O). In viticulture, δ13C is used in experiments related to water relations and irrigation in vineyards. δ18O is used much less but it could be a good complement to δ13C. The aim of this study was to generate knowledge on how these isotopic ratios, measured in musts, could help to better understand the water behavior of grape varieties. 

Aerial thermography has emerged as a promising tool for water stress detection in grapevines, but there are still challenges associated with this technology, particularly concerning the methodology employed to extract reliable canopy temperature values. This consideration is relevant especially in vertically trained vineyards, due to the presence of multiple surfaces which are captured by drone thermal cameras with high-resolution. To test the technology and the data analysis required, a field study was conducted during the 2022-2023 season in a model vineyard with multiple scions-rootstock combinations trained on a vertical shoot-positioning (VSP) system. Additionally, three irrigation regimes were implemented to introduce variability in water stress levels.

Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can consistently stimulate (MLF+ phenotype) or inhibit (MLF- phenotype) malolactic bacteria and the MLF process as a function of numerous winemaking practices, but the molecular evidence behind still remains a mystery. In this study, such evidence was elucidated by the direct comparison of extracellular metabolic profiles of MLF+ and MLF- yeast phenotypes. Untargeted metabolomics combining ultrahigh-resolution FT-ICR-MS analysis, powerful machine learning methods and a comprehensive wine metabolite database, discovered around 800 putative biomarkers and 2500 unknown masses involved in phenotypic distinction.