Fast, and full microbiological wine analysis using triple cellular staining.

Full understanding of grapevine responses to variable soil resources requires assessing the grapevine root system. Grapevine root systems are expansive and examining deep roots (i.e., >40 cm) is particularly important in conditions where grapevines increase reliance on deep soil resources, such as drought or plant competition. Traditional methods of assessing roots rely on morphological traits associated specific functions (e.g., root color, diameter, length), while recent methodological advances allow for estimating root function more directly (e.g., omics). Yet, the potential of applying refined methods remains underexplored for roots at deep depths.

This paper presents the results of an agroclimatic study of the viticulture area called DOC Monreale (Pa), Italy, which was carried out with the aim to supply a working instrument supporting viticulture planning.

Context and Purpose. Management of plant-parasitic nematodes in perennial cropping systems such as wines grapes is challenging.

Recognizing the influence of alcohol preference on health behaviors is essential for developing tailored interventions that effectively promote healthier lifestyles and optimize disease management strategies in the vulnerable population of patients with cardiometabolic diseases (CMD). The present study aims to provide valuable insights into how alcohol preference relates to dietary habits and medication adherence among patients with CMD diseases.

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).