The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.

The nitrogen composition of the grapes directly affects the developments of alcoholic fermentation and influences the final aromatic composition of the wines. The aim of this study was to determine the effect and efficiency of foliar applications of urea on the nitrogen composition of grapes. This study was carried out during 2023 vintage and in the Chenin vineyard located in Estacion Experimental Mendoza (Argentina). Three urea concentrations 3, 6 and 9 Kg N/ha (C1, C2, and C3, respectively) and control (T) were applied in this vineyard at veraison. In all solutions were added 1ml/l of Tween 80 ® surfactant.

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.

Xinomavro is a red grape variety from Northern Greece (Protected Designation of Origin), known for the nice acidities, perfectly appropriate for sparkling wine production (Rosé and Blanc de Noir). The elabo- ration of sparkling wine requires technical as well as scientific skills. Although the impact of the yeast strains and their metabolites on the final product quality is well documented, the action of bacteria still remains unknown.
The present work focuses (i) on the population diversity of lactic acid bacteria isolated from sparkling wines and (ii) on the technological effect of the species during sparkling wine elaboration.

Today, a variety of remote sensing tools are used to characterise plant performance. However, the vine is rarely studied, as a major crop specificity is canopy discontinuity. Registered images of the vineyard are anisotropic, therefore difficult to analyse.