Amphora Wines: To Pitch Or Not To Pitch

While most brands belong to individual enterprises, some brands belong to groups of enterprises based in a single territory. This conceptual paper examines the characteristics

Inter-row soil tillage in vineyards, stimulates vigor and production due to the absence of competition for water and nutrients, however negatively affects organic matter content, soil erosion, and compaction, resulting in reduced fertility. In this study, we investigated the effects of different cover crop management approaches, including cultivation type and termination timing, on the physiological and productive responses of a Glera vineyard.
The experimental trial was conducted in Precenicco (UD) from 2019 to 2021. A commercial mixture for autumn cover cropping was sown in alternating rows, and the sowing pattern was changed each year.

La région viticole de San Juan (Argentine) est marquée par des températures très élevées et des variations diurnes faibles. La valorisation de la connaissance de cet environnement et de ses interactions avec le fonctionnement de la vigne et le lien au vin passent par l’étude de ses terroirs et de leur caractérisation. Le point de départ de ce travail est l’étude des zones mésoclimatiques aptes à la culture de la vigne de la Province de San Juan et à la caractérisation des sols de cette même région. L’objectif est de définir le potentiel vitivinicole des zones considérées.

Dans le zonage viticole mis en place dans la province de Taranto, on a introduit la méthode du bilan hydrique pour évaluer les réserves hydriques dans les 8 zones déterminées

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.