Soil functional characteristics for qualitative Sangiovese wine production in Tuscany (Italy)

Under standard champagne tasting conditions, the complex interplay between the level of dissolved CO2 found in champagne, its temperature, the glass shape, and the bubbling rate, definitely impacts champagne tasting by modifying the neuro-physico-chemical mechanisms responsible for aroma release and flavor perception. Based on theoretical principles combining heterogeneous bubble nucleation, ascending bubble dynamics and mass transfer equations, a global model is proposed (depending on various parameters of both the wine and the glass itself), which quantitatively provides the progressive losses of dissolved CO2 from laser-etched champagne glasses.

Monferace project is born from an idea of 12 winegrowers willing to create a new “old style” Grignolino wine and inspired byancient winemaking techniques of this variety (1). Monferace wine is produced with 100% Grignolino grapes after 40 months of ageing, of which 24 in wooden barrels of different volumes. Grignolino is an autochthonous Italian variety cultivated in Piedmont (north-west Italy), recently indicated as a “nephew” of the famous Nebbiolo (2) and is used to produce three different DOC wines. The Monferace Grignolino is cultivated in the geographical area identified in the Aleramic Monferrato, defined by the Po and Tanaro rivers, in the heart of Piedmont and the produced wine is characterized by a high content of tannins, marked when young, that evolve over the years. Its color is generally slight ruby red and garnet red with orange highlights with ageing.

Dada la importancia de los suelos y de los substratos geológicos en la zonificación vitivinícola, los autores realizan una revisión de estudios sobre las formaciones más importantes en la D.O. Jerez-Xérès-Sherry y Manzanilla-Sanlúcar de Barrameda.

Changes in the low molecular weight phenolic fraction, obtained by liquid-liquid microextraction technique, were studied after controlled oxidation of two typologies of Sangiovese wines (Brunello di Montalcino and Chianti Classico) belonging to two vintages (2017 and 2018). The fractions were characterized by LC-MS and quantified by HPLC. The most abundant extracted compounds were the phenolic acids. The effect of oxidation, vintage, and wine typology was stated by a three-ways ANOVA. Gallic and syringic acids significantly increased after oxidation while (–)-epicatechin decreased the most.

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.