Terroir in Slovak viticulture area

Le climat a de fortes implications sur le bon fonctionnement physiologique de la vigne et a besoin d’être quantifié afin de déterminer l’aptitude des régions à la culture de la vigne. Une méthode, qui pourrait éventuellement servir à prévoir l’aptitude des régions à la culture de la vigne, est proposée.

Nutrient availability – nitrogen, lipids, vitamins or oxygen – has a major impact on the kinetics of winemaking fermentations. Nitrogen is usually the growth-limiting nutrient and its availability determines the fermentation rate, and therefore the fermentation duration. In some cases, in particular in Champagne, grape musts have high nitrogen concentrations and are sometimes clarified with turbidity below 50 NTU. In these conditions, lipid deficiencies may occur and longer fermentations can be observed. To better understand this situation, a study was realized using a synthetic medium simulating the composition of a Champagne must : 180 g/L of sugar, 360 mg/L of assimilable nitrogen and a lipid content ranging from 1 to 8 mg/L of phytosterols (mainly β-sitosterol).

Top quality sparkling wines (SW) are mostly produced using the traditional method that implies a second fermentation into the bottle[1]. That is the case of sparkling wines of reputed AOC such as Champagne, Cava or Franciacorta. However, it seems that the first SW was elaborated using the ancestral method in which only one fermentation takes place[2]. That is the case of the classical SW from the AOC Blanquette de Limoux[3]. In both cases, SW age in the bottle during some time in contact with lees favoring yeast’s autolysis[4]. There is a lot of information about traditional method but only few exists about ancestral method. The aim of this work was to compare SW made by the ancestral method with SW made by the traditional method.

A work involving the finding, the description and the recovery of old grapevine varieties from the north and north east of Spain was begun in the CSIC in the year 1987.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).