Comparison of ancestral and traditional methods in the elaboration of sparkling wines; preliminary results

The O2 uptake in the different winemaking processes is generally considered to be negative for the sensory characteristics of white and rosé wines. Wine racking is a critical point of O2 uptake, as the large surface area of the wine exposed during this operation and the inability to maintain an effective inert gas blanket over it.
The objective was to study O2 uptake during the racking of a model wine without using inert gases and to compare it with the purging of the destination tank with different inert gases.

The phenolic profile of a wine plays an essential role in its oxidative capacity and in both white and red wines it defines its shelf life[1]. The study of minority varieties to produce wines with peculiar characteristics necessarily includes the phenolic and oxidative characterization of the wines produced. This paper presents the study of wines made from 24 minority and majority white and red grape varieties, focusing on phenolic characteristics (total phenols, slightly polymerized phenols, highly polymerized phenols, anthocyanins…), color, as well as parameters related to the oxidability of the wines and their capacity to consume oxygen [2].

Grapevine (Vitis spp.) is greatly influenced by climatic conditions and its economic value is therefore directly linked to environmental factors. Among these factors, temperature plays a critical role in vine phenology and fruit composition. In such conditions, elucidating the mechanisms employed by the vine to cope with heat waves becomes urgent. For the past few years, our research team has been producing molecular and metabolic data to highlight the molecular players involved in the response of the vine and the fruit to high temperatures [1]. Some of these temperature-sensitive genes are currently undergoing characterization using transgenesis approaches coupled or not with genome editing, taking advantage of the Microvine genotype [2].

Controlling the development of the bacterial population during the winemaking process is essential for obtaining correct wines[1]. Carbonic Maceration (CM) wines are recognised as high-quality young wines. However, due to its particularities, CM winemaking implies a higher risk of bacterial growth: lower SO2 levels, enrichment of the must in nutrients, oxygen trapped between the clusters… Therefore, wines produced by CM have slightly higher volatile acidity values than those produced by the destemming/crushing method[2].

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).