Characterization of a Sémillon clonal population: exploring genetic diversity, metabolomic profiles, and phenotypic variations

The production of most red wines that are sold involves an alcoholic fermentation carried out by yeasts of the Saccharomyces genus, and a subsequent fermentation carried out by lactic bacteria of the Oenococus oeni species after the first one is fully completed. However, the traditional process can face complications, which can be more likely in grape juices with high levels of sugar and pH. Because of climate change, these situations are more frequent in the wine industry. The main hazards in those scenarios are halts or delays in the alcoholic fermentation or the growth of unwanted bacteria while the alcoholic fermentation is not done yet and the wine still has residual sugars.

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].

Chile is considered vulnerable to climate change; and these phenomena affect several mechanisms in the grape physiology and quality. The global temperature increase affects sugar contents, organic acids, and phenolic compounds in grapes, producing an imbalance maturity. In this sense, an alternative to reduce the impact is to perform pruning after vine budburst, known as “Late Pruning” (LP).

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).

The fungicidal effect of UV-C radiation (100-280 nm wavelength) is well known, but its applicability for the control of pathogenic molds of grapes is conditioned by its effect on the host and by the risks inherent in its handling[1].
As an alternative, the effect in vitro of UV-B radiation (280-315 nm) on the main pathogenic molds of grapes has been studied: Botrytis cinerea, Aspergillus niger, Penicillium expansum and Rhizopus stolonifer.