Development and validation of a free solvent UHPLC/MS-MS method to analyse melatonin and its precursors in Spanish commercial wines  

Several studies have tried to develop different methods to study the photodegradation of wine in an accelerated way, trying to elucidate the effect of light on the wine compounds[1]. In a previous study, our team developed a chamber that speeds up the photodegradation of rosé wine[2]. In the present work we have tried to establish a correlation between irradiation times in accelerated conditions and the natural exposure to the cycles of light that usually exist in markets or at home.

Over the last years, due to climate change, several red wines, such as the Sangiovese wines, have been often subjected to loss of clarity due to the formation of deposits of fine needle-shaped crystals. This phenomenon turned out to be due to an excess of quercetin (Q) and its glycosides (Q-Gs) in wines. These compounds are synthesized to a large extent when grapes are excessively exposed to UVB radiations in vineyards[1]. Unfortunately, it is not easy to predict the degree of Q precipitation because its solubility strongly depends on the wine and matrix composition[2].

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.

Grapevine cultivars are vegetatively propagated to preserve their varietal characteristics. However, spontaneous somatic variations that occur and are maintained during cycles of vegetative growth offer opportunities for the natural improvement of traditional grape cultivars. One advantageous trait for winegrowing is reduced bunch compactness, which decreases the susceptibility to pests and fungal diseases and favor an even berry ripening.

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).