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

The wooden barrel is a key factor in enology, since wine chemical composition and sensory properties changes significantly in contact with the barrel[1]. Today’s highly competitive market constantly demands new differentiated products and wineries search innovations continuously.
Wood selection is crucial: barrels stability to keep constant their contribution and the result on products, and additional and differentiated wood contributions to impact their new products. Oak wood selection has traditionally been carried out using parameters such as specie, location and grain, however, it goes one step further nowadays. Large cooperage work with non-destructive techniques that allow classifying oak wood quickly and easily according to their organoleptic contribution[2].

Condensed grape tannins play a major role in the organoleptic properties and quality of red wine. Recently, a new sub-family of macrocyclic condensed tannins has been identified in red wine and named “crown tannins”. Indeed, the first compound of the family identified and characterised by NMR was the crown procyanidin tetramer which is composed of a macrocyclic structure composed of four (-)-epicatechins link together by B-type interflavanoid linkage in the following an alternative sequences of C4-C8 and C4-C6 linkage. The 3D structure of this unusual crown procyanidin family reveals a central cavity in the molecule [1].

Red grape pomace can be an important source of polysaccharides, but currently they are little studied and even less with viable and environmental extraction processes (green extraction). These green techniques must be able to break the cell wall so that the compounds contained in the cells, including polysaccharides, are released and can have a great influence on extraction yields, the chemical structure of polysaccharides and applications in wines. Amongst the emerging green techniques most applied to the extraction of bioactive compounds, such as polysaccharides, high-power ultrasound (US) and enzyme-assisted extraction stand out.

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 presence of acetic acid bacteria in wine can lead to the appearance of acetic acid at concentrations above the perception threshold, causing the wine rejection by the consumer. During the winemaking process, avoiding the presence of acetic acid bacteria is very difficult, as there is always a residual population accompanying the wine[1], and the problem arises with the significant development of these microorganisms that metabolizes large amounts of acetic acid.
The concern of wineries to control the presence of acetic acid bacteria in wines during their conservation is due to the absence of simple and effective analyses that allow the detection of these microorganisms in the initial stages.