Evaluation of the effects of pruning methodology on the development of young vines 

Melatonin is a bioactive compound with antioxidant properties, that has been found in many fermented beverages, such as beer and wine [1]. Indeed, it has been shown that yeast can synthesize melatonin during alcoholic fermentation, although its role inside the cell, as well as the metabolic pathway involved in its synthesis, is still unclear [1]. Recent studies showed that during fermentation, melatonin interacts with different proteins of the glycolytic pathway in both Saccharomyces and non-Saccharomyces yeast, for instance glyceraldehyde 3-phosphate dehydrogenase, pyruvate kinase or enolase [2].

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.

Grapevine rootstocks provide protection against environmental biotic and abiotic stresses. Nitrogen (N) and iron (Fe) are growth-limiting factors in many crop plants due to their effects on the chlorophyll and photosynthetic characteristics. Iron nutrition of plants can be significantly affected by different nitrogen forms through altering the uptake ratio of cations and anions, and changing rhizosphere pH. The aim of this study was to investigate the response mechanisms of grapevine rootstocks due to the interaction between different nitrogen forms and iron uptake.

The wine industry produces an enormous amount of waste every year. A wider inclusion of disregarded by-products in the human diet or its use as a source of bioactive compounds is a good strategy for reducing waste. It will not only introduce an added value to a waste product but also come upon the European Union and United Nations’ demands towards more sustainable agricultural approaches and circular economy.

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).