Freeze-thaw treatment to enhance phenolic ripening and tannin oxidation of seeds

Background: The Flavan-3-ol extraction from grape skin and seed during red-winemaking and their retention into wines depend on many factors, some of which are modified in the winemaking of blend wines. Recent research shows that Marselan, have grapes with high proportion of skins with high concentrations of flavanols, but produces red-wines with low proportion of skin derived flavanols, differently to the observed in Syrah or Tannat. But the factors explaining these differences are not yet understood.

Botrytis cinerea Pers., the causal agent of grey mould disease, is responsible for substantial economic losses, as it causes reduction of grape and wine quality and quantity. Exploitation of antagonistic yeasts is a promising strategy for controlling grey mould incidence and limiting the usage of synthetic fungicides. In our previous studies, 119 different indigenous yeasts were screened for putative multidimensional modes of action against filamentous fungus B. cinerea [1]. The most promissing biocontrol yeast was Pichia guilliermondii ZIM624, which exhibited several anatagonistic traits (production of cell wall degrading enzymes, chitinase and β-1,3-glucanase; demonstration of in vitro inhibitory effect on B. cinerea mycelia radial growth; production of antifungal volatiles, assimilation of a broad diversity of carbon sources, contributing to its competitivnes in inhabiting grapes in nature).

New and developing technologies, that provide sensors and the software systems for using and interpreting them, are becoming pervasive through our lives and society. From smart phones to cars to farm machinery, all contain a range of sensors that are monitored automatically with intelligent software, providing us with the information we need, when we need it. This technological revolution has the potential to monitor all aspects of vineyard activity, assisting growers to make the management choices they need to achieve the outcomes they want. For example, a future vineyard may possess automated imaging that generates a three dimensional model of the vine canopy, highlighting differences from the desired structure and how to use canopy management to improve fruit composition, or generates maps with yield estimates and measurements of berry composition throughout the growing season.

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).

Climate can greatly affect grape yield and quality (van Leeuwen et al., 2024). Growing suitable cultivars in a given region and or breed environmental resilient cultivars are essential for maintaining viticulture sustainability, particularly in the face of climate change (Wolkovich et al., 2018).