Phenolic acid characterization in new varieties descended from Monastrell.

AIM: Stalks are empirically known to bring many benefits to the wine such as alcoholic reduction, color protection or improvement of the tannic intensity. Not much used on Swiss grape varieties, the aim of this study was to identify the relevance of using this type of winemaking in the case of Gamay and Gamaret red grape varieties.

The increasing demand for healthier, more transparent, and sustainable wine products has prompted the need for innovative solutions to optimize the wine health value chain.

Since the approval in 2019 of the use of high-power ultrasound (US) in winemaking to support extractive processes from grape to must, the study of this technology in red winemaking has increased significantly, with laboratory and semi-industrial scale studies.

The need to rationalize agricultural inputs has recently increased interest in assessing vineyard variability in order to implement variable rate input applications, so-called ‘precision viticulture’. In many viticultural areas globally, precision viticulture is already widely used such as for selective harvesting and variable rate application (VRA) of inputs such as irrigation and/or fertilizer. Robust VRA relies on having a geostatistically accurate map (of one or more vineyard attributes) requiring high sampling densities, which can be cost- and time-prohibitive to obtain. Previous work on spatial interpolation using kriging have upscaled ground-based measurements, but such upscaling strategies are applicable only when vineyard conditions are spatially continuous and satisfies the assumption of second-order stationary processes. Alternatively, mixed models that combine kriging and auxiliary information, such as the regression kriging (RK) method, are more instructive for spatial predictions. In order to improve prediction accuracies, it is therefore necessary to incorporate additional information to achieve accurate spatial patterns with low error.

The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.