Temperature-based phenology modelling for the grapevine 

Many microbial starters for the alcoholic and malolactic fermentation processes are commercially available, indicated for diverse wine styles and quality goals. The screening protocols cover a wide range of oenologically relevant features, although some characteristics could also be studied using underexplored powerful techniques. In this study, we applied Fourier Transform Infrared (FTIR) microspectroscopy [1,2] to compare the cell wall biochemical composition and monitor the autolytic process in several wine strains of Saccharomyces cerevisiae.

Light-induced reactions can be responsible for detrimental changes of white and rosé wines. This is associated to the photo-degradation of riboflavin (RF) and of methionine (Met) causing the appearance of light-struck taste (LST).

Le but de notre travail a été d’étudier l’influence de différents systèmes de la gestion du sol en viticulture sur des paramètres biologiques de sol comme indicateurs de la protection et de la qualité du sol. La conservation de sol est indispensable pour une viticulture durable et la protection du terroir. Nos résultats ont montré, que la matière

Context and purpose of the study. Conventional viticulture relies heavily on synthetic inputs (fertilizers, pesticides), as well as mechanization to manage pests, weeds, and diseases and maximize yields.

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.