Cumulative effects of repeated drought stress on berry composition, and phenolic profile: Field experiment insights

The increasing frequency of heat waves during grape ripening presents challenges for the production of high-quality wine grapes. This underscores the significance of developing effective irrigation and canopy management techniques to optimize both yield and grape quality.
A field experiment was carried out during 2021 and 2022 using Manto negro wine grapes to study the effect of two irrigation strategies and different light exposure levels on grape quality. In a four-block experimental vineyard at Bodega Ribas in Mallorca, two irrigation treatments—moderate and severe deficit irrigation—were implemented. Within each irrigation plot, three light exposure treatments were randomly assigned, encompassing exposed clusters from pea size, non-exposed clusters, and shaded clusters after softening.

The ISOPlexis – Center for Sustainable Agriculture and Food Technology, University of Madeira, is a research unit that develops activities in the fields of Sustainable Agriculture, Agri-food Technology and Bioeconomy, with focus on agrodiversity monitoring and phenotyping,

[English version below]

L’objectif de l’étude est de mettre en évidence les différences rencontrées entre les vins Barbera d’Asti, qui sont produits en AOC. Celles-ci sont imputées aux terroirs caractérisés selon les facteurs pédologiques, climatiques, et qui conduisent à des différents potentiels viticoles et œnologiques. Il est proposé une individualisation des sous-zones.

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).

In Mediterranean rainfed vineyards, cover cropping and dry mulching are increasingly implemented to improve soil structure, microclimate, and vine resilience, yet their effects on grapevine-associated microbiomes remain only partially understood.