Grape phylloxera meets drought: increased risk for vines under climate change?

‘Tempranillo Tinto’ is one of the most relevant grapevine cultivars worldwide. Despite its early ripening and relatively short vegetative cycle, which may not be ideal for high-quality grape and wine production in warming conditions, its long-standing cultivation has led to an intense multiplication by cuttings, which originated the high level of clonal variation currently available. Now, this intra-varietal diversity provides an interesting opportunity for cultivar improvement by identifying genotypes with better adaptation potential.

Precision nutrient management in viticulture can be addressed on the basis of a spatial characterization of within‐vineyard vine

The Casablanca Valley (CV) has a complex topography and is located near the Pacific Ocean. These factors generate important climatic differences in relation to other wine producing zones of Central Chile.

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).

L’appellation d’origine contrôlée “Côtes du Rhône” se caractérise par une très forte implantation du mouvement coopératif. Afin de mieux exploiter le potentiel qualitatif de leurs terroirs, plusieurs coopératives élaborent des “cuvées terroir”, résultat des sélections de vendanges provenant de différents secteurs.