Observed climatic trends in South African wine regions and potential implications for viticulture

Cette étude a pour but d’évaluer la modification de l’état hydrique (potentiel hydrique foliaire), le comportement productif (matière sèche et rendement) et la expression qualitative (poids de baie, degrée Brix, pH, acidité totale, concentration polyphénolique) de la varieté Tempranillo dans la Vallée du Douro, à l’A.O. Cigales, comme conséquence de l’application d’une irrigation modérée. Pour développer l’essai on a appliqué les suivantes

Drought caused by climate change has a dramatic incidence on the vineyard. Despite employing specific rootstocks tolerant to drought like 110 Richter, the vineyard continues to experience various losses, revealing the importance of the scion cultivar in the adaptation to drought stress. In this regard, Merlot, a widely cultivated grapevine, exhibited reduced drought tolerance compared to less cultivated varieties like Callet, a local cultivar originating from the Balearic Islands that demonstrated greater resilience to drought. Therefore, understanding the drought stress response in both cultivars and the cross-talk between scion and rootstock is key to unveiling possible differences that could affect to the adaptation to drought in vineyard.

Gum arabic is composed of a polysaccharide rich in galactose and arabinose along with a small protein fraction [1, 2], which gives its stabilizing power with respect to the coloring substances or tartaric precipitation of bottled wine. It is a gummy exudation from Acacia trees; the products used in enology have two possible botanical origins, i.e. Acacia seyal and Acacia senegal, with different chemical-physical features and consequently different technological effects on wines. The aim of this work is to evaluate the feasibility of discrimination of commercial gums Arabic between their two different sources, on the basis of the absorption of the Fourier Transform Infrared (FT-IR) spectra of their aqueous solutions, in order to propose an extremely rapid and cost-saving method for quality control laboratories.

Several Eurasian wild grapevine populations were found along Extremadura region (southwestern Spain). For conservation and study, one individual from four different populations (named L1, L2, L5 and L6) was vegetatively propagated and planted at Instituto de Investigaciones Agrarias Finca La Orden (CICYTEX), Badajoz. The aim of the present work was to characterize those conserved individuals from four different populations based on both an ampelographic description and a molecular analysis. Three vines per individual were studied.

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).