Testing the pathogen e-learning and field training course on grapevine virus knowledge and management

Yeast assimilable nitrogen (YAN) in the grape must is a key variable for wine quality as a source of aroma precursors. In a situation of YAN deficiency, a foliar urea application upon the vine at veraison enhances YAN concentration and facilitates must fermentation. In 2013, Agroscope investigated the impact of leaf-fruit ratio on the nitrogen (N) assimilation and partitioning in grapevine Vitis vinifera cv. Chasselas following foliar-urea application with the aim of improving its efficiency on the YAN concentration.

Temperature is a relevant parameter during vineyard development, affecting vine phenology and grape maturity. Moreover, the climate of the different Chilean valleys influences the varieties cultivated, the ripening period and the final quality of the wines. The use of growing degree days (GDD) is known worldwide for the study of climate in viticulture regions. However, little is known about the evolution of maturity and the sugar loading stop, based on this parameter.

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).

The Columbia Valley American Viticultural Area (AVA) of the Pacific Northwest, USA is the world’s largest officially recognized viticultural area with basalt bedrock.

Aim: The aim of this study was to investigate the impact of topsoil thickness on dormant pruning weights, cluster compactness, and fruit composition (°Brix, titratable acidity, pH) in the Mid-Atlantic of the United States.