Soil management of interrow spacing as an important factor to protect the vineyard soils from runoff and erosion under the Mediterranean climate

Quercetin (Q), a phenolic compound released from grape skins during red wine maceration, has been identified as a source of instability in bottled wines, particularly Sangiovese, due to crystallisation. This phenomenon represents an economic challenge for producers and affects wine clarity and consumer perception.

For coopers, toasting process is considered as a crucial step in barrel production where oak wood develops several specific aromatic nuances released to the wine during its maturation

L’utilisation de levures sélectionnées est généralement considérée comme le moyen d’éviter les problèmes fermentaires. Néanmoins de nombreux viticulteurs pensent que ces levures sont à l’origine d’une standardisation des vins et militent pour le respect d’une flore indigène (Bourguignon, 1992).

Plus de la moitié du vignoble suisse (14’000 ha) est situé sur des coteaux en forte pente (> 30%). Dans certains vignobles, la pente naturelle du terrain a été réduite par la construction de terrasses soutenues par des murs.

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).