Deciphering the function and regulation of VviEPFL9 paralogs to modulate stomatal density in grapevine through New Genomic Techniques

Rio grande do sul is the main grape producing state in Brazil, with the largest wine-growing area, responsible by 90% of the national production of wines and grape juices. Serra Gaúcha is the main vitivinicultural region, where around 15% of the area is destined to produce wines from vitis vinifera L. grapes. This region presents high rainfall during the grape maturation cycle, a factor that leads to great risk of attacks by fungal pathogens. the use of resistant varieties can reduce the cost and quantity of spraying, improving wine quality, focusing on a sustainable vitiviniculture.

s it is well known, myo and scyllo-inositol are two characteristic sugars of grape must and, for this reason, their quantification has been proposed to control the authenticity of the concentrated and rectificated grape must.

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).

Terroir zoning studies have to manage the heterogeneity and complexity of the landscape properties and processes. The varying geology is one of the main landscape properties conditioning the spatial variability of terroirs.

In recent years, wine consumption has been evolving towards new trends. On the one hand, awareness of health and responsible consumption has been growing, and with it, the demand for wines with lower or without alcohol content [1].