Stomatal restrictions to photosynthesis in grapevine cultivars grown in a semiarid environment

Phenolic acids are phytochemicals that are expansively distributed in daily food intake. Phenolic acids are involved in various physiological activities, such as nutrient uptake, enzyme activity, protein synthesis, photosynthesis, and cytoskeleton structure in seeds, leaves, roots, and stems. Also exhibit antibacterial, antiviral, anticarcinogenic, anti-inflammatory, and vasodilatory activities due to their antioxidant property.

Context and purpose of the study ‐ Phytopathogenic diseases impact the development and yield of grapevines, resulting in economical, social and environmental losses.

The soil plays a pivotal role in the agroecological transition processes, due to its numerous implications in production support, water regulation, air and nutrient supply, and its function of reservoir for the major part of planet biodiversity. Therefore, soil quality and adequate soil management are key levers for an ecologically and economically sustainable viticulture. Gascogn’Innov (2017-2022) is an Operational Group funded by the European Innovation Partnership for Agriculture. As such, it gathered winegrowers from the south-west of France (Gascony), scientists, advisors and technicians, around a project focused on the biological functioning of viticultural soil and the design of better-adapted technical paths for soil protection.

Phenolic compounds are very important in crop plants and have been the subject of a large number of studies. Three main reasons can be cited for optimizing the level of phenolic compounds in crop plants: their physiological role in plants, their technological significance for food processing, and their nutritional characteristics1 Indeed, an enormous diversity of phenolic antioxidants is found in fruits and vegetables, and their presence and roles can be affected or modified by several pre- and postharvest cultural practices and/or food processing technologies (Ruiz-García et al. 2012, Goldman et al. 1999, Tudela et al. 2002). In winegrapes, the technological importance of phenolic compounds, mainly flavonoids, is well-known.

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).