Characterization of the adaptive mechanisms of grapevine rootstocks to iron deficiency induced by lime stress

The interest in understanding the water balance of terrestrial plants under drought has led to the creation of the isohydric/anisohydric terminology. The classification was related to an implication-driven framework, where isohydric plants maintain a constant and high leaf water potential through an early and intense closure of their stomata, hence risking carbon starvation. In contrast, anisohydric plants drop their leaf water potential to low values as soil drought is establishing due to insensitive stomata and thus risk mortality through hydraulic failure, albeit maximizing carbon intake. When applied to grapevines, this framework has been elusive, yielding discrepancies in the classification of different wine grape varieties around the world.

The search for underground shelters is one of the oldest forms of human habitation, providing refuge in extreme environments such as deserts and polar regions.

Terpenes are responsible for flavors and aromas of grapes, however, they also protect from radiation, participate in biotic stress and antioxidant mechanisms. The phytohormone methyl jasmonate (MeJA) mediates many of these stress responses and has been associated with increased terpene content in berries. Here, we generated transcriptomic data of Vitis vinifera cv. ‘Gamay’ cells treated with MeJA (100 μM) and cyclodextrins (50 μM) to understand these responses. Ontology analysis revealed that up-regulated genes (URGs) were enriched in jasmonic acid biosynthesis and signaling terms, as expected. Inspection of transcription factors (TFs) among URGs allowed us to study uncharacterized TFs.

La conoscenza dell’interazione genotipo x ambiente e pertanto della caratterizzazione territoriale è di prioritaria importanza nella valutazione dei siti. Grazie alla combinazione di dati GIS

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).