Methodological approach to zoning

Over the last decades, climate change and rising temperatures have impacted the wine industry. Wines from warm regions tend to have a higher pH and lower total acidity.

Wine acidity is a parameter of great importance that influences different quality factors of the product such as biological stability or organoleptic characteristics. In the current context of climate change, which gives rise to wines with higher levels of ethanol and lower acidity, the biological acidification with yeast species such as Lachancea thermotolerans could be a solution.
In this work, the effect of the inoculation of different L. thermotolerans on the acidity of wine was studied.

Les fromages d’Appellation d’Origine Contrôlée (AOC) représentent un enjeu économique important pour la filière laitière (11 % des fromages produits en France sont des fromages d’AOC, et dans certaines régions de montagne, cette proportion dépasse 50 %). Les spécificités de ces fromages et leurs liaisons avec les caractéristiques du terroir constituent un système complexe où interagissent en particulier la technologie fromagère et les caractéristiques des laits (composition chimique en particulier). Ces dernières dépendent elles-mêmes des caractéristiques des animaux (origine génétique, facteurs physiologiques, état sanitaire) et de leur mode de conduite (alimentation, hygiène, traite…) (fig. 1). L’influence de ces facteurs de production (alimentation et type d’animal en particulier) sur les caractéristiques des fromages est fréquemment mise en avant par les fromagers, sur la base d’observations empiriques. Il existe cependant très peu de travaux expérimentaux sur le sujet, en raison, entre autres, de la difficulté de séparer correctement les effets propres de ces facteurs d’amont de ceux liés à la technologie fromagère.

Grapevine rootstocks provide protection against environmental biotic and abiotic stresses. Nitrogen (N) and iron (Fe) are growth-limiting factors in many crop plants due to their effects on the chlorophyll and photosynthetic characteristics. Iron nutrition of plants can be significantly affected by different nitrogen forms through altering the uptake ratio of cations and anions, and changing rhizosphere pH. The aim of this study was to investigate the response mechanisms of grapevine rootstocks due to the interaction between different nitrogen forms and iron uptake.

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).