Insights into the stable isotope ratio variability of hybrid grape varieties

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.

he intensification of t vineyard practices led to an impoverishment of the biological diversity. In vineyard management, the reflection to reduce pesticides uses concerns mainly the soil management of the vineyard, and often focuses on flora management in the inter-row.

The need to rationalize agricultural inputs has recently increased interest in assessing vineyard variability in order to implement variable rate input applications, so-called ‘precision viticulture’. In many viticultural areas globally, precision viticulture is already widely used such as for selective harvesting and variable rate application (VRA) of inputs such as irrigation and/or fertilizer. Robust VRA relies on having a geostatistically accurate map (of one or more vineyard attributes) requiring high sampling densities, which can be cost- and time-prohibitive to obtain. Previous work on spatial interpolation using kriging have upscaled ground-based measurements, but such upscaling strategies are applicable only when vineyard conditions are spatially continuous and satisfies the assumption of second-order stationary processes. Alternatively, mixed models that combine kriging and auxiliary information, such as the regression kriging (RK) method, are more instructive for spatial predictions. In order to improve prediction accuracies, it is therefore necessary to incorporate additional information to achieve accurate spatial patterns with low error.

A Visual Information eNvironment for Effective agricultural management and Sustainability (VINES) is under development, which can provide significant competitive advantages to winegrowers by sustaining their appellation-specific grape and wine qualities and yields while measurably conserving water resources.

Throughout the growing season, grapevine frequently encounters environmental challenges associated with heat and light radiation stress, especially during the ripening stage, thereby constraining the yield and quality of berries. MYB24 has been previously proposed to control light responses during late fruit ripening stages, and it has been found to require the co-factor MYC2. We have generated transcriptomic data from grapevine leaves transiently co-transformed with MYB24 and MYC2. Differential expression analysis revealed 179 up-regulated genes (URGs). Considering tissue specificity, where MYB24 is specifically and highly expressed in flowers and late-ripening berries, the expression of these URGs was explored using a previously published Berry Development Atlas gathering berry development data of cv. ‘Pinot Noir’ and ‘Cabernet Sauvignon’ in different vintages.