Étude intégrée et allégée des terroirs viticoles en Anjou: caractérisation et zonage de l’unité terroir de base, en relation avec une enquête parcellaire

Copper (Cu) is widely and historically used in viticulture as a fungicide against mildew. Cu has a strong affinity for soil organic matter and accumulates in topsoil horizons. Thus, Cu may negatively affect soil organisms and plants, consequently reducing soil fertility and productivity. The Bordeaux vineyards have the largest vineyard surfaces (26%) within French controlled appellation and a great proportion of French wine production (around 5 million hl per year). Considering the local context of vineyard surfaces decreasing (vine uprooting) and possible new crop plantation, the issue of Cu potential toxicity rises. Therefore, the aims of this work are firstly to evaluate the Cu contamination in vineyard soils of Bordeaux, secondly to produce a risk assessment map for new vine or crop plantation. We used soil analyses from several local studies to build a database with 4496 soil horizon samples. The database was enhanced by means of pedotransfer functions in order to estimate the bioaccessible (EDTA-extractable) Cu in soils of samples without measurements. From this database, 1797 georeferenced samples with CuEDTA concentrations in the topsoil (0-50 cm depth) were used for kriging interpolation in order to produce the spatial distribution map of CuEDTA in vineyard soils. Then, the spatial distribution of Cu was crossed with vine uprooting surfaces and municipality boundaries. CuEDTAconcentrations ranged from 0.52 to 459 mg/kg and showed clear anomalies. Our results from spatial analysis showed that almost 50% of vineyard soil surfaces have CuEDTA concentrations higher than 30 mg/kg (moderate risk for new plantation) and 20% with concentrations higher than 50 mg/kg (high risk for new plantation). A decision-support map based on municipalities was realised to provide a simple tool to stakeholders concerned by land use management.

In many regions, climate change leads to an increase in air temperature combined with a reduction of rainfall, intensifying climatic demand and water deficits (WD) (Cardell et al. 2019), which in turn may negatively impact grapevine development, yield and grape composition (Santos et al. 2020). In addition, climate change may also increase disease pressure, leading to further yield and quality losses, besides increasing costs due to increased vineyard spraying (Santos et al. 2020) and reducing viticulture acceptability by consumers (Guichard et al. 2017). Adopting new resistant varieties appears as a promising long-term solution to better manage vine protection, but unfortunately little is known regarding their behavior in front of WD.

AIM Current winery efforts in Spanish warm climate regions, as Andalusia, are aimed at red wine production in spite of sub-optimal climatological conditions

Nitrogen (N) uptake by grapevine roots in forms like nitrate, ammonium, urea, or amino acids influences vegetative and generative growth, impacting grape quality and wine sensory profile. The study examined nitrogen’s influence on phenolic compounds in leaves, berries, and wine across different scales — hydroponics, soil culture, and vineyard trials. Nitrogen forms altered metabolite patterns in leaves and wine significantly, affecting aroma and flavor. Key nitrogen assimilation enzymes (NR, NiR, GS) in grapevine rootstocks responded to nitrogen forms and timing. Hydroponically grown rootstocks fertilized with various forms showed differences in enzyme expression and activity, suggesting rootstocks can assimilate amino acid glutamine (Gln).

By dissecting the root system architecture (RSA) into its underpinning components (e.g. root emission, axial growth, radial growth, branching, root direction or tropism) and identifying the relationships between them, functional-structural 3D root models are promising tools for analyzing the diversity and complexity of root system phenotypes with Genotype × Environment interactions. The model parameters are assumed to be synthetic traits, less influenced by the environment, and consequently with less polygenic architectures than the integrative RSA traits they drive. Root models can serve as a basis for in silico development of root system ideotypes by highlighting the developmental processes and parameters that most likely influence RSA fitness.