Climate effect on ripening process in Vitis vinifera, L. cv. Cencibel

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.

Harvesting grapes at adequate maturity is key to the production of high-quality red wines. Enologists and wine makers define several types of maturity, including technical maturity, phenolic maturity and aromatic maturity. Technical maturity and phenolic maturity are relatively well documented in the scientific literature, while articles on aromatic maturity are scarcer. This is surprising, because aromatic maturity is, without a doubt, the most important of the three in determining wine quality and typicity (including terroir expression). Optimal terroir expression can be obtained when the different types of maturity are reached at the same time, or within a short time frame. This is more likely to occur when the ripening takes place under mild temperatures, neither too cool, nor too hot. Aromatic expression in wine can be driven, from low to high maturity, by green, herbal, fresh fruit, ripe fruit, jammy fruit, candied fruit or cooked fruit aromas. Green and cooked fruit aromas are not desirable in red wines, while the levels of other aromatic compounds contribute to the typicity of the wine in relation to its origin. Wines produced in cool climates, or on cool soils in temperate climates, are likely to express herbal or fresh fruit aromas; while wines produced under warm climates, or on warm soils in temperate climates, may express ripe fruit, jammy fruit or candied fruit aromas. Growers can optimize terroir expression through their choice of grapevine variety. Early ripening varieties perform better in cool climates and late ripening varieties in warm climates. Additionally, maturity can be advanced or delayed by different canopy management practices or training systems.

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.

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).

The aim of this work was to analyze the phenology variability of Tempranillo and Chardonnay cultivars, related to the climatic characteristics in La Mancha Designation of Origin, and their potential changes under climate change scenarios. Phenological dates referred to budbreak, flowering, veraison and harvest were analyzed for the period 2000-2019. The weather conditions at daily time scale, recorded during the same period, were also evaluated. The thermal requirements to reach each of these phenological stages were calculated and expressed as the GDD accumulated from DOY=60. Changes in phenology were projected by 2050 and 2070 taking into account those values and the projected temperatures and precipitation, simulated under two Representative Concentration Pathway (RCP) scenarios –RCP4.5 and RCP8.5– using an ensemble of models. The average phenological dates during the period under study were, April 16th ± 6.6 days and April 5th ± 6.0 days for budbreak, May 31st ± 6.0 days and May 27th ± 5.3 days for flowering, July 26th ± 5.6 days and July 25th ± 5.8 days for veraison, and Ago 23rd ± 10.8 days and Ago 17th ± 9.0 days for harvest, respectively, for Tempranillo and Chardonnay. The projected changes in temperature imply an average change in the maximum growing season (April-August) temperatures of 1.2 and 1.9°C by 2050, and 1.6 and 2.6°C by 2070, under the RCP4.5 and RCP8.5 scenarios, respectively. A reduction in precipitation is predicted, which vary between 15% for 2050 under RCP4.5 scenario and up to 30% by 2070 under RCP8.5. The advance of the phenological dates for 2050, could be of 6, 7, 7, and 8 days for Tempranillo and 4, 6, 6 and 9 days for Chardonnay, respectively for budbreak, flowering, veraison and harvest under the RCP4.5 scenario. Under the RCP8.5 emission scenario, the advance could be up to 30% higher.