Long-term drought resilience of traditional red grapevine varieties from a semi-arid region

The gradual change in rainfall patterns experienced in the south of France vineyards, especially around the Mediterranean sea, means that the vines are increasingly subject to summer drought. The winegrowers developped the use of irrigation techniques to ensure the maintenance of competitive yields in the production of wines under Protected Geographical Indication label. In practice, drip irrigation pipes can be installed above the ground or buried into the soil as well as at different distances from the vine row. The objective of this study was to examine the profiles of the wet bulbs of the soil obtained from two drip irrigation systems : aerial drip located under the vine row and subsurface drip placed in the middle of the inter-row. This experiment took place over two consecutive seasons (2020-2021) on a 3.4 ha Viognier plot in the Mediterranean region (PGI Oc, France) on sandy clay soil. The annual rainfalls were less than 400 mm. Soil water content probes were installed at different depths (20 – 40 – 60 – 80 cm) and at different lateralities from the vine row (30 – 60 – 90 – 120 cm) to control the formation of the soil wet bulb during irrigation. The mapping and the analysis of the data allowed a better understanding and differentiation of the water percolation when irrigating with subsurface or aerial drip. For the same amount of water and without differences of vine water status, it is shown that in a subsurface drip irrigation situation, the size of the wet bulb formed is larger than in aerial drip irrigation system.

To evaluate the current and future impact of climate change on Viticulture requires an integrated view on a complex interacting system within the soil-plant-atmospheric continuum under continuous change. Aside of the globally observed increase in temperature in basically all viticulture regions for at least four decades, we observe several clear trends at the regional level in the ratio of precipitation to potential evapotranspiration. Additionally the recently published 6th assessment report of the IPCC (The physical science basis) shows case-dependent further expected shifts in climate patterns which will have substantial impacts on the way we will conduct viticulture in the decades to come.
Looking beyond climate developments, we observe rising temperatures in the upper soil layers which will have an impact on the distribution of microbial populations, the decay rate of organic matter or the storage capacity for carbon, thus affecting the emission of greenhouse gases (GHGs) and the viscosity of water in the soil-plant pathway, altering the transport of water. If the upper soil layers dry out faster due to less rainfall and/or increased evapotranspiration driven by higher temperatures, the spectral reflection properties of bare soil change and the transport of latent heat into the fruiting zone is increased putting a higher temperature load on the fruit. Interactions between micro-organisms in the rhizosphere and the grapevine root system are poorly understood but respond to environmental factors (such as increased soil temperatures) and the plant material (rootstock for instance), respectively the cultivation system (for example bio-organic versus conventional). This adds to an extremely complex system to manage in terms of increased resilience, adaptation to and even mitigation of climate change. Nevertheless, taken as a whole, effects on the individual expressions of wines with a given origin, seem highly likely to become more apparent.

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.

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.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.