Natural variability and vine-growers behaviour

The objective of the work described here is the elaboration of a map of the different types of vineyard soils that to guide the famers in the choice of the most productive vine rootstocks and varieties. 90 vineyard soils profiles were analysed in the entire territory of the Origen Denominations of Valdepeñas. The sampling was carried out in 2018 (June to October) by making a sampling grid, followed by photointerpretation and control in the field. The studied soils can be grouped into 9 different soil types (according to FAO 2006 classification): Leptosols, Regosols, Fluvisols, Gleysols, Cambisols, Calcisols, Luvisols and Anthrosols. A map showing the soil distribution with different type of soils has been made with the ArcGIS program. Regarding to the choice of rootstock, Calcisoles are soils with a high active limestone content, so the rootstocks used in these soils must be resistant to this parameter; Luvisols are deep soils with high clay content, so they will support vigorous rootstocks. Because the cartographic units are composed of two or more subgroups, with are associated in variable proportions, 9 different soil associations have been established; Unit 1: Leptosols, Cambisols and Luvisols (80%, 15% and 5% respectively); Unit 2: Cambisols with Regosols and Luvisols (40%, 30% and 30% respectively); Unit 3: Cambisols and Gleysols with Regosols (40%, 40% and 20% respectively); Unit 4: Regosols with Cambisols, Leptosols and Calcisols (40%, 30%, 15% and 15% respectively); Unit 5: Cambisols, Leptosols, Calcisols and Regosols (25% each of them); Unit 6: Luvisols with Cambisol and Calcisols (80%, 10% and 10% respectively); Unit 7: Luvisols and Calcisols with Cambisols (40%, 40% and 20% respectively); Unit 8: Calcisols with, Cambisols and Luvisols (80%, 10% and 10% respectively); Unit 9: Anthrosols. These study allow to elaborate the first map of vineyard soils of this Protected Designation of Origin in Castilla-La Mancha.

Current climate change is increasing inter- and intra-annual variability in atmospheric conditions leading to grapevine phenological shifts as well altered grape ripening and composition at ripeness. This study aims to (i) detect weather anomalies within a long-term time series, (ii) model grape ripening revealing altered traits in time to target specific ripeness thresholds for four Vitis vinifera cultivars, and (iii) establish empirical relationships between ripening and weather anomalies with forecasting purposes. The Day of the Year (DOY) to reach specific grape ripeness targets was determined from time series of sugar concentrations, total acidity and pH collected from a private company in the period 2009-2021 in North-Eastern Italy. Non-linear models for the DOY to reach the specified ripeness thresholds were assessed for model efficiency (EF) and error of prediction (RMSE) in four grapevine cultivars (Merlot, Cabernet Sauvignon, Glera and Garganega). For each vintage and cultivar, advances or delays in DOY to target specified ripeness thresholds were assessed with respect to the average ripening dynamics. Long-term meteorological series monitored at ground weather station by means of hourly air temperature and rainfall data were analyzed. Climate statistics were obtained and for each time period (month, bimester, quarter and year) weather anomalies were identified. A linear regression analysis was performed to assess a possible correlation that may exist between ripening and weather anomalies. For each cultivar, ripeness advances or delays expressed in number of days to target the specific ripening threshold were assessed in relation to registered weather anomalies and the specific reference time period in the vintage. Precipitation of the warmest month and spring quarter are key to understanding the effect of climate change on sugar ripeness. Minimum temperatures of May-June bimester and maximum temperatures of spring quarter best correlate with altered total acidity evolution and pH increment during the ripening process, respectively.

Under-vine (UV) management has traditionally consisted of synthetic herbicide use to limit competition between weeds and grapevines. With growing global interest towards non-synthetic chemical use, this study aimed to capture the effects of alternative UV management at two commercial Shiraz vineyards in South Australia, where the sole management variables were UV management since 2016. In adjacent treatment blocks, cultivation (CU) was compared to spontaneous vegetation (SV) in McLaren Vale (MV), and herbicide was compared to SV in Eden Valley (EV). Soil water infiltration rates were slower and grapevine stem water potential was lower in CU compared to SV in MV, with the latter having a plant community dominated by soursob (Oxalis pes-caprae) during winter; while in EV, there was little separation between the treatments. Yields were affected at both sites, with SV being higher in MV and HE being higher in EV. In MV, the only effect on grape must was a lower 13C:12C isotope ratio in CU, indicating greater grapevine water stress. In the grape must at EV, SV had higher total soluble solids, total phenolics, anthocyanins, and yeast available nitrogen; and lower pH and titratable acidity. Pruning weights were not affected by the treatments in MV, while they were higher in HE at EV. Assessments revealed that the differing soil types at the two sites were likely the main determinants of the opposing production outcomes associated with UV management. In the silty loam soil of MV, the higher yields in SV were likely due to more plant-available water, as a potential result of the continuous soil bio-pores formed by winter UV vegetation. Conversely, in the loamy sand soils of EV with a lower cation exchange capacity, the lower yields and pruning weights in SV suggest the UV vegetation competed significantly with the grapevines for available water and nutrients.

With contemporary climate change, cultivated Vitis vinifera L. is at risk as climate is a critical component in defining ecologically fitted plant materiel. While winegrowers can draw on the rich diversity among grapevine varieties to limit expected impacts (Morales-Castilla et al., 2020), replacing a signature variety that has created a sense of local distinctiveness may lead to several challenges. In order to sustain wine identity in uncertain climate outcomes, the study of intra-varietal diversity is important to reflect the adaptive and evolutionary potential of current cultivated varieties. The aim of this ongoing study is to understand to what extent can intra-varietal diversity be a climate change adaptation solution. With a focus on early (Sauvignon blanc, Riesling, Grolleau, Pinot noir) to moderate late (Chenin, Petit Verdot, Cabernet franc) ripening varieties, data was collected for flowering and veraison for the various studied accessions (from conservatory plots) and clones. For these phenological growing stages, heat requirements were established using nearby weather stations (adapted from the GFV model, Parker et al., 2013) and model performances were verified. Climate change projections were then integrated to predict the future behaviour of the intra-varietal diversity. Study findings highlight the strong phenotypic diversity of studied varieties and the importance of diversification to enhance climate change resilience. While model performances may require improvements, this study is the first step towards quantifying heat requirements of different clones and how they can provide adaptation solutions for winegrowers to sustain local wine identity in a global changing climate. As genetic diversity is an ongoing process through point mutations and epigenetic adaptations, perspective work is to explore clonal data from a wide variety of geographic locations.

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).