VINIoT – Precision viticulture service

Choosing the rootstock, the scion variety and the training system best suited to the local soil and climate are the key elements for an economically sustainable production of wine. The choice of the rootstock/scion variety best adapted to the characteristics of the soil is essential but, by changing climatic conditions, ongoing climate change disrupts the fine-tuned local equilibrium. Higher temperatures induce shifts in developmental stages, with on the one hand increasing fears of spring frost damages and, on the other hand, ripening during the warmest periods in summer. Expected higher water demand and longer and more frequent drought events are also major concerns. The genetic control of the phenotypes, by genomic information but also by the epigenetic control of gene expression, offers a lot of opportunities for adapting the plant material to the future. For complex traits, genomic selection is also a promising method for predicting phenotypes. However, ecophysiological modelling is necessary to better anticipate the phenotypes in unexplored climatic conditions Genetic approaches applied on parameters of ecophysiological models rather than raw observed data are more than ever the basis for finding, or building, the ideal varieties of the future.

Protected Designation of Origin “Jumilla” (PDO Jumilla) is located in the Spanish provinces of Albacete and Murcia, in the South-eastern part of the Iberian Peninsula, where most of the models predict a severe impact of climate change in next decades. PDO Jumilla covers an area of 247,054 hectares, of which more than 22,000 hectares

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.

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

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.