Ampelograpic and genetic characterisation of grapevine genetic resources from Ozalj-Vivodina region (Croatia)

Root system architecture (RSA) is important for soil exploration and edaphic resources acquisition by the plant, and thus contributes largely to its productivity and adaptation to environmental stresses, particularly soil water deficit. In grafted grapevine, while the degree of drought tolerance induced by the rootstock has been well documented in the vineyard, information about the underlying physiological processes, particularly at the root level, is scarce, due to the inherent difficulties in observing large root systems in situ. The objectives of this study were to determine genetic differences in the root architectural traits and their relationships to water uptake in two Vitis rootstocks genotypes (RGM, 140Ru) differing in their adaptation to drought. Young rootstocks grafted upon the Riesling variety were transplanted into cylindrical tubes and in 2D rhizotrons under two conditions, well watered and moderate water stress. Root traits were analyzed by digital imaging and the amount of transpired water was measured gravimetrically twice a week. Root phenotyping after 30 days reveal substantial variation in RSA traits between genotypes despite similar total root mass; the drought-tolerant 140Ru showed higher root length density in the deep layer, while the drought-sensitive RGM was characterised by shallow-angled root system development with more basal roots and a larger proportion of fine roots in the upper half of the tube. Water deficit affected canopy size and shoot mass to a greater extent than root development and architectural-related traits for both 140Ru and RGM, suggesting vertical distribution of roots was controlled by genotype rather than plasticity to soil water regime. The deeper root system of 140Ru as compared to RGM correlated with greater daily water uptake and sustained stomata opening under water-limited conditions but had little effect on above-ground growth. Our results highlight that grapevine rootstocks have constitutively distinct RSA phenotypes and that, in the context of climate change, those that develop an extensive root network at depth may provide a desirable advantage to the plant in coping with reduced water resources.

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

Vineyards are complex agro-ecosystems with high spatial and temporal variability. An efficient training system may counteract the adverse effects of this variability. Moreover, considering the climate change issues, choosing an efficient training system that enhances water use and protects the vines from radiative thermal stress has become a priority for the farmers. A multidisciplinary approach that assesses the soil-crop-yield-wine relationships of vineyards in a distributed and holistic way could bring added knowledge on the behavior of the different training systems. This ongoing research aimed to implement a multidisciplinary approach to study the behavior of “Aglianico del Vulture” grapevines trained with two different systems: a spurred cordon (SC) and an “Alberello in parete” (AL), grown in a high-quality wine production area of Basilicata region (Italy). The approach merged several methods and scales of soil, ecophysiology, must/wine quality, and spectral data collection to assess the influence of the training system. Homogeneous zones (HZs) in both training systems were defined through a procedure based on geomorphological classification, unmanned aerial vehicles (UAV) images analysis, and a traditional soil survey supported by geophysical scanning. During the 2021 season, TDR probes monitored soil water content, while grapevine health status was assessed using eco-physiological measurements (LWP, chlorophyll content, PSII photosynthetic efficiency, LAI, and point-based field spectroscopy). These grapevine in-vivo measurements validated the spectral vegetation indexes (NDVI, RENDVI, CVI, and TVI) derived from the UAV multispectral imagery, which monitored the grapevine status in a distributed and non-invasive way. Grape yield, quality of berries, must and wine were measured to assess the effects of the training systems. The first experimental year results showed the variability of the vineyards and revealed relationships among soil parameters, crop characteristics, and vegetation indices of the SC and AL training systems. This multidisciplinary study could bring new insights into the vineyard training system’s effects on grape yield and wine quality.

In viticulture, the challenges of local climate modelling are multiple: taking into account the local environment, fine temporal and spatial scales, reliable time series of climate data, ease of implementation and reproducibility of the method. At the local scale, recent studies have demonstrated the contribution of spatialization methods for ground-based climate observation data considering topographic factors such as altitude, slope, aspect, and geographic coordinates (Le Roux et al, 2017; De Rességuier et al, 2020). However, these studies have shown questions in terms of the reproducibility and sustainability of this type of climate study. In this context, we evaluated the potential of MODIS thermal satellite images validated with ground-based climate data (Morin et al, 2020). Previous studies have been encouraging, but questions remain to be explored at the regional scale, particularly in the dynamics of the massive use of bioclimatic indices to classify the climate of wine regions. The results at the local scale were encouraging, but this approach was tested in the current study at the regional scale. Several objectives were set: 1) to evaluate the downscaling method for land surface temperature time series, 2) to identify regional thermal structure variations. We used weekly minimum and maximum surface temperature time series acquired by MODIS satellites at a spatial resolution of 1000 m and downscaled at 500 m using topographical variables. Two types of analyses were performed:

Increasing temperatures worldwide are expected to cause a change in spatial distribution of plant species along elevational gradients and there are already observable shifts to higher elevations as a consequence of climate change for many species. Not only naturally growing plants, but also agricultural cultivations are subject to the effects of climate change, as the type of cultivation and the economic viability depends largely on the prevailing climatic conditions. A shift to higher elevations therefore represents a viable adaptation strategy to climate change, as higher elevations are characterized by lower temperatures. This is especially important in the case of viticulture because a certain wine-style can only be achieved under very specific climatic conditions. Although there are several studies investigating climatic suitability within winegrowing regions or longitudinal shifts of winegrowing areas, little is known about how fast vineyards move to higher elevations, which may represent a viable strategy for winegrowers to maintain growing conditions and thus wine-style, despite the effects of climate change. We therefore investigated the change in the spatial distribution of vineyards along an elevational gradient over the past 20 years in the mountainous wine-growing region of Alto Adige (Italy). A dataset containing information about location and planting year of more than 26000 vineyard parcels and 30 varieties was used to perform this analysis. Preliminary results suggest that there has been a shift to higher elevations for vineyards in general (from formerly 700m to currently 850 m a.s.l., with extreme sites reaching 1200 m a.s.l.), but also that this development has not been uniform across different varieties and products (i.e. vitis vinifera vs hybrid varieties and still vssparkling wines). This is important for climate change adaptation as well as for rural development. Mountain areas, especially at mid to high elevations, are often characterized by severe land abandonment which can be avoided to some degree if economically viable and sustainable land management strategies are available.