A 4D high resolution vineyard soil assessment for soil-hydrological interpretation in combination with automated data analysis and visualization to manage site-specific grape and wine quality

Soils in vineyards are recognized as complex agrosystems whose characteristics reflect complex interactions between natural factors (lithology, climate, slope, biodiversity) and human activities. To date, most of the unknown lies in an incomplete understanding of soil ecosystems, and specifically in the microbial biodiversity even though soil microbiota is involved in many key functions, such as nutrient cycling and carbon sequestration. Soil biological properties are indicative of soil quality. Therefore, understanding how soil communities are related to soil ecosystem functioning is becoming an essential issue for soil strategy conservation. Here, we propose to assess the importance of land-cover history on the present-day microbiological and physico-chemical properties. The studied area was selected in the Burgundian vineyards (Pernand-Vergelesses, Burgundy, France) where land occupation has been reconstructed over the last 40 years. Soil samples were collected in five areas reflecting various land cover history (forest, vineyards, shifting from forest to vineyards). For each area, physico-chemical parameters (pH, C, N, P, grain size) were measured and DNA was extracted to characterize the abundance and diversity of microbial communities. The obtained results show significant differences in the five areas suggesting that present-day microbial molecular biomass and bacterial taxonomic is partly inherited from past land occupation. Over longer period of time, such study of land-uses legacies may help to better assess ecosystem recovery and the impact of management practices for a better soil quality and vineyards sustainability.

Global climate change affects regional climates and hold implications for wine growing regions worldwide. Although winegrowers are constantly adapting to internal and external factors, it seems relevant to develop tools, which will allow them to better define actual and future agro-climatic potentials. Within this context, we develop a modelling approach, able to simulate the impact of environmental conditions and constraints on vine behaviour and to highlight potential adaptation strategies according to different climate change scenarios. Our modeling approach, named SEVE (Simulating Environmental impacts on Viticultural Ecosystems), provides a generic modeling framework for simulating grapevine growth and berry ripening under different conditions and constraints (slope, aspect, soil type, climate variability…) as well as production strategies and adaptation rules according to climate change scenarios. Each activity is represented by an autonomous agent able to react and adapt its reaction to the variability of environmental constraints. Using this model, we have recently analyzed the evolution of vineyards’ exposure to climatic risks (frost, pathogen risk, heat wave) and the adaptation strategies potentially implemented by the winegrowers. This approach, implemented for two climate change scenarios, has been initiated in France on traditional (Loire Valley) and emerging (Brittany) vineyards. The objective is to identify the time horizons of adaptations and new opportunities in these two regions. Carried out in collaboration with wine growers, this approach aims to better understand the variability of climate change impacts at local scale in the medium and long term.

Vitis champinii cultivars Ramsey and Dog-ridge are main choices for rootstocks to adapt viticulture in semi-arid and arid regions thanks to their distinctive tolerance to drought and salinity. However, genetic studies on non-vinifera rootstocks have heavily relied on the grapevine (Vitis vinifera) reference genome, which difficulted the assessment of the genetic variation between rootstock species and grapevines. In the present study, this limitation is addressed by introducing a novo phased genome assembly and annotation of Vitis champinii. This new Vitis champinii genome was employed as reference for mapping RNA-seq reads from the same species under drought and salt stresses, and for comparison the same reads were also mapped to the Vitis vinifera PN40024.V4 reference genome. A significant increase in alignment rate was gained when mapping Vitis champinii RNA-seq reads to its own genome, compared to the Vitis vinifera PN40024.V4 reference genome, thus revealing the expression levels of genes specific to Vitis champinii. Moreover, differences in coding sequences were observed in ortholog genes between Vitis champinii and Vitis vinifera, which therefore challenges previous differential expression analyses performed between contrasting Vitis genotypes on the same gene from the Vitis vinifera genome. Genes with possible implications in drought and salt tolerance have been identified across the genome of Vitis champinii, and the same genomic data can potentially guide the discovery of candidate genes specific from Vitis champinii for other traits of interest, therefore becoming a valuable resource for rootstock breeding designs, specially towards increased drought and salinity due to climate change.

Vitis vinifera L. ‘Gewürztraminer’ is a historical grape variety of Alto Adige (Südtirol), Italy, which is widely grown in the area of Tramin an der Weinstraße, but is also grown globally. It produces highly aromatic wines that are strongly influenced by the terroir of the vineyard sites where they are grown. This study looked at musts and young wines from ‘Gewürztraminer’ grapes harvested in seven distinct vineyards near Tramin and then processed at Cantina di Termeno, minimizing winemaking protocol variability. Samples were profiled using bidimensional gas chromatography–time-of-flight mass spectrometry, liquid chromatography coupled to electrochemical detection, and near-IR spectrometry. The data were subjected to Principle Component Analysis and Hierarchical Clustering Analysis. Sensory discriminant testing was undertaken using the sorting method with a semi-trained panel, and the data were processed using Multidimensional Scaling. Seven must/wine pairs could be distinguished based on their untargeted volatilome profiles and on sensory evaluation. As expected, there were greater differences in the volatile compounds between the wines than between the musts. The wines from vineyards 4 and 5 were nonetheless quite homogenous in terms of chemical and sensory analyses, as were the wines from vineyards 1 and 3. For the phenolic profile, differences were noted between the musts and wines of vineyards 2, 3, and 4, but the musts from vineyards 5 and 7 were similar. Sensory analysis showed the wines from vineyards 6 and 7 to be distinct from the rest. These results reinforce that the composition of ‘Gewürztraminer’ musts and wines is strongly determined by vineyard site, even in a small geographic area with high variability of the terroir (soil and microclimate), and that these differences are apparent in the flavours and aromas of the finished wines. Further confirmation would require a larger sample of wines, preferably from several vintages.

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.