Proposition of a simplified approach of the viticultural landscape

Monitoring vine water status is a major challenge for vineyard management because it influences both yield and harvest quality. It is also a challenge at the territorial scale for identifying periods of high water restriction or zones regularly impacted by water stress. This information is of major importance for defining collective strategies, anticipating harvest logistic or applying for irrigation authorisation. At this spatial scale, existing tools and methods for monitoring vine water status are few and often require strong assumptions (e.g. water balance model). This paper proposes to consider a collaborative collection of observations by winegrowers and wine industry stakeholders (crowdsourcing) as an interesting alternative. Indeed, it allows the collection of a large number of field observations while pooling the collection effort. However, the feasibility of such a project and its interest in monitoring vine water status at regional scale has never been tested.

The objective of this article is to explore the possibility of making a regional map of vine water status based on crowdsourcing observations. It is based on the study of the free mobile application ApeX-Vigne, which allows the collection of observations about vine shoot growth. This information is easy to collect and can be considered, under certain conditions, as a proxy for vine water status. This article presents the first results obtained from the nearly 18,000 observations collected by winegrowers and wine industry stakeholders during 2019, 2020 and 2021 seasons. It presents the vine shoot growth maps obtained at regional scale and their evolution over the three vintages studied. It also proposes an analysis of the factors that favoured the number of observations collected and those that favoured their quality. These results open up new perspectives for monitoring vine water status at a regional scale but above they provide references for other crowdsourcing projects in viticulture.

The Barossa zone is arguably one of the most well-recognised wine producing regions in Australia and internationally; known mainly for the production of its distinct Shiraz wines. However, within the broad Barossa geographical delimitation, a variation in terroir can be perceived and is expressed as sensorial and chemical profile differences between wines. This study aimed to explore the sub-division classification across the Barossa region using chemical and sensory measurements. Shiraz grapes from 4 different vintages and different vineyards across the Barossa (2018, n = 69; 2019, n = 72; 2020, n = 79; 2021, n = 64) were harvested and made using a standardised small lot winemaking procedure. The analysis involved a sensory descriptive analysis with a highly trained panel and chemical measurement including basic chemistry (e.g. pH, TA, alcohol content, total SO2), phenolic composition, volatile compounds, metals, proline, and polysaccharides. The datasets were combined and analysed through an unsupervised, clustering analysis. Firstly, each vintage was considered separately to investigate any vintage to vintage variation. The datasets were then combined and analysed as a whole. The number of sub-divisions based on the measurements were identified and characterised with their sensory and chemical profile and some consistencies were seen between the vintages. Preliminary analysis of the sensory results showed that in most vintages, two major groups could be identified characterised with one group showing a fruit-forward profile and another displaying savoury and cooked vegetables characters. The exploration of distinct profiles arising from the Barossa wine producing region will provide producers with valuable information about the regional potential of their wine assisting with tools to increase their target market and reputation. This study will also provide a robust and comprehensive basis to determine the distinctive terroir characteristics which exist within the Barossa wine producing region.

Climate change represents a major challenge for the French wine industry. Climatic conditions in French vineyards have already changed and will continue to evolve. One of the notable effects on grapevine is the advancing growing season. The aim of this study is to characterise the evolution of agroclimatic indicators (Huglin index, number of hot days, mean temperature, cumulative rainfall and number of rainy days during the growing season) at French wine-growing regions scale between 1980 and 2019 using gridded data (8 km resolution, SAFRAN) and for the middle of the 21th century (2046-2065) with 21 GCMs statistically debiased and downscaled at 8 km. A set of three phenological models were used to simulate the budburst (BRIN, Smoothed-Utah), flowering, veraison and theoretical maturity (GFV and GSR) stages for two grape varieties (Chardonnay and Cabernet-Sauvignon) over the whole period studied. All the French wine-growing regions show an increase in both temperatures during the growing season and Huglin index. This increase is accompanied by an advance in the simulated flowering (+3 to +9 days), veraison (+6 to +13 days) and theoretical maturity (+6 to +16 days) stages, which are more noticeable in the north-eastern part of France. The climate projections unanimously show, for all the GCMs considered, a clear increase in the Huglin index (+662 to 771 °C.days compared to the 1980-1999 period) and in the number of hot days (+5.6 to 22.6 days) in all the wine regions studied. Regarding rainfall, the expected evolution remains very uncertain due to the heterogeneity of the climates simulated by the 21 models. Only 4 regions out of 21 have a significant decrease in the number of rainy days during the growing season. The two budburst models show a strong divergence in the evolution of this stage with an average difference of 18 days between the two models on all grapevine regions. The theoretical maturity is the most impacted stage with a potential advance between 40 and 23 days according to wine-growing regions.

Since the 1980s global regime shift, grape growers have been steadily adapting to a changing climate. These adaptations have preserved the region-climate-cultivar rapports that have established the global trade of wine with lucrative economic benefits since the middle of 17th century. The advent of using fractions of crop and actual evapotranspiration replacement in vineyards with the use of supplemental irrigation has furthered the adaptation of wine grape cultivation. The shift in trellis systems, as well as pruning methods from positioned shoot systems to sprawling canopies, as well as adapting the bearing surface from head-trained, cane-pruned to cordon-trained, spur-pruned systems have also aided in the adaptation of grapevine to warmer temperatures. In warm climates, the use of shade cloth or over-head shade films not only have aided in arresting the damage of heat waves, but also identified opportunities to reduce the evapotranspiration from vineyards, reducing environmental footprint of vineyard. Our increase in knowledge on how best to understand the response of grapevine to climate change was aided with the identification of solar radiation exposure biomarker that is now used for phenotyping cultivars in their adaptability to harsh environments. Using fruit-based metrics such as sugar-flavonoid relationships were shown to be better indicators of losses in berry integrity associated with a warming climate, rather than solely focusing on region-climate-cultivar rapports. The resilience of wine grape was further enhanced by exploitation of rootstock × scion combinations that can resist untoward droughts and warm temperatures by making more resilient grapevine combinations. Our understanding of soil-plant-atmosphere continuum in the vineyard has increased within the last 50 years in such a manner that growers are able to use no-till systems with the aid of arbuscular mycorrhiza fungi inoculation with permanent cover cropping making the vineyard more resilient to droughts and heat waves. In premium wine grape regions viticulture has successfully adapted to a rapidly changing climate thus far, but berry based metrics are raising a concern that we may be approaching a tipping point.

Viticulture is entangled with weather and climate. Therefore, areas currently suitable for grape production can be challenged by climate change. Winegrowers in Italy already experiences the effect of climate change, especially in the form of warmer growing season, more frequent drought periods, and increased frequency of weather extremes.
The aim of this study is to investigate the impact of climate variability and change on grape yield in Italy to provide winegrowers the information needed to make their business more sustainable and resilient to climate change. We computed a specific range of bioclimatic indices, selected by the International Organisation of Vine and Wine (OIV), and correlated them to grape yield data. We have worked in collaboration with some wine consortiums in northern and central Italy, which provided grape yield data for our analysis.
Using climate variables from the E-OBS dataset we investigate how the bioclimatic indices changed in the past, and the impact of this change on grape productivity in the study areas. The climate impact on productivity is also investigated by using high-resolution convection-permitting models (CPMs – 2.2 horizontal resolution), with the purpose of estimating productivity in future emission scenarios. The CPMs are likely the best available option for this kind of impact studies since they allow a better representation of small-scale processes and features, explicitly resolve deep convection, and show an improved representation of extremes. In our study, we also compare CPMs with regional climate models (RCMs – 12 km horizontal resolution) to assess the added value of high-resolution models for impact studies. Further development of our study will lead to assessing the future suitability for vine cultivation and could lead to the construction of a statistical model for future projection of grape yield.