Studying heat stress response of grapevine berries in the field often relies on weather conditions during the growing season. We constructed a mobile heating device, able to induce controlled heat stress on grapes in vineyards. The heater consisted of six 150 W infrared lamps mounted in a profile frame. Heating power of the lamps could be controlled individually by a control unit consisting of a single board computer and six temperature sensors to reach a pre-set temperature. The heat energy applied to individual berries within a cluster decreases by the squared distance to the heat source, enabling the establishment of temperature profiles within individual clusters. These profiles can be measured by infrared thermography once a steady state has been reached. Radiant flux density received by a berry depending on the distance was calculated based on a view factor and measured lamp surface temperature and resulted to 665 Wm-2 at 7cm. Infrared thermography of the fruit surface was in good agreement with measurements conducted with a thermocouple inserted at epidermis level. In combination with infrared thermography, the presented device offers possibilities for a wide range of applications like phenotyping for heat tolerance in the field to proceed in the understanding of the complex response of plants to heat stress. Sunburn necrosis symptoms were artificially induced with the aid of the device for cv. Bacchus and cv. Sylvaner in the 2020 and 2021 growing season. Threshold temperatures for sunburn induction (LT5030min) were derived from temperature data of single berries and visual sunburn assessment, applying logistic regression. A comparison of threshold temperatures for the occurrence of sunburn necrosis confirmed the higher susceptibility of cv. Bacchus. The lower susceptibility of cv. Sylvaner did not seem to be related to its phenolic composition, rendering a thermoprotective role of berry phenolic compounds unlikely.

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.

The Languedoc-Roussillon wineries are facing a decline in wine yields particularly PGI yields due to many factors. Climate change is just ones, but is expected to increase in the future. There is also structurally a large heterogeneity of yield profiles among terroirs, varieties and strategies. This work investigates the link between yield, competitiveness and resilience to explore how resilient winegrowers have been in the recent past. To this end two approaches have been combined; (i) an accountancy database analysis at estate scale and (ii) municipality level competitiveness analysis. A new resilience indicator that characterizes the capacity of an estate to absorb yield variation is also defined. The FADN database between 2000 and 2018 of ex-Languedoc-Roussillon (France) and other data are used to analyse the current situation and the past evolution of competitiveness and resilience by type of estate (type of farm: PGI and/or PDO & type of commercialization: bulk and/or bottles). The net margin, which defines competitiveness, is not correlated to yield for all types but depends on the type of commercialization and the level of specialisation. The resilience indicator shows that the net margin of estates specialized in PGI is particularly sensitive to yield declines. We also show that price evolutions seem to compensate the effect of yield losses for the majority of types. Municipality scale analysis shows the links between local pedoclimate, yield, commercialization strategies and price. Overlapping a PDO with a PGI does not always increase a municipality’s PGI competitiveness. It is difficult to make links between causes and effects due to the complexity of the wine production system. Production diversification may be a solution. Resorting to the two level of analysis helps resolving the data gap that is necessary to explore the links between yield and economic performance of the wine estates in the long term.

Barolo DOCG is an economically important wine producing region in Northwest Italy. It is a small region of approximately 70 km2 gross area. The topography is very complex with steep sloped hills ranging in elevation from below 200 m to 550 m. Barolo DOCG wine is made exclusively from the Nebbiolo grape. Bioclimatic indexes are often used in viticulture to gain a better understanding of broader climate trends which can be compared temporally and geographically. These indexes are also used for identifying potential phenological timing, growing region suitability, and potential risks associated with expected climatic changes. Understanding how topography influences bioclimatic indexes can help with understanding of mesoscale climate behaviour leading to improved decision making and risk management strategies. The average monthly maximum and minimum temperatures, the Cool Night Index, the Huglin Index, and the monthly diurnal range (from July to October) were calculated using data from 45 weather stations within a 40 km radius of the Barolo DOCG growing area between the years 1996 and 2019. Linear and multiple regression models were developed using independent variables (elevation, aspect, slope) extracted from a digital elevation model to identify significant relationships. Bioclimatic indexes were then kriged with external drift using independent variables that showed significant relationships with the bioclimatic index using a 100 m resolution grid. The maximum monthly temperatures and the Huglin Index showed consistent significant negative relationships with elevation in all years. The minimum monthly temperatures showed no relationship with elevation but in some months a small but significant relationship was observed with aspect. Due to the lack of a relationship between minimum monthly temperatures and elevation compared to the significant relationship between maximum monthly temperatures and elevation, monthly diurnal range had a negative relationship with elevation.

This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.