ABSTRACT. Due to the development of connected and moderately cheap temperature sensors, climate zoning within vineyards is now more accessible to both the research community and the wine industry. However, the methodological framework for implementing climate zoning remains unclear. In order to clarify the methodology for climate mapping at the local level, we explore here the impact of sensor network density on the accuracy of climate mapping at the local level. Within an 800-hectare wine-growing area in Burgundy (France), 112 temperature sensors were deployed 60 cm above the ground in vineyard plots from March 2023 to September 2024. Spatial interpolation of daily minimum (Tmin) and maximum (Tmax) temperatures was compared for seven methods, first with all sensors deployed, then by reducing the number of sensors through stratified sampling based on terrain characteristics. Our results show that below 40 sensors (5 sensors/km²), spatial interpolation has more than a modeling day out of two an efficiency of less than 0.4, indicating poor performance. Between 5 and 10 sensors/km², random forest interpolation, calibrated by machine learning, performs best, especially for maximum temperatures, where interpolation is most inaccurate. With 112 sensors (14/km²), the regression-kriging method achieves the highest accuracy. The average RMSE reaches 0.4°C for Tmin and 0.56°C for Tmax. These results, as well as the impact of interpolation errors on various agroclimatic indices (average temperature during the growing season, heat stress indices), provide useful information for the implementation of climate zoning of wine-growing terroirs.

ABSTRACT. Climate change is disrupting grapevine phenology and threatening terroir-driven wine typicity, challenging the definition of optimal harvest timing. This study develops and validates an on-the-go dual-range hyperspectral imaging (HSI) workflow for non-destructive, real-time monitoring of grape maturity in Vitis vinifera L. cv. Tempranillo. The system integrates two push broom cameras—VIS-NIR (400–1000 nm) and SWIR (900–1700 nm)—mounted on a mobile platform operating under field conditions. Over seven sampling dates from veraison to harvest (August–September 2025), hyperspectral images were collected in a commercial vineyard in Logroño (La Rioja, Spain). Corresponding reference analyses included total soluble solids (TSS), pH, titratable acidity (TA), tartaric acid, malic acid, yeast-assimilable nitrogen (YAN), anthocyanins, and total phenolic index (TPI).

Partial least squares (PLS) regression models were developed to predict grape composition parameters from processed hyperspectral data. Model performance was assessed through cross-validation, exhibiting very good to excellent predictive performance for key technological maturity traits: TA (R²cv = 0.96), malic acid (R²cv = 0.94), pH (R²cv = 0.93), and TSS (R²cv = 0.88). YAN (R²cv = 0.71) achieved good quantitative accuracy, while tartaric acid (R²cv = 0.58), anthocyanins (R²cv = 0.60), and TPI (R²cv = 0.64) provided satisfactory qualitative discrimination among maturity classes. The high performance for malic acid highlights the relevance of including the SWIR spectral range, where absorption features of organic acids are more pronounced. This work represents, to the best of our knowledge, the first field-based demonstration of YAN prediction from hyperspectral data, expanding the analytical scope of proximal sensing for viticulture.

The proposed on-the-go HSI framework offers a practical, scalable tool for adaptive harvest decision-making under increasing climate variability. It supports the maintenance of varietal typicity and wine style consistency by facilitating timely, data-driven harvest scheduling. Future work will extend model validation across seasons and sites and integrate automated segmentation and machine learning algorithms for operational deployment.

ABSTRACT. Climate change is reshaping viticultural regions worldwide, altering temperature regimes, precipitation patterns, and the frequency of extreme weather events. These shifts pose major challenges to grapevine phenology, yield, and wine quality, challenging alternative approaches that account for the fine-scale environmental heterogeneity within vineyards. This study integrates high-resolution microclimate modelling (10 m spatial resolution) with the STICS crop model to assess vineyard responses to both present and future climate conditions. Two Portuguese living-lab vineyards—Quinta do Bomfim in the Douro wine region and Herdade do Esporão in Alentejo—were selected as complementary test sites, representing steep, heterogeneous topography versus flat, homogeneous terrain. Hourly temperature and precipitation data from ERA5-Land were bias-corrected using a quantile-mapping approach and dynamically downscaled with the NicheMapR model, which simulates the energy and mass exchanges governing local air temperature, humidity, wind speed, and soil moisture. By incorporating slope, aspect, and shading effects, the model captures the strong microclimatic gradients. The resulting datasets were used as inputs for the STICS model to simulate grapevine growth, phenology, and yield under a historical baseline (1981–2010) and two future periods (2041–2070 and 2071–2100) following RCP 4.5 and RCP 8.5 emission scenarios. Results show consistent warming across both sites, with mean air temperature increases by late century. Phenological stages such as flowering, fruit filling, and physiological maturity are projected to advance by 10–25 days, leading to shortened growing cycles and increased risk of heat and water stress during ripening. Simulated yields declined by up to 30% under RCP 8.5, reflecting the compounded effects of high temperatures and reduced soil moisture availability. The coupled NicheMapR–STICS framework provides a scalable tool for designing adaptation strategies specific to site conditions. These include optimised irrigation scheduling, canopy and soil-cover management, altered row orientation, and the selection of more heat- and drought-tolerant cultivars. By resolving sub-vineyard climatic variability, this integrative approach bridges the gap between regional climate projections and practical decision-making, supporting a transition toward climate-resilient and sustainable viticulture.

ABSTRACT. The grapevine (Vitis vinifera L.) is a drought tolerant crop species that can be cultivated without irrigation in dry climates, even with rainfall as low as 350 mm/year. Drought tolerance strategies involve, however, complex mechanisms. A multitude of strategies to cope with drought have been identified, and these are based on a wide range of physiological processes or structural features. Some of these strategies are short-term and involve adjustments on the time scale of minutes or hours, others are long-term and are implemented over an entire season or even across several years. Drought tolerance is highly variable among varieties. Identifying the most drought tolerant varieties for dry climates allows to make optimal use of increasingly scarce fresh water resources, either by maintaining dry farming wherever possible, or by minimizing the need for irrigation water where this practice is mandatory. As drought episodes become more frequent and intense under climate change, the issue of drought tolerance in increasingly addressed in the scientific literature. In most studies on drought tolerance in grapevine, only one strategy is investigated. These studies allow a better understanding of the particular mechanism involved in the strategy investigated, but the results are generally not of much interest for end-users, because one single mechanism cannot explain how grapevines behave in production conditions. After reviewing some of the major drought tolerance mechanisms in plants, a practical approach is proposed: visual observation of drought symptoms across a wide range of varieties in a common garden, scored on a range from 0 (no visible symptoms) to 5 (severe visible symptoms). These symptoms cannot always be related to a particular strategy or mechanism, but can be considered as a global assessment of the efficiency of the strategy implemented by the grapevine variety. The potential contribution of this approach to the study of drought tolerance mechanisms in grapevine, as well as its limitations, are discussed.

ABSTRACT. Climate is known as an essential factor for grapevine phenology, yield and quality, and climate change may challenge or open new opportunities of the sustainability of wine grape production. The wine industry in China spreads across a wide range of regions with huge diversity of climate patterns, while their climate change trends as well as the influences on grapevine growth and berry quality remain largely unknown. To fill these gaps, we have developed a series of modeling work, with historical long-term climate records, as well as field observation of phenology and berry quality data, to illustrate the regional climate change trends over the last 60 years in most of the wine regions in China. In addition, a phenology model able to precisely predicts the sugar-based maturity dates was developed suitable for the continental climate conditions in China, and then this maturity model was used to evaluate the risk of freezing injury before harvest with diverse cultivars of different precocities in different growing regions. Moreover, berry quality models, such as berry sugars and anthocyanins were also developed to evaluate the responses of different cultivars in the past and future climate scenarios. Finally, vineyard zoning was proposed based on an integrative model framework by considering both the current climate conditions as well as climate projections in the futures, so that providing a solid foundation for sustainable development of viticulture.

ABSTRACT. Climate change (CC) strongly affects grapevine development and wine typicity, driving shifts in the geographical distribution of viticulture. While global projections provide valuable insights, they often neglect fine-scale climatic variability, which is critical for site-specific vineyard management. This study assesses current and future viticultural climates in Uruguay and evaluates fine-scale projections for the emerging Atlantic coastal wine region. Observed daily temperature and precipitation data (1994–2023) from the Uruguayan Meteorological Institute were used to compute six viticulture-related indices (GDD, HI, rainfall, GFV, GSR for Tannat and Albariño). Data were spatialised at a 1-km resolution using a hybrid geostatistical model based on topographic and coastal predictors. Future climate projections were derived from twelve bias-corrected CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios, downscaled to 1 km resolution using a Self-Organizing Map (SOM) approach consistent with the ADVICLIM framework. Current conditions reveal a marked north–south thermal gradient, with the Huglin Index averaging 2374 ± 174, classifying northern regions as warm (IH5) and southeastern coastal vineyards as temperate (IH3–IH4). Projections indicate a progressive shift toward warmer classes, reaching +2 °C under SSP2-4.5 and up to +4 °C under SSP5-8.5 by 2100. Most regions currently temperate-warm (IH4) are expected to become warm (IH5) by mid-century and very warm (IH6) by the end of the century, while the Atlantic coast remains a climatic buffer. Phenological indices project earlier flowering and ripening of Tannat by two to four weeks, especially inland, reflecting accelerated vine development. At a finer scale, downscaling over the Garzón region highlights significant topographic and oceanic influences on spatial variability, emphasizing the need to consider microclimatic heterogeneity in adaptation strategies. These results underline the value of high-resolution modelling for guiding regional planning and promoting sustainable viticulture under future conditions.

ABSTRACT. In the face of environmental challenges and economic constraints, the transition to sustainable viticulture has become both a necessity and a strategic lever for winegrowing regions. In this context, the Yvorne Grandeur Nature association, founded in 2019, aims to make Yvorne (Switzerland) the first Swiss appellation fully committed to sustainability across the entire value chain, from grape production to wine marketing. The appellation is conceived as an open-air laboratory for testing and promoting more environmentally friendly practices, with a methodology designed to be transferable to other winegrowing regions.

Yvorne is located on the south-facing slopes of the Vaud Alps. Most of the vineyard is established on an alluvial fan formed after a major landslide from the massif north of the village. The lower plots have slopes of around 10°, whereas those in the upper part reach up to 58°. The village is crossed by a river, which subsequently flows into the Rhône. The combination of steep slopes and the presence of this watercourse increase the risk of plant protection products (PPPs) being transported to surface waters.

In 2024, a parcel-scale analysis was carried out to identify areas vulnerable to PPPs transfer via runoff. The approach combines field surveys with spatial analyses performed in a geographic information system (GIS). The study area covered 150 ha, corresponding to the entire vineyard surface of Yvorne. The variables considered include slope gradient and length, distance to the hydrographic network, landscape elements influencing runoff (road surfacing, drainage systems, hedges, forests, grass strips), soil texture, land use (proportion of grass cover within plots) and orientation of tillage in relation to the slope. Each factor is classified into different risk levels (from none to very high) and assigned a coefficient ranging from 0 to 4, defined on the basis of bibliographic references and expert knowledge (Noll et al., 2010). A multi-criteria evaluation grid is then used to integrate these factors and compute an overall risk index for each plot. This methodology allows to generate thematic maps for each factor and a synthetic map of PPPs transfer potential.

The analysis of each surveyed factors is ongoing and results are expected in spring 2026. This work will provide winegrowers with an operational decision-making tool, enabling them to identify at-risk plots and adapt their practices by implementing tailored corrective measures (e.g. grass cover management, tillage practices, landscape features) to reduce the transfer of plant protection products to surface waters.

ABSTRACT. Regional-scale vineyard monitoring is crucial for addressing climate change adaptation, notably water stress. While crowdsourcing offers a promising solution for collecting data at this large spatial scale, its true effectiveness, including participant mobilization and robustness against sampling biases, remains under-documented. This paper provides a critical analysis of crowdsourcing's potential and limitations for regional vineyard monitoring, using the seven-year Apex-Vigne project as a case study. Apex-Vigne monitors vine water status via a simple, calculated indicator, iG-Apex, derived from weekly vine shoot growth observations contributed by industry stakeholders (winegrowers and advisors) through a mobile application. The analysis focused on the spatio-temporal distribution of data collected in Metropolitan France, specifically within a 49,500 km2 Mediterranean study zone (2019–2025). The project’s capacity to generate regional-scale information was assessed by mapping iG-Apex values, and key scientific challenges were identified. Over seven seasons, Apex-Vigne successfully gathered 31,141 observations from over 887 contributors on 13,896 fields. Observations were collected following three main use cases scenarios according to the specific interests of contributors: on-farm experimentation at within-field level, field monitoring at farm level and reference field monitoring at regional level. The data volume proved sufficient to spatialize vine water status and illustrate temporal dynamics at the regional level. These results demonstrate crowdsourcing's potential as a new source of information for regional decision support in viticulture. The study also highlights scientific challenges raised by crowdsourcing projects in viticulture. Social sciences are needed to understand contributors' motivations and new data sciences approaches are to be explored to limit the influence of sampling biases or to automatically identify observations with atypical behaviour.

ABSTRACT. Spring frosts pose a significant threat to viticulture by damaging buds and, in severe cases, leading to their destruction. Climate change has exacerbated this issue by advancing phenological stages, making plants more vulnerable to prolonged frost events and increasing agronomic losses, yield reduction, and economic impacts on the wine industry.

In the Centre-Val de Loire region, winegrowers are increasingly adopting wind machines — fans mounted on masts that mix warmer air from upper layers with cold ground air, raising the temperature around the vines by a few degrees. Traditional frost-mitigation methods such as heaters and candles are still used, locally diffusing heat in vulnerable areas to safeguard the buds.

While scientific literature has primarily focused on field observations of the combined use of wind machines and heating systems, applying numerical simulation to this context is innovative. Field datasets on frost events are spatially sparse and limited in number, as frost occurrences are infrequent and depend on specific meteorological and topographic conditions. In contrast, numerical simulations allow dense, parametric exploration of frost scenarios, enabling systematic assessment across a wide range of configurations.

Large Eddy Simulation (LES) models, such as the open-source PALM model, offer advanced capabilities for studying the Atmospheric Boundary Layer (ABL). The PALM model, which includes a module based on actuator disk theory, has been adapted to simulate the airflow from wind machines in nocturnal stable ABL flows. Calibrated with field measurements, the model accurately reproduces the flow at vine height and the thermal signature of the jet during each tower rotation.

Findings from the European Innovation Partnership (EIP) SICTAG project (2019–2024) have raised two key questions : • How can heating devices be strategically placed around a wind machine, considering topography and frost severity, to enhance efficiency and reduce environmental impact ? • Does the continuous airflow from the wind machine create a crosswind strong enough to maintain generated heat at bud height?

Exploring these questions paves the way for sustainable frost-protection strategies. This research is part of the EIP OPTITAG project (2025–2028), which aims to optimize wind machine use through a multidisciplinary approach integrating agronomy, aerodynamics, acoustics, sociology, and economics. The model will incorporate topographic and ABL data for realistic frost-event simulations. A dedicated module will reproduce the thermal plume from heat sources, and sensitivity analyses on key parameters will guide the development of efficient combined protection strategies under varying frost conditions.

ABSTRACT. Fungal diseases such as downy mildew (Plasmopara viticola) can severely impact grapevine yield and quality, making timely-wise fungicide applications essential. For that, Decision Support Systems (DSS) in precision viticulture guide farmers on optimal timing for treatments. However, most current DSS rely mainly on weather data and overlook biological indicators such as real-time dynamics of spore concentrations within the vineyard. To address this gap, we assessed the use of an automatic air-flow cytometer (SwisensPoleno Jupiter) for the real-time detection and quantification of P. viticola sporangia. The instrument combines holographic imaging, fluorescence spectroscopy, and artificial intelligence-based classification. Laboratory measurements using naturally and artificially infected leaves provided training datasets comprise >17,000 single sporangia (events), enabling the development of classifier software using advanced AI methods. We used Random Forest models. Specificity tests of the classifier against databases of common airborne fungal spores confirmed their high accuracy in matching true with predicted labels. Field validation was conducted in Swiss vineyards using complementary approaches: Hirst-type spore traps (microscopy identification of sporangia and qPCR-based DNA quantification) and SwisensPoleno classification. Spearman correlations were calculated to compare between strategies (p < 0.5). Comparison between manual microscopy and SwisensPoleno classification began to emerge during the 2023 pilot study (60 days) and strengthened markedly throughout the 2024 monitoring season (140 days). Seasonal analyses revealed that SwisensPoleno data correlated more strongly with DNA quantification (r = 0.53) than with microscopy identification (r = 0.44). Correlations were weak early in the season, during leaf development and the onset of flowering, but strengthened as vine phenology progressed and disease pressure increased, reaching up to r = 0.94 with microscopy counting and r = 0.83 with DNA concentration. Moreover, airborne concentrations of P. viticola sporangia were strongly associated with mean daily air temperature, and daily sporangia measurements were different depending on the aerosol inlet height of the SwisensPoleno instrument. Visual disease assessments in 2024 confirmed high downy mildew pressure, affecting nearly 100% of unprotected leaves. Consequently, DNA concentrations were strongly correlated with symptom severity (r = 0.96). With further refinement, these first models for real-time and automatic identification of P. viticola sporangia have the potential to provide reliable spore monitoring data for DSS integration, supporting precision viticulture worldwide.

ABSTRACT. The present study aims to develop a multidisciplinary method capable of estimating the age of vineyards within the Protected Designation of Origin (P.D.O.) Campo de Borja in a probabilistic manner. This objective arose from the growing interest in "old vineyards", driven by their heritage value and the oenological character they provide, that generates a need for scientific tools that allow their objective identification and certification. Although the International Organisation of Vine and Wine (OIV, 2024) has recently established a consensus definition, reliable historical records are often unavailable in many contexts to verify this information. Therefore, we proposed an approach based on the compilation and analysis of the plot's configuration using historical aerial photographs, vine training scheme, and a morphological study analyzing the plants' annual growth. A total of 85 plots were examined between 2023 and 2025. Results confirm a moderate-to-strong correlation between the geospatial age and the P.D.O. records in the total study set (r = 0.504). However, in the sub-sample of 14 plots selected for their verified age, both indicators showed an insufficient correlation with local records (geospatial r = 0.38, morphological r = 0.17), due to the lack of accurate historical data. In any case, the proposed methodology allowed a reliable estimation of age, constituting a useful tool for the certification and valorization of the viticultural heritage.

ABSTRACT. Grapevine (Vitis vinifera) is the world’s third most valuable horticultural crop. Today, climate change significantly threatens grape productivity, notably due to more frequent and extended drought periods. To address the critical issue of grapevine response to water stress, soil-plant hydraulic processes can be considered the cornerstone of the physiological mechanisms involved in grapevine tolerance to drought. Although recognized, the key role of belowground hydraulics on grapevine water status is rarely addressed because difficult to measure. This work aims to understand how soil-grapevine hydraulics impact the stomatal control of in situ grapevine cv. Chardonnay. First, we revealed experimentally that the transpiration control of grapevine is soil texture-specific and is triggered by a decrease of belowground hydraulic conductance, rather than xylem cavitation. Then, by using a biophysical model representing explicitly the series of hydraulic conductances between the bulk soil and the trunk, we demonstrated that during drought, the main hydraulic bottleneck is the rhizosphere in sandy soils, while it is the root system in loamy soils. By examining the complex dynamics of soil-grapevine water interactions under various edaphic conditions, this work could help winemakers to address uncertainties linked to climate change, thereby enhancing overall vineyard resilience.

ABSTRACT. The history of grapevine in South America dates back approximately 500 years. During this period, criolla varieties emerged from natural crossings among the cultivars introduced by the Spanish (e.g., Listán Prieto, Muscat of Alexandria, or Muscat à Petits Grains). Using molecular markers, we have identified and recovered around 60 unique varieties from different regions of Argentina, which are preserved in our germplasm collection. Most of them are not grown commercially and their enological potential remains unknown. Therefore, in this study we aimed to characterize them to assess their enological aptitude. During the 2023–24 and 2024-25 seasons, we analyzed 20 varieties (11 white, 5 red, and 4 pink) in terms of berry weight, total soluble solids (TSS), pH, titratable acidity, yield components, balance indexes, and the chemical composition of berries and wines. Ripening dynamics were analyzed from veraison based on growing degree days (GDD), determining the GDD at which rapid sugar accumulation began, maximum berry weight occurred, and maximum TSS was reached. White varieties were harvested when TSS reached 21–22 °Brix, and pink and red varieties at 23–24 °Brix. Our results showed high variability in yield components. Berry weight ranged from 1.5 g to 4.4 g, and clusters per plant from 15 to 50 clusters plant⁻¹. Varieties with the lowest berry weight (e.g. Uva Pascua, Canela, and Apicia) have previously been shown to have Muscat à Petits Grains as one of their parents, while several others exhibiting the highest berry weights (e.g., Criolla Blanca, Moscatel Tinto, or Torrontés Sanjuanino) descend from Muscat of Alexandria. Yield ranged from 3.5 kg plant⁻¹ in Uva Pascua to 15 kg plant⁻¹ in Balsamina. Most varieties showed a Ravaz index between 5 and 10, although some were below or above this range. Most varieties exhibited low pH at harvest, from 3.15 to 3.65. For comparison, Chardonnay in the same vineyard and at similar °Brix (22 °Bx) presented a pH of 3.45, while Malbec (23.5 °Bx) ranged between 3.65 and 3.8. Growing degree days from veraison to harvest ranged from 290 °Cd for Canela to 1100 °Cd for Balsamina. This study demonstrates that there is substantial diversity within Argentina’s heritage grapevine varieties that must be better explored.

ABSTRACT. As predicted by climate models, the rise in global temperatures is set to have a significant impact on vineyards. In regions such as the Douro, models show a change in the pattern of annual precipitation and an increase in temperature during the growing season (March–September or April–October). This may affect the suitability of some varieties for the region in the near future (Jones & Alves, 2012). In order to maintain the quality of the wines produced, winegrowers could adopt various adaptation measures. Short-term measures are applied during the annual cycle of the vine, while long-term measures are adopted beyond the lifetime of the vineyard. One of the most widely discussed long-term adaptation measures is selecting better-adapted grapevine varieties (van Leeuwen et al., 2024). In 2014, Symington Family Estates installed an experimental vineyard in the Douro Superior sub-region with 53 different Vitis vinifera varieties. The aim is to preserve and gain knowledge about these varieties, promote vine diversity, and study their viticultural and oenological potential under the same climate conditions. Since 2016 (ten years dataset), phenology data has been collected according to the VitAdapt project protocol (Destrac-Irvine & van Leeuwen, 2016), with grape samples collected weekly from mid-veraison to assess ripening. During the 2023 and 2024 seasons, the isotopic δ13C content of grape juice was analysed to indirectly study the water use efficiency of grapevine varieties. The collected data enabled the classification of grapevine varieties according to cycle duration, thermal requirements for completing the main phenological phases and their capacity to cope with heat and water scarcity through carbon isotope discrimination (δ13C) (Plantevin et al., 2022; van Leeuwen et al., 2023). The results obtained help to fill an information gap regarding grapevine varieties by providing winegrowers with knowledge to help them select grapes that are well adapted to local climatic conditions, thereby ensuring the sustainability of the industry in the future.

ABSTRACT. The original paper, published in International Review of Intellectual Property and Competition Law (Max Planck Institute for Innovation and Competition & Springer Nature), “examines the intersection of innovation and tradition in the context of Geographical Indications (GIs) for wine, focusing on the transformative potential of New Genomic Techniques (NGTs) in viticulture. GIs signal prove- nance, whilst requiring a commitment to traditional production methods. However, viticulture in the EU today faces several challenges, including climate change, increasing competition from New World wine producers, and shifting consumer preferences. Innovation is an important resource for meeting these challenges. NGTs, exemplified by CRISPR technology, enable precise genetic modifications to promote traits such as disease resistance while preserving the genetic identity of traditional grape varieties. They hold out the promise of reconciling innovation with tradition. The European Commission’s Proposal for a Regulation on plants obtained by certain new genomic techniques (COM(2023) 411 final) could pave the way for their adoption across the wine sector. However, the adoption of NGTs within this sector raises complex regulatory, legal, and socio-economic questions. The novel contribution of the study is to analyse the compatibility of NGTs with the European Union’s strict GI regulations, considering public perception challenges related to biotechnology, and implications for wine typicity and varietal diversity. In bridging the domains of GIs, biosafety regulation, and agricultural innovation, this study identifies the challenges to be overcome by the EU wine sector when seeking to reconcile its deep-rooted traditions with the radical potential of NGTs” (Vives-Vallés & Gangjee, 2025, p. 1141). This communication will provide an updated overview of the matter, by addressing the main developments and challenges encountered in the legislative process and the evolution of the academic debate, as well as further insights on the questions raised in the original paper, including the foreseeable implications for GI protected wines.

ABSTRACT. In viticulture, the evaluation of scion varieties and rootstocks relies on multi-site field trials that must be maintained and monitored for several years once the vineyards become productive. Such trials are costly and resource-demanding, so it would be valuable to know how long they need to be maintained to provide meaningful results. However, we have little evidence of how long a trial must last to reach robust and reliable conclusions. To shed light on this question, in this work we analysed yield data from a 10-year Tempranillo trial that included both commercial and newly developed rootstocks to quantify how the number of evaluated years affects the robustness of rootstock performance rankings. The dataset was analysed using several complementary approaches. For each possible trial duration from two to ten years, all combinations of years were treated as partial series and their rankings compared with that obtained from the complete 10-year dataset. Rank-based statistics, including Kendall’s τ and pairwise inversion rate were used to quantify stability. To assess the robustness of conclusions across different trial durations, we also applied leave-one-year-out and leave-k-years-out simulations. The analyses of commercial rootstocks performance revealed a rapid increase in stability with the number of evaluated years, followed by a plateau beyond a certain duration. In contrast, newly developed selections displayed slower convergence and lower stability at comparable trial lengths, suggesting that longer evaluations are needed to reach equivalent reliability.

ABSTRACT. Climate change is driving the wine industry to re-evaluate the appropriate use of rootstocks. The French network of vine rootstock experiments, established by research and technical institutes, launched a study (2023–2026) to collect and analyse collectively the data of field trials distributed across the French wine regions. The objective was to improve our general knowledge about the roles of rootstocks on vine agronomic performances. Data from 75 experiments conducted in French vineyards across nine wine-growing regions have been integrated into a database. The meta-analysis included 18 experiments with pruning weight measurements, 34 with yield data, and 14 with Ravaz Index values. To quantify rootstock effects and establish a classification based on vigor and yield, the data were normalized based on the average got in each experiment each year, to eliminate the influence of regions, vineyard management practices and vintages. The study shows that there is a significant effect of the rootstock on the normalized variables (pruning wood weight, yield and Ravaz Index). The percentages of variances explained by the rootstock are 9.6% on the normalized pruning weight, 16 % on the normalized yield and 12% on the normalized Ravaz Index. Overall Rupestris du Lot significantly increased pruning wood weight in comparison to the other rootstocks, whereas 3309 C, RSB 1, and Riparia Gloire de Montpellier significantly decreased it. Similarly, 420 A and 41 B MGt significantly increased yield compared to the other rootstocks, while Vialla and Nemadex Alain Bouquet significantly decreased it. 41 B MGt, 420 A, and Riparia Gloire de Montpellier significantly increased the Ravaz Index, whereas 140 Ru, 1103 P, 44-53 M, and Rupestris du Lot significantly decreased it. There is a significant effect of the age of the vineyard and of the density of plantation on the pruning wood weight and the yield. Eventually, our results supported the idea that organizing a multi-level network of partners and sharing results for meta-analyses are essential to improving our understanding of the complex interactions between rootstock, scion, and environment, as well as facilitating the exchange of tools, expertise, and resources.

ABSTRACT. Rootstocks are key to sustaining yield, wine style, and vineyard resilience under increasing climatic variability. However, decision-making for matching genotypes to site conditions remains constrained by limited belowground data and the perennial nature of grapevine root system development, highlighting the need for models that help explore structural and functional root system dynamics virtually.

We present a new process-based model for perennial grapevine root growth that integrates seasonal dormancy, age-dependent turnover of structural and absorptive roots, secondary thickening, and functional transitions emerging from root demography. The model extends the CPlantBox framework and is parameterized using high-resolution 3D root architecture data from both young and mature vines. By coupling root development with soil hydraulics, it enables dynamic estimation of water uptake under contrasting site conditions.

We demonstrate how this framework can serve as a terroir-oriented decision tool to explore rootstock × environment × management interactions. The model dynamically simulates root system architecture and couples it with environmental and management factors. “Environment” can be represented by climatic and edaphic conditions (e.g., shallow soils with intermittent summer rainfall versus deep profiles recharged during winter), while “management” can be represented by plant–plant interactions such as cover cropping, which introduces competition for soil resources. Simulations translate measurable RSA traits such as rooting depth, vertical distribution, lateral spread and structural root longevity into performance indicators for drought resilience and resource use.

This approach provides a mechanistic link between site properties, root system architecture, and vine water relations, enabling transparent evaluation of trait-based trade-offs across contrasting rootstock genotypes and drought scenarios. Rather than identifying a single “best” rootstock, it supports evidence-based matching of root systems to vineyard conditions. Beyond site-specific decision support, the model lays the groundwork for integrating perennial root development into vineyard water balance models, climate adaptation scenarios, and breeding pipelines targeting root traits for drought resilience.