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Increasing water scarcity challenges crop sustainability inmany regions. As a consequence, the enhancement of transpiration efficiency (TE)—that is, the biomass produced per unit of water transpired—has become crucial in breeding programs. This could be achieved by reducing plant transpiration through a better closure of the stomatal pores at the leaf surface. However, this strategy generally also lowers growth, as stomatal opening is necessary for the capture of atmospheric CO₂ that feeds daytime photosynthesis. Here, we considered the reduction in transpiration rate at night (En) as a possible strategy to limit water use without altering growth. For this purpose, we carried out a genetic analysis for En and TE in grapevine, a major crop in drought-prone areas. Using recently developed phenotyping facilities, potted plants of a cross between Syrah and Grenache cultivars were screened for 2 y under well-watered and moderate soil water deficit scenarios. High genetic variability was found for En under both scenarios and was primarily associated with residual diffusion through the stomata. Five quantitative trait loci (QTLs) were detected that underlay genetic variability in En. Interestingly, four of them colocalized with QTLs for TE. Moreover, genotypes with favorable alleles on these common QTLs exhibited reduced En without altered growth. These results demonstrate the interest of breeding grapevine for lower water loss at night and pave the way to breeding other crops with this underexploited trait for higher TE.

In a dynamic business environment, the accuracy of sales forecasts plays a pivotal role in strategic decision making and resource allocation. This article offers a systematic review of the existing literature on techniques and methodologies used in forecasting, especially in sales forecasting across various domains, aiming to provide a nuanced understanding of the field. Our study examines the literature from 2013 to 2023, identifying key techniques and their evolution over time. The methodology involves a detailed analysis of 516 articles, categorized into classical qualitative approaches, traditional statistical methods, machine learning models, deep learning techniques, and hybrid approaches. The results highlight a significant shift towards advanced methods, with machine learning and deep learning techniques experiencing an explosive increase in adoption. The popularity of these models has surged, as evidenced by a rise from 10 articles in 2013 to over 110 by 2023. This growth underscores their growing prominence and effectiveness in handling complex time series data. Additionally, we explore the challenges and limitations that influence forecasting accuracy, focusing on complex market structures and the benefits of extensive data availability.

The stomatal control of transpiration is one of the major strategies by which plants cope with water stress. Here, we investigated the genetic architecture of the rootstock control of scion transpiration-related traits over a period of 3 yr. The rootstocks studied were full sibs from a controlled interspecific cross (Vitis vinifera cv. Cabernet Sauvignon x Vitis riparia cv. Gloire de Montpellier), onto which we grafted a single scion genotype. After 10 d without stress, the water supply was progressively limited over a period of 10 d, and a stable water deficit was then applied for 15 d. Transpiration rate was estimated daily and a mathematical curve was fitted to its response to water deficit intensity. We also determined delta C-13 values in leaves, transpiration efficiency and water extraction capacity. These traits were then analysed in a multienvironment (year and water status) quantitative trait locus (QTL) analysis. Quantitative trait loci, independent of year and water status, were detected for each trait. One genomic region was specifically implicated in the acclimation of scion transpiration induced by the rootstock. The QTLs identified colocalized with genes involved in water deficit responses, such as those relating to ABA and hydraulic regulation. Scion transpiration rate and its acclimation to water deficit are thus controlled genetically by the rootstock, through different genetic architectures.

In the face of water stress, plants evolved with different abilities to limit the decrease in leaf water potential, notably in the daytime (ΨM). So-called isohydric species efficiently maintain high ΨM, whereas anisohydric species cannot prevent ΨM from dropping as soil water deficit develops. The genetic and physiological origins of these differences in (an)isohydric behaviours remain to be clarified. This is of particular interest within species such as Vitis vinifera L. where continuous variation in the level of isohydry has been observed among cultivars. With this objective, a 2 year experiment was conducted on the pseudo-F1 progeny from a cross between the two widespread cultivars Syrah and Grenache using a phenotyping platform coupled to a controlled-environment chamber. Potted plants of all the progeny were analysed for ΨM, transpiration rate, and soil-to-leaf hydraulic conductance, under both well-watered and water deficit conditions. A high genetic variability was found for all the above traits. Four quantitative trait loci (QTLs) were detected for ΨM under water deficit conditions, and 28 other QTLs were detected for the different traits in either condition. Genetic variation in ΨM maintenance under water deficit weakly correlated with drought-induced reduction in transpiration rate in the progeny, and QTLs for both traits did not completely co-localize. This indicates that genetic variation in the control of ΨM under water deficit was not due simply to variation in transpiration sensitivity to soil drying. Possible origins of the diversity in (an)isohydric behaviours in grapevine are discussed on the basis of concurrent variations in soil-to-leaf hydraulic conductance and stomatal control of transpiration. This study on a grapevine mapping population shows that isohydric or anisohydric behaviour is under genetic control and is not simply controlled by transpiration response to soil drought.

Taking into account the major economical role and specificities of the French wine industry, adaptation to climate change is a very challenging issue. In 2011, 23 research teams launched a systemic and multidisciplinary program to analyze the impacts from the vine to the region, to define adaptation strategies combining technical, spatial and organizational options and to evaluate the perception by the actors and consumers of climate change issues. Thermal variability was studied at local scale to develop high resolution atmospheric models which better simulate future climate trends. Impacts on growth/developmental conditions and vine responses were estimated from the calculation of eco-climatic indices and a combination of functional models. Genetic and physiological bases of grapevine adaptation to high temperature and drought were analyzed. Improving oenological and cultural practices as well as plant material innovation have been investigated as major technical adaptations. How these options could be implemented at the plot level was examined to elaborate decision tools. Multi-agent modelling was developed for this purpose. Surveys were performed to evaluate the perception of the main actors regarding climate change and their level of acceptability towards technical changes. Consumer acceptability of new types of wines was also investigated with an experimental economy approach. Finally a foresight exercise was conducted to design four potential adaptation strategies: conservative, innovative, nomad and liberal. Outcomes of this exercise are now used as a tool for wine industry members to develop their own strategic plan for adaptation.

BACKGROUND AND AIMS: In grapevine, canopy-structure-related variations in light interception and distribution affect productivity, yield and the quality of the harvested product. A simple statistical model for reconstructing three-dimensional (3D) canopy structures for various cultivar-training system (C x T) pairs has been implemented with special attention paid to balance the time required for model parameterization and accuracy of the representations from organ to stand scales. Such an approach particularly aims at overcoming the weak integration of interplant variability using the usual direct 3D measurement methods. MODEL: This model is original in combining a turbid-medium-like envelope enclosing the volume occupied by vine shoots with the use of discrete geometric polygons representing leaves randomly located within this volume to represent plant structure. Reconstruction rules were adapted to capture the main determinants of grapevine shoot architecture and their variability. Using a simplified set of parameters, it was possible to describe (1) the 3D path of the main shoot, (2) the volume occupied by the foliage around this path and (3) the orientation of individual leaf surfaces. Model parameterization (estimation of the probability distribution for each parameter) was carried out for eight contrasting C x T pairs. KEY RESULTS AND CONCLUSIONS: The parameter values obtained in each situation were consistent with our knowledge of grapevine architecture. Quantitative assessments for the generated virtual scenes were carried out at the canopy and plant scales. Light interception efficiency and local variations of light transmittance within and between experimental plots were correctly simulated for all canopies studied. The approach predicted these key ecophysiological variables significantly more accurately than the classical complete digitization method with a limited number of plants. In addition, this model accurately reproduced the characteristics of a wide range of individual digitized plants. Simulated leaf area density and the distribution of light interception among leaves were consistent with measurements. However, at the level of individual organs, the model tended to underestimate light interception.

Plants evolved different strategies to cope with water stress. While isohydric species maintain their midday leaf water potential (ΨM) under soil water deficit by closing their stomata, anisohydric species maintain higher stomatal aperture and exhibit substantial reductions in ΨM. It was hypothesized that isohydry is related to a locally higher sensitivity of stomata to the drought-hormone abscisic acid (ABA). Interestingly, recent lines of evidence in Arabidopsis suggested that stomatal responsiveness is also controlled by an ABA action on leaf water supply upstream from stomata. Here, we tested the possibility in grapevine that different genotypes ranging from near isohydric to more anisohydric may have different sensitivities in these ABA responses. Measurements on whole plants in drought conditions were combined with assays on detached leaves fed with ABA. Two different methods consistently showed that leaf hydraulic conductance (Kleaf) was downregulated by exogenous ABA, with strong variations depending on the genotype. Importantly, variation between isohydry and anisohydry correlated with Kleaf sensitivity to ABA, with Kleaf in the most anisohydric genotypes being unresponsive to the hormone. We propose that observed response of Kleaf to ABA may be part of the overall ABA regulation of leaf water status.

This paper presents HydroShoot, a leaf-based functional-structural plant model (FSPM) that simulates gas exchange rates of complex plant canopies under water deficit conditions. HydroShoot is built assuming that simulating both the hydraulic structure of the shoot together with the energy budget of individual leaves is the asset for successfully scaling-up leaf to canopy gas exchange rates. HydroShoot includes three interacting modules: hydraulic, which calculates the distribution of xylem water potential across shoot hydraulic segments; energy, which calculates the complete energy budget of individual leaves; and exchange, which calculates net carbon assimilation and transpiration rates of individual leaves. HydroShoot was evaluated on virtual and real grapevines having strongly contrasted canopies, under well-watered and water deficit conditions. It captured accurately the impact of canopy architecture and soil water status on plant-scale gas exchange rates and leaf-scale temperature and water potential. Both shoot hydraulic structure and leaf energy budget simulations were, as postulated, required to adequately scaling-up leaf to canopy gas exchange rates. Notwithstanding, simulating shoot hydraulic structure was found more necessary to adequately performing this scaling task than simulating leaf energy budget. That is, the intra-canopy variability of leaf water potential was a better predictor of the reduction of whole plant gas exchange rates under water deficit than the intra-canopy variability of leaf temperature. We conclude that simulating the shoot hydraulic structure is a prerequisite if FSPMs are to be used to assess gas exchange rates of complex plant canopies as those of grapevines. Finally, HydroShoot is available through the OpenAlea platform (https://github.com/openalea/hydroshoot) as a set of reusable modules.

• Background and Aims Shoot architecture variability in grapevine (Vitis vinifera) was analysed using a generic modelling approach based on thermal time developed for annual herbaceous species. The analysis of shoot architecture was based on various levels of shoot organization, including pre‐existing and newly formed parts of the stem, and on the modular structure of the stem, which consists of a repeated succession of three phytomers (P0–P1–P2). • Methods Four experiments were carried out using the cultivar ‘Grenache N’: two on potted vines (one of which was carried out in a glasshouse) and two on mature vines in a vineyard. These experiments resulted in a broad diversity of environmental conditions, but none of the plants experienced soil water deficit. • Key Results Development of the main axis was highly dependent on air temperature, being linearly related to thermal time for all stages of leaf development from budbreak to veraison. The stable progression of developmental stages along the main stem resulted in a thermal‐time based programme of leaf development. Leaf expansion rate varied with trophic competition (shoot and cluster loads) and environmental conditions (solar radiation, VPD), accounting for differences in final leaf area. Branching pattern was highly variable. Classification of the branches according to ternary modular structure increased the accuracy of the quantitative analysis of branch development. The rate and duration of leaf production were higher for branches derived from P0 phytomers than for branches derived from P1 or P2 phytomers. Rates of leaf production, expressed as a -function of thermal time, were not stable and depended on trophic competition and environmental conditions such as solar radiation or VPD. • Conclusions The application to grapevine of a generic model developed in annual plants made it possible to identify constants in main stem development and to determine the hierarchical structure of branches with respect to the modular structure of the stem in response to intra‐ and inter‐shoot trophic competition.

Modelling the distribution of leaf nitrogen is central to specify photosynthetic parameters and simulate canopy photosynthesis using leaf gas exchange models. Nitrogen distribution depends both on soil nitrogen availability and within-canopy light distribution. We propose the use of a set of empirical relationships with measurable parameters to dynamically account for it. The model was assessed on alfalfa canopies under contrasting N nutrition levels. It proved able to predict nitrogen distribution and daily patterns of photosynthesis from leaf to whole canopy for a large range of situations. Abstract Modelling the spatial and temporal distribution of leaf nitrogen (N) is central to specify photosynthetic parameters and simulate canopy photosynthesis. Leaf photosynthetic parameters depend on both local light availability and whole-plant N status. The interaction between these two levels of integration has generally been modelled by assuming optimal canopy functioning, which is not supported by experiments. During this study, we examined how a set of empirical relationships with measurable parameters could be used instead to predict photosynthesis at the leaf and whole-canopy levels. The distribution of leaf N per unit area (Na) within the canopy was related to leaf light irradiance and to the nitrogen nutrition index (NNI), a whole-plant variable accounting for plant N status. Na was then used to determine the photosynthetic parameters of a leaf gas exchange model. The model was assessed on alfalfa canopies under contrasting N nutrition and with N2-fixing and non-fixing plants. Three experiments were carried out to parameterize the relationships between Na, leaf irradiance, NNI and photosynthetic parameters. An additional independent data set was used for model evaluation. The N distribution model showed that it was able to predict leaf N on the set of leaves tested. The Na at the top of the canopy appeared to be related linearly to the NNI, whereas the coefficient accounting for N allocation remained constant. Photosynthetic parameters were related linearly to Na irrespective of N nutrition and the N acquisition mode. Daily patterns of gas exchange were simulated accurately at the leaf scale. When integrated at the whole-canopy scale, the model predicted that raising N availability above an NNI of 1 did not result in increased net photosynthesis. Overall, the model proposed offered a solution for a dynamic coupling of leaf photosynthesis and canopy N distribution without requiring any optimal functioning hypothesis.