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.
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.
• 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 × 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 δ13C 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.
The estimation of repair costs for car damage is a critical yet challenging task for insurance companies and repair shops. Accurate and the rapid predictions are essential for providing reliable cost ...estimates to customers. Traditional methods in this domain face multiple challenges, including manual processes and inaccuracies in repair cost estimation, as outlined in our article.
This paper introduces a novel approach that combines regression models with ontology reasoning to enhance the accuracy of car damage repair cost predictions. An Ontology for Car Damage (OCD)11industryportal.enit.fr/ontologies/OCD.,22github.com/OntologyCarDamage/OCD. has been developed, which is meticulously structured and populated using Named Entity Recognition (NER) and Relation Extraction (RE) techniques. This ontology provides a comprehensive framework for organizing and understanding the complex domain of car damage, capturing essential semantic relationships and variables that significantly influence repair costs. By integrating OCD with seven regression models, such as Random Forest and Decision Tree, we have proposed a hybrid methodology that leverages both structured data and semantic understanding. Our approach not only accounts for typical variables such as the type and severity of damage, and labor costs but also identifies novel features through the use of SWRL (Semantic Web Rule Language) rules, enhancing the model’s predictive capabilities.
The performance of our models was evaluated using a substantial real-world dataset comprising over 300,000 records. This evaluation used metrics such as mean absolute error (MAE), root mean squared error (RMSE), and R-squared. The results indicate that our hybrid approach, which incorporates ontology reasoning, significantly outperforms traditional regression models.
The Random Forest model, especially when combined with the OCD ontology, showcased superior performance, exhibiting a minimal average deviation from the actual repair costs and achieving a low MAE.
This study’s findings demonstrate the potential of combining ontology reasoning with machine learning techniques for precise cost prediction in the automotive repair industry. Our methodology offers a robust tool for insurance companies and repair shops to generate more accurate, reliable, and automated cost estimates, ultimately benefiting both businesses and customers.
•Development of an Ontology for Car Damage.•Use information extraction to populate the ontology and integrate SWRL rules.•Combining ontology and regression models for accurate cost predictions.•Validate cost prediction with a comparative analysis using real-world data.
A geometrical canopy model describing radiation absorption (Riou et al. 1989, Agronomie 9, 441–450) and partitioning between grapevines (Vitis vinifera L.) and soil was coupled to a soil water ...balance routine describing a bilinear change in relative transpiration rate as a function of the fraction of soil transpirable water (FTSW). The model was amended to account for changes in soil evaporation after precipitation events and subsequent dry-down of the top soil layer. It was tested on two experimental vineyards in the Alsace region, France, varying in soil type, water-holding capacity and rooting depth. Simulations were run over four seasons (1992–1993, 1995–1996) and compared with measurements of FTSW conducted with a neutron probe. For three out of four years, the model simulated the dynamics in seasonal soil water balance adequately. For the 1996 season soil water content was overestimated for one vineyard and underestimated for the other. Sensitivity analyses revealed that the model responded strongly to changes in canopy parameters, and that soil evaporation was particularly sensitive to water storage of the top soil layer after rainfall. We found a close relationship between field-average soil water storage and pre-dawn water potential, a relationship which could be used to couple physiological models of growth and / or photosynthesis to the soil water dynamics.
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.
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.
Titanium minerals are classically considered to be very resistant to weathering in soils. Consequently, variations of titanium concentrations within the soils were used to estimate rates of ...weathering of parent material. Mobility of Ti was studied in an Amazonian ferralsol using a large set of techniques. Chemical and mineralogical studies of Ti distribution in the soil profile showed that weathering of Ti minerals follows the mineral sequence: ilmenite, pseudorutile, rutile and anatase. This weathering leads to absolute Ti losses on the profile scale. Mineral bags were located at different depths within the top soil, and removed after 6, 12, 18 months in the soil. In all bags the presence of newly generated anatase was recorded after the exposure periods, showing the rapidity of the processes. The vegetation recycles a significant quantity of Ti, increasing Ti mobility in soils. These results indicate that Ti can be mobile under certain conditions and thus should not always be used to estimate weathering rates.
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