Search results for " Simulation"

showing 10 items of 4034 documents

Influence de l'apport d'amendements organiques sur les émissions de N2O et de N2 par les sols, au cours de la dénitrification, révélée par le traçage…

2006

International audience

[SDE] Environmental Sciences[ SDE ] Environmental Sciences[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation[SDE]Environmental Sciences[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputingMilieux_MISCELLANEOUS
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La gestion des betteraves adventices résistantes à un herbicide: une approche par simulation

2007

National audience; Les variétés de betteraves sucrières génétiquement modifiées (GM) résistantes à un herbicide sont, a priori, intéressantes dans des champs fortement infestés par la betterave adventice. Cependant, la montée à fleurs de ces betteraves GM peut entraîner l’apparition d’individus résistants, via la dispersion de pollen. Nous avons développé et utilisé le modèle GENESYS-Betterave pour simuler, à l’échelle d’une petite région agricole, l’impact des pratiques culturales sur la dispersion du transgène. Il permet d'identifier des stratégies pour contrôler les adventices et limiter l'apparition de populations résistantes en zone de production de betterave sucrière. L’utilisation de…

[SDE] Environmental Scienceshttp://aims.fao.org/aos/agrovoc/c_24242http://aims.fao.org/aos/agrovoc/c_28744[SDV]Life Sciences [q-bio]Évaluation du risquehttp://aims.fao.org/aos/agrovoc/c_5728H60 - Mauvaises herbes et désherbageFlux de gènesPollution par l'agriculture[SHS]Humanities and Social SciencesMéthode de luttehttp://aims.fao.org/aos/agrovoc/c_33990http://aims.fao.org/aos/agrovoc/c_34285http://aims.fao.org/aos/agrovoc/c_37331http://aims.fao.org/aos/agrovoc/c_2018Variétéhttp://aims.fao.org/aos/agrovoc/c_3566http://aims.fao.org/aos/agrovoc/c_8157http://aims.fao.org/aos/agrovoc/c_37932Résistance aux pesticidesSaccharum officinarumU10 - Informatique mathématiques et statistiquesExpérimentation au champhttp://aims.fao.org/aos/agrovoc/c_6727Modèle de simulationhttp://aims.fao.org/aos/agrovoc/c_25427[SDV] Life Sciences [q-bio]Pratique culturalehttp://aims.fao.org/aos/agrovoc/c_8347Organisme génétiquement modifié[SDE]Environmental SciencesSystème de culture[SHS] Humanities and Social SciencesHerbicidehttp://aims.fao.org/aos/agrovoc/c_1971P02 - PollutionMauvaise herbe
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DEXi Fusariose de l’ail : Prototype d’outil d’évaluation multicritère en vue de la maitrise du risque de développement de la fusariose de l’ail (Fusa…

2022

[SDE] Environmental Sciencessystèmes de cultureFusariose de l'ailOutil d'aide à la décisioncontexte pédoclimatique[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulationleviers agronomiques[SDV.BV.PEP] Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy
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Modelling the optical properties of fresh biomass burning aerosol produced in a smoke chamber: results from the EFEU campaign

2007

A better characterisation of the optical properties of biomass burning aerosol as a function of the burning conditions is required in order to quantify their effects on climate and atmospheric chemistry. Controlled laboratory combustion experiments with different fuel types were carried out at the combustion facility of the Max Planck Institute for Chemistry (Mainz, Germany) as part of the "Impact of Vegetation Fires on the Composition and Circulation of the Atmosphere" (EFEU) project. The combustion conditions were monitored with concomitant CO<sub>2</sub> and CO measurements. The mass scattering efficiencies of 8.9±0.2 m<sup>2</sup> g<sup&gt…

[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphereoptical propertiesSmokeAtmospheric Science[SDU.OCEAN] Sciences of the Universe [physics]/Ocean AtmosphereChemistryCombustionAtmospheric scienceslcsh:QC1-999AerosolDilutionlcsh:ChemistryAtmospherelcsh:QD1-999complex refractive indexEnvironmental chemistryAtmospheric chemistryParticle-size distributionBiomass burning aerosolMie simulationsAbsorption (electromagnetic radiation)number size distributionlcsh:PhysicsAtmospheric Chemistry and Physics
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Changes in the frequency of the Weather Regimes over the Euro-Atlantic and Mediterranean sector and their relation to the anomalous temperatures over…

2013

19 pages; International audience; An exercise has been carried out to assess to what extent the Euro-Atlantic Weather Regimes (WR),described from the ERA-interim Reanalysis in the summer season, projects onto a pool of AGCMAMIPsimulations in which sea surface temperatures (SST) are prescribed from observations.Although the model simulations present some biases in the spatial structure and seasonality of WRs,exhibiting also less variability, they are able to capture main WR over the region in summer season:+Middle East –Middle East, +NAO, -NAO. WR paradigm is used to quantify changes in theatmosphere under warmer/colder than normal conditions over the Mediterranean Sea. To addressthis proble…

[SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/ClimatologyAGCM-AMIP simulationfrequency of occurrenceMediterranean Sea[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/ClimatologyWeather Regimes
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Typology of exogenous organic matters based on chemical and biochemical composition to predict potential nitrogen mineralization

2010

Our aim was to develop a typology predicting potential N availability of exogenous organic matters (EOMs) in soil based on their chemical characteristics. A database of 273 EOMs was constructed including analytical data of biochemical fractionation, organic C and N, and results of N mineralization during incubation of soil–EOM mixtures in controlled conditions. Multiple factor analysis and hierarchical classification were performed to gather EOMs with similar composition and N mineralization behavior. A typology was then defined using composition criteria to predict potential N mineralization. Six classes of EOM potential N mineralization in soil were defined, from high potential N minerali…

[SDV.BIO]Life Sciences [q-bio]/Biotechnologygenetic structures010501 environmental sciences01 natural sciencesMinéralisationBiochemical compositionOrganic ChemicalsWaste Management and DisposalHigh potentialhttp://aims.fao.org/aos/agrovoc/c_35657chemistry.chemical_classificationMineralsChemistry04 agricultural and veterinary sciencesGeneral MedicineComposition chimiqueClassificationhierarchical classificationDisponibilité d'élément nutritifCycle de l'azoteEnvironmental chemistryhttp://aims.fao.org/aos/agrovoc/c_5193http://aims.fao.org/aos/agrovoc/c_1794AlgorithmsP33 - Chimie et physique du solBiochemical fractionationEnvironmental EngineeringNitrogenhttp://aims.fao.org/aos/agrovoc/c_7170Mineralogybiochemical fractionationBioengineeringhttp://aims.fao.org/aos/agrovoc/c_27938FractionationTeneur en azoten mineralizationMatière organique du solhttp://aims.fao.org/aos/agrovoc/c_5268Fertilité du solMultiple factor analysisOrganic matterComputer SimulationNitrogen cycle0105 earth and related environmental sciencesRenewable Energy Sustainability and the EnvironmentP35 - Fertilité du sol[ SDV.BIO ] Life Sciences [q-bio]/BiotechnologyMineralization (soil science)eye diseasesAmendement organiqueModels Chemical040103 agronomy & agriculture0401 agriculture forestry and fisheriessense organsexogenous organic mattertypologyhttp://aims.fao.org/aos/agrovoc/c_12965http://aims.fao.org/aos/agrovoc/c_1653http://aims.fao.org/aos/agrovoc/c_15999F04 - Fertilisation
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How optical density measurements on artificially reconstituted soil ecosystems show the validity of the competitive exclusion principle

2010

aeres : C-COM; International audience

[SDV.EE]Life Sciences [q-bio]/Ecology environment[SDV.EE] Life Sciences [q-bio]/Ecology environment[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH][ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH][INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputingMilieux_MISCELLANEOUS
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The growth of soil bacteria revisited

2010

aeres : C-COM; International audience

[SDV.EE]Life Sciences [q-bio]/Ecology environment[SDV.EE] Life Sciences [q-bio]/Ecology environment[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH][ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH][INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputingMilieux_MISCELLANEOUS
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Modélisation de paysages agricoles pour la simulation et l'analyse de processus

2017

L’objet de ce colloque est de partager des connaissances, expériences et outils autour de la modélisation des paysages agricoles, de leur structure et de leur dynamique en considérant la modélisation de la structure physique du paysage agricole et celle des processus socio-techniques qui gouvernent les usages des éléments le constituant (parcelles, fossés, etc.). Par ailleurs, les paysages agricoles sont le support de processus biotiques et abiotiques spatialisés. Les processus biotiques incluent par exemple les dynamiques d’organismes d’importance en agriculture – ravageurs et auxiliaires – ou contribuant à la biodiversité patrimoniale ou ordinaire. Les processus abiotiques incluent par ex…

[SDV.EE]Life Sciences [q-bio]/Ecology environment[STAT.AP]Statistics [stat]/Applications [stat.AP]partage de connaissance[SDV]Life Sciences [q-bio]outildynamique de paysagemodèle[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation[SDE.ES]Environmental Sciences/Environmental and Societyvariable spatiale[SHS]Humanities and Social Sciences[SDE.BE] Environmental Sciences/Biodiversity and Ecology[SDV.EE] Life Sciences [q-bio]/Ecology environment[STAT.AP] Statistics [stat]/Applications [stat.AP][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[INFO]Computer Science [cs][INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[SDE.ES] Environmental Sciences/Environmental and Society[MATH]Mathematics [math][SDE.BE]Environmental Sciences/Biodiversity and Ecologyprocessus socio-techniquepaysage agricolemodélisation
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Soilμ3d project: emergent properties of soil microbial functions from 3d modelling and spatial descriptors of pore scale heterogeneity

2021

International audience; The reduction of greenhouse gas emissions by improving the efficiency of agricultural systems through robust ecologically-based management practices represents the most important challenge facing agriculture. Models are needed to evaluate the effects of soil properties, climate, and agricultural management practices on soil carbon and on the nitrogen transformations responsible for GHG emissions. Models of Carbon and nitrogen cycles in soils need improvements so they can provide more accurate and robust predictions. They use empirical functions which account for the different environmental factors that affect microbial functions. However, these types of function have…

[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy[SDE.BE] Environmental Sciences/Biodiversity and Ecology[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[SDE.BE]Environmental Sciences/Biodiversity and Ecology[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
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