2014
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2014

2014

Liste des publications utilisant Stics pour 2014

  • Baey, C., Didier, A., Lemaire, S., Maupas, F., Cournede, P.H., 2014. Parametrization of five classical plant growth models applied to sugar beet and comparison of their predictive capacity on root yield and total biomass. Ecological Modelling 290, 11-20.
  • Bassu, S., Brisson, N., Durand, J.-L., Boote, K., Lizaso, J., Jones, J.W., Rosenzweig, C., Ruane, A.C., Adam, M., Baron, C., Basso, B., Biernath, C., Boogaard, H., Conijn, S., Corbeels, M., Deryng, D., De Sanctis, G., Gayler, S., Grassini, P., Hatfield, J.L., Hoek, S., Izaurralde, C., Jongschaap, R., Kemanian, A.R., Kersebaum, K.C., Kim, S.-H., Kumar, N.S., Makowski, D., Müller, C., Nendel, C., Priesack, E., Pravia, M.V., Sau, F., Shcherbak, I., Tao, F., Teixeira, E., Timlin, D., Waha, K., 2014. How do various maize crop models vary in their responses to climate change factors? Global Change Biology, n/a-n/a.
  • Bergez, J.E., Raynal, H., Launay, M., Beaudoin, N., Casellas, E., Caubel, J., Chabrier, P., Coucheney, E., Dury, J., Garcia de Cortazar-Atauri, I., Justes, E., Mary, B., Ripoche, D., Ruget, F., 2014. Evolution of the STICS crop model to tackle new environmental issues: New formalisms and integration in the modelling and simulation platform RECORD. Environmental Modelling & Software.
  • Bourgeois, C., Fradj, N., Jayet, P.-A., 2014. How Cost-Effective is a Mixed Policy Targeting the Management of Three Agricultural N-pollutants? Environmental Modeling & Assessment 19, 389-405.
  • Caubel, J., Launay, M., Garcia de Cortazar-Atauri, I., Ripoche, D., Huard, F., Buis, S., Brisson, N., 2014. A new integrated approach to assess the impacts of climate change on grapevine fungal diseases: the coupled MILA-STICS model. Journal International des Sciences de la Vigne et du Vin, 45-54.
  • Chen, Y.T., Cournede, P.H., 2014. Data assimilation to reduce uncertainty of crop model prediction Convolution Particle Filtering. Ecological Modelling 290, 165-177.
  • Colbach, N., Granger, S., Guyot, S.H.M., Mézière, D., 2014. A trait-based approach to explain weed species response to agricultural practices in a simulation study with a cropping system model. Agriculture, Ecosystems & Environment 183, 197-204.
  • Defossez, P., Richard, G., Keller, T., Adamiade, V., Govind, A., Mary, B., 2014. Modelling the impact of declining soil organic carbon on soil compaction: Application to a cultivated Eutric Cambisol with massive straw exportation for energy production in Northern France. Soil & Tillage Research 141, 44-54.
  • Dumont, B., Basso, B., Leemans, V., Bodson, B., Destain, J.-P., Destain, M.-F., 2014. Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions. Precision Agric, 1-24.
  • Dumont, B., Leemans, V., Ferrandis, S., Bodson, B., Destain, J.-P., Destain, M.-F., 2014. Assessing the potential of an algorithm based on mean climatic data to predict wheat yield. Precision Agric 15, 255-272.
  • Dumont, B., Leemans, V., Mansouri, M., Bodson, B., Destain, J.-P., Destain, M.-F., 2014. Parameter identification of the STICS crop model, using an accelerated formal MCMC approach. Environmental Modelling & Software 52, 121-135.
  • Ferrant, S., Gascoin, S., Veloso, A., Salmon-Monviola, J., Claverie, M., Rivalland, V., Dedieu, G., Demarez, V., Ceschia, E., Probst, J.L., Durand, P., Bustillo, V., 2014. Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration. Hydrology and Earth System Sciences 18, 5219-5237.
  • Jego, G., Chantigny, M., Pattey, E., Belanger, G., Rochette, P., Vanasse, A., Goyer, C., 2014. Improved snow-cover model for multi-annual simulations with the STICS crop model under cold, humid continental climates. Agricultural and Forest Meteorology 195, 38-51.
  • Khila, S.B., Douh, B., Mguidiche, A., Ruget, F., Mohsen, M., Boujelben, A., 2014. Application of STICS Model in Assessment of the Effects of Irrigation Practices and Soil Properties on Yield of a Durum Wheat (Triticum durum Desf.) Cultivar in the Irrigated Area of Oued Rmel in Tunisia. Annual Research & Review in Biology 4, 747-765.
  • Langevin, B., Génermont, S., Basset-Mens, C., Lardon, L., 2014. Simulation of field NH3 and N2O emissions from slurry spreading. Agronomy for Sustainable Development, 1-12.
  • Mansouri, M., Dumont, B., Leemans, V., Destain, M.-F., 2014. Bayesian methods for predicting LAI and soil water content. Precision Agric 15, 184-201.
  • McDowell, R.W., Moreau, P., Salmon-Monviola, J., Durand, P., Leterme, P., Merot, P., 2014. Contrasting the spatial management of nitrogen and phosphorus for improved water quality: Modelling studies in New Zealand and France. European Journal of Agronomy 57, 52-61.
  • Poch-Massegu, R., Jimenez-Martinez, J., Wallis, K.J., de Cartagena, F.R., Candela, L., 2014. Irrigation return flow and nitrate leaching under different crops and irrigation methods in Western Mediterranean weather conditions. Agricultural Water Management 134, 1-13.
  • Porter, C.H., Villalobos, C., Holzworth, D., Nelson, R., White, J.W., Athanasiadis, I.N., Janssen, S., Ripoche, D., Cufi, J., Raes, D., Zhang, M., Knapen, R., Sahajpal, R., Boote, K., Jones, J.W., 2014. Harmonization and translation of crop modeling data to ensure interoperability. Environmental Modelling & Software 62, 495-508.
  • Sansoulet, J., Pattey, E., Kröbel, R., Grant, B., Smith, W., Jégo, G., Desjardins, R.L., Tremblay, N., Tremblay, G., 2014. Comparing the performance of the STICS, DNDC, and DayCent models for predicting N uptake and biomass of spring wheat in Eastern Canada. Field Crops Research 156, 135-150.
  • Singh, A.K., Madramootoo, C.A., Goyal, M.K., Smith, D.L., 2014. Corn Yield Simulation Using the STICS Model under Varying Nitrogen Management and Climate-Change Scenarios. Journal of Irrigation and Drainage Engineering 140.
  • Strullu, L., Beaudoin, N., Garcia de Cortàzar Atauri, I., Mary, B., 2014. Simulation of biomass and nitrogen dynamics in perennial organs and shoots of Miscanthus×Giganteus using the STICS model. Bioenergy Research.
  • Talbot, G., Roux, S., Graves, A., Dupraz, C., Marrou, H., 2014. Relative yield decomposition: A method for understanding the behaviour of complex crop models. Environmental Modelling & Software 51, 136-148.
  • Valade, A., Ciais, P., Vuichard, N., Viovy, N., Caubel, A., Huth, N., Marin, F., Martine, J.F., 2014. Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values. Geoscientific Model Development 7, 1225-1245.
  • Valade, A., Vuichard, N., Ciais, P., Ruget, F., Viovy, N., Gabrielle, B., Huth, N., Martiné, J.-F., 2014. ORCHIDEE-STICS, a process-based model of sugarcane biomass production: calibration of model parameters governing phenology. Global Change Biology - Bioenergy 6, 606-620.
  • Valdés-Gómez, H., Gary, C., Brisson, N., Matus, F., 2014. Modelling indeterminate development, dry matter partitioning and the effect of nitrogen supply in tomato with the generic STICS crop–soil model. Scientia Horticulturae 175, 44-56.

Date de modification : 21 juin 2023 | Date de création : 18 novembre 2015 | Rédaction : Equipe Projet Stics