HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation


Poster number Presenter Title
S1-P.01 Lethicia Magno Modelling Memory : do crop models need to become nostalgic?
S1-P.02 Danaë Rozendaal Crop growth models for tropical perennials: current advances and remaining challenges
S1-P.03 Yan Zhu Current rice models underestimate yield losses by short-term heat stresses
S1-P.04 A L C De Silva Variation in photosynthesis and transpiration efficiency of sugarcane at elevated atmospheric CO2 and temperature
S1-P.05 Kendall DeJonge Using crop coefficients and standardized evapotranspiration methods to evaluate crop model behavior
S1-P.06 Jean-Louis Durand Phenology of grasslands: a new model
S1-P.07 Florian Heinlein Modelling the transpiration of single maize plants using an explicit xylem flux model
S1-P.08 Panu Korhonen Root descriptions of crop simulation models - do they serve studies of climate-smart agriculture?
S1-P.09 Mukhtar Ahmed Modeling phenological responses of table grape cultivars
S1-P.10 Fety Andrianasolo Developing a mechanistic foliar stage model adapted to wheat diseases decision tools
S1-P.11 Fety Andrianasolo Predicting wheat yield and protein content at the plot scale with machine-learning and mechanistic models
S1-P.12 Ioannis Droutsas New modelling methodology for improving crop model performance under stress conditions
S1-P.13 Sylvain Edouard Analysis and modeling (STICS / L-egume) of crop growth under shading conditions in Agri-PV context
S1-P.14 Deborah Gaso Assimilating leaf area index into a simple crop model to predict soybean yield and maximum root depth at field scale
S1-P.15 Armen Kemanian What can crop modelers learn from machine learning models about corn, sorghum and soybean?
S1-P.16 Christoph Müller Potential yield simulated by Global Gridded Crop Models: what explains their difference
S1-P.17 Chinaza Onwuchekwa-Henry Potential for using low-cost spectral sensors to predict yield in small-scale rice fields in northwest Cambodia
S1-P.18 Simona Bassu Potential maize yields in a Mediterranean environment depend on conditions around flowering
S1-P.19 Rafael Battisti Performance of CSM-DSSAT-CROPGRO model for soybean plant density in low latitude in Brazil
S1-P.20 Martin Bednařík Potential and challenges of long term uninterrupted field crop rotations modelling: case study from Czech Republic
S1-P.21 Kurt-Christian Kersebaum From point to field scale: How consistent are agro-ecosystem models in terms of changes in soil texture?
S1-P.22 Bruce Kimball Prediction of Evapotranspiration and Yields of Maize: An Inter-comparison among 29 Maize Models and Future Plans
S1-P.23 Kritika Kothari First Soybean Multi-model Sensitivity Analysis to CO2, Temperature, Water, and Nitrogen
S1-P.24 Crystele Leauthaud Modelling floodplain grasslands to explore the impact of changing hydrological conditions on vegetation productivity
S1-P.25 Bing Liu Comparison of wheat simulation models for impacts of extreme temperature stress on grain quality
S1-P.26 Eva Pohanková Modelling of drought stress in field crops by crop growth model DAISY
S1-P.27 Elodie Ruelle Predicting grass growth: The MoSt GG model
S1-P.28 Hossein Zare Comparison of DSSAT wheat models performances with different regions and cultivars
S1-P.29 Mukhtar Ahmed APSIM Next Generation to Model Red Clover Under Nordic Climate
S1-P.30 Ahmad Banakar Extraction of FAO Growth Model in a Fuzzy Control Hydroponic Greenhouse
S1-P.31 Yuji Masutomi Development of a global crop growth simulation model for simulating long-term trends in rice yields: Global MATCRO-Rice
S1-P.32 João Vasco Silva Winter wheat development and growth in The Netherlands: Using a detailed field trial to update crop parameters in WOFOST
S1-P.33 Tamara ten Den The effect of potato cultivar differences on parameters in WOFOST
S1-P.34 Jingbo Zhen Modelling water and carbon balances of date palm trees under different salinity conditions
S1-P.35 Laura Delhez TADA, a mechanistic model for carbon, nitrogen and water cycle in cropland and grassland ecosystems