| Poster number | Presenter | Title |
| S6-P.01 | Llorenç Cabrera-Bosquet | Enabling data exchange between crop growth models and PHIS information system for phenomics through ICASA and AgMIP data standards and tools |
| S6-P.02 | Nándor Fodor | Database Sensitivity of the Biome-BGCMAg Biogeochemical Model |
| S6-P.03 | Clément Saint Cast | An online database of plant and crop computational models |
| S6-P.04 | Serge ZAKA | Using open weather data for crop modeling? It is possible! |
| S6-P.05 | Marco Carozzi | "Evaluation of mitigation practices to reduce N2O and increase soil C |
| S6-P.06 | Ranju Chapagain | Historical and current approaches to decompose uncertainty in crop model predictions |
| S6-P.07 | Mathias Christina | Comparison of sugarcane STICS model calibrations to simulate growth response to climate variability |
| S6-P.08 | Elsa Coucheney | Sensitivity of soil-crop models to spatial variation in soil-management interactions across Southern Sweden |
| S6-P.09 | Willem Coudron | Identifiability analysis to improve experimental design for crop model calibration |
| S6-P.10 | Gerrit Hoogenboom | Comparison of three calibration methods for modeling rice phenology |
| S6-P.11 | Asha Karunaratne | Calibration of the phenology sub-model of APSIM-Oryza and validation for rice varieties: going beyond goodness of fit |
| S6-P.12 | Amit Kumar Srivastava | Impact of different sets of climate variables on regional Maize yield simulations- A case study in Sub-Saharan Africa |
| S6-P.13 | Nicolas Beaudoin | Associated tools for STICS testing and development towards agro-ecology, mitigation and adaptation to climate change |
| S6-P.14 | Christian Folberth | Combining crop modelling and machine learning for rapid provision of crop yield estimates and externalities |
| S6-P.15 | Joe Gallear | A machine learning pipeline for climate impacts: crop models versus deep learners |
| S6-P.16 | Gerrit Hoogenboom | Tools to Support Computational Crop Model Analysis and Comparison |
| S6-P.17 | Kwang Soo Kim | Application of a gridded crop growth simulation support system to a Raspberry Pi cluster computer |
| S6-P.18 | Cyrille Midingoyi | CyML language and transpiler: Re-using biophysical processes in crop growth models across multiple platforms |
| S6-P.19 | Alfredo Rodríguez | Computationally-intensive crop model simulations using serverless computing for Mars colonization |
| S6-P.20 | Tibor Marton | Exploit the Panel: Combining Agronomic Weather Measures and Year Effect in a Spatial Study |
| S6-P.21 | Alfredo Rodríguez | Using spatial data for running and validating process-based models. A case study for a Spanish province |