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Multi-wheat-model ensemble responses to interannual climate variability, , , , , , , , , and 38 other author(s). Environmental Modelling & Software, (July 2016)Evaluating methods to simulate crop rotations for climate impact assessments - A case study on the Canterbury plains of New Zealand., , , , and . Environ. Model. Softw., (2015)Estimating model prediction error: Should you treat predictions as fixed or random?, , , , , , , and . Environ. Model. Softw., (2016)Simulating canopy temperature for modelling heat stress in cereals., , , , , , , , and . Environ. Model. Softw., (2016)Practical use of components in agro-ecological simulation., , , , , , and . SCSC, page 17. Simulation Councils, Inc., (2007)Heat stress in cereals: Mechanisms and modelling, , , , and . European Journal of Agronomy, (2015)Designing future barley ideotypes using a crop model ensemble, , , , , , , , , and 11 other author(s). European Journal of Agronomy, (2017)Comparison of Machine Learning Methods for Predicting Winter Wheat Yield in Germany., , , , , , , and . CoRR, (2021)FAIRagro: Ein Konsortium in der Nationalen Forschungsdateninfrastruktur (NFDI) für Forschungsdaten in der Agrosystemforschung., , , , , , , , , and 19 other author(s). Inform. Spektrum, 46 (1): 24-35 (February 2023)Defining assessment projects and scenarios for policy support: Use of ontology in Integrated Assessment and Modelling., , , , , , , , , and 3 other author(s). Environ. Model. Softw., 24 (12): 1491-1500 (2009)