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|Title:||An extensible, multi-model software library for simulating crop growth and development|
|Authors:||CONFALONIERI Roberto; BREGAGLIO Simone; STELLA T.; NEGRINI G; ACUTIS Marco; DONATELLI Marcello|
|Citation:||ENVIRONMENTAL MODELLING & SOFTWARE|
|Publisher:||ELSEVIER SCI LTD|
|Type:||Articles in periodicals and books|
|Abstract:||The availability of different crop models and of a variety of techniques to evaluate their behaviour is leading to a change of paradigm in crop models use. Modellers are now looking beyond groups of users and developers built around a specific model, and international initiatives focusing on model improvement based on inter-comparison and knowledge sharing are recently catalysing the attention of the international community. Also, the analysis under environmental conditions of no adaptation by crops, such as the ones of climate change scenarios, demand for extension of crop models to account for extreme events, diseases and pests impact, difficult to implement into legacy code. The Crop Models Library (CropML) is a modelling framework-independent MS .NET software component where different known (e.g., WOFOST, CropSyst, WARM) and new modelling solutions for crop growth and development are implemented following a fine granularity. A software architecture developed targeting reuse and composition of model units as key requirements, already used for several other model libraries in the biophysical domain, was adopted. CropML can be autonomously extended by third parties and is distributed at no cost with a software development kit, including documentation of code and algorithms, and sample applications. CropML provides modellers with an environment enabling the evolution of existing approaches, and the possibility of analysing and comparing diverse modelling solutions. As an example of the extensibility of the framework, a new generation of SUCROS-type models has been developed and included in the component. A comparison of the standard and of the new version of the WOFOST model, made using data from rice field experiments, revealed an increase in accuracy and robustness with less than half of the parameters used by the standard version of the model. These results support the concept that high-level technology for model formalization can favour the development of the models, hence broadening from a pure technological aspect to knowledge sharing and development.|
|JRC Directorate:||Sustainable Resources|
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