Research output per year
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Cyrille Ahmed Midingoyi, Christophe Pradal*, Andreas Enders, Davide Fumagalli, Hélène Raynal, Marcello Donatelli, Ioannis N. Athanasiadis, Cheryl Porter, Gerrit Hoogenboom, Dean Holzworth, Frédérick Garcia, Peter Thorburn, Pierre Martre*
Research output: Contribution to journal › Article › Academic › peer-review
Process-based crop models are popular tools to analyze and simulate the response of agricultural systems to weather, agronomic, or genetic factors. They are often developed in modeling platforms to ensure their future extension and to couple different crop models with a soil model and a crop management event scheduler. The intercomparison and improvement of crop simulation models is difficult due to the lack of efficient methods for exchanging biophysical processes between modeling platforms. We developed Crop2ML, a modeling framework that enables the description and the assembly of crop model components independently of the formalism of modeling platforms and the exchange of components between platforms. Crop2ML is based on a declarative architecture of modular model representation to describe the biophysical processes and their transformation to model components that conform to crop modeling platforms. Here, we present Crop2ML framework and describe the mechanisms of import and export between Crop2ML and modeling platforms.
Original language | English |
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Article number | 105055 |
Journal | Environmental Modelling and Software |
Volume | 142 |
Early online date | 30 Apr 2021 |
DOIs | |
Publication status | Published - Aug 2021 |
Research output: Non-textual form › Software