A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth
The process of crop modelling to develop operational software requires different skills, from conceptualization of the biophysical system to computer programming, involving three main scientific disciplines: agronomy, mathematics, and software engineering. Model building implies transforming a conceptual model into sets of mathematical equations and then translating these equations into a computer program. Although recent crop modelling frameworks can technically support model building, the modelling process is not always well documented and difficult to repeat. The focus of this paper is therefore on developing and documenting an approach to re-assemble crop models, i.e. develop a new model from an existing one, using a crop modelling framework and crop physiological knowledge. Modifications to an initial crop model were classified according to three categories: (i) changes in parameter values, (ii) changes in equations, and (iii) changes in overall model structure. We illustrate the approach with a case study transforming a wheat crop model into a pea crop model. We discuss the role of each actor in the process to document diverse uncertainties related to the model (i.e. contextual situation, data, structure), and the general applicability of the approach for different crop modelling frameworks. We conclude that the use of our approach to re-assemble a crop model within a modelling framework facilitates integration of different disciplines around a modelling objective, and facilitates creating transparent and reproducible models.
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Subjects: | U10 - Informatique, mathématiques et statistiques, F62 - Physiologie végétale - Croissance et développement, U30 - Méthodes de recherche, modélisation des cultures, modèle mathématique, logiciel, croissance, physiologie végétale, conception, Triticum durum, Pisum sativum, http://aims.fao.org/aos/agrovoc/c_9000024, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_24008, http://aims.fao.org/aos/agrovoc/c_3394, http://aims.fao.org/aos/agrovoc/c_25189, http://aims.fao.org/aos/agrovoc/c_2208, http://aims.fao.org/aos/agrovoc/c_7955, http://aims.fao.org/aos/agrovoc/c_5933, http://aims.fao.org/aos/agrovoc/c_4819, http://aims.fao.org/aos/agrovoc/c_4188, http://aims.fao.org/aos/agrovoc/c_3081, |
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dig-cirad-fr-5667852024-12-18T20:32:23Z http://agritrop.cirad.fr/566785/ http://agritrop.cirad.fr/566785/ A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth. Adam Myriam, Wery Jacques, Leffelaar Peter A., Ewert Franck, Corbeels Marc, Van Keulen Herman. 2013. Ecological Modelling, 250 : 258-268.https://doi.org/10.1016/j.ecolmodel.2012.10.012 <https://doi.org/10.1016/j.ecolmodel.2012.10.012> A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth Adam, Myriam Wery, Jacques Leffelaar, Peter A. Ewert, Franck Corbeels, Marc Van Keulen, Herman eng 2013 Elsevier Ecological Modelling U10 - Informatique, mathématiques et statistiques F62 - Physiologie végétale - Croissance et développement U30 - Méthodes de recherche modélisation des cultures modèle mathématique logiciel croissance physiologie végétale conception Triticum durum Pisum sativum http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_24008 http://aims.fao.org/aos/agrovoc/c_3394 http://aims.fao.org/aos/agrovoc/c_25189 http://aims.fao.org/aos/agrovoc/c_2208 http://aims.fao.org/aos/agrovoc/c_7955 http://aims.fao.org/aos/agrovoc/c_5933 Midi-Pyrénées Languedoc-Roussillon France http://aims.fao.org/aos/agrovoc/c_4819 http://aims.fao.org/aos/agrovoc/c_4188 http://aims.fao.org/aos/agrovoc/c_3081 The process of crop modelling to develop operational software requires different skills, from conceptualization of the biophysical system to computer programming, involving three main scientific disciplines: agronomy, mathematics, and software engineering. Model building implies transforming a conceptual model into sets of mathematical equations and then translating these equations into a computer program. Although recent crop modelling frameworks can technically support model building, the modelling process is not always well documented and difficult to repeat. The focus of this paper is therefore on developing and documenting an approach to re-assemble crop models, i.e. develop a new model from an existing one, using a crop modelling framework and crop physiological knowledge. Modifications to an initial crop model were classified according to three categories: (i) changes in parameter values, (ii) changes in equations, and (iii) changes in overall model structure. We illustrate the approach with a case study transforming a wheat crop model into a pea crop model. We discuss the role of each actor in the process to document diverse uncertainties related to the model (i.e. contextual situation, data, structure), and the general applicability of the approach for different crop modelling frameworks. We conclude that the use of our approach to re-assemble a crop model within a modelling framework facilitates integration of different disciplines around a modelling objective, and facilitates creating transparent and reproducible models. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/566785/1/document_566785.pdf application/pdf Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1016/j.ecolmodel.2012.10.012 10.1016/j.ecolmodel.2012.10.012 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolmodel.2012.10.012 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1016/j.ecolmodel.2012.10.012 |
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U10 - Informatique, mathématiques et statistiques F62 - Physiologie végétale - Croissance et développement U30 - Méthodes de recherche modélisation des cultures modèle mathématique logiciel croissance physiologie végétale conception Triticum durum Pisum sativum http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_24008 http://aims.fao.org/aos/agrovoc/c_3394 http://aims.fao.org/aos/agrovoc/c_25189 http://aims.fao.org/aos/agrovoc/c_2208 http://aims.fao.org/aos/agrovoc/c_7955 http://aims.fao.org/aos/agrovoc/c_5933 http://aims.fao.org/aos/agrovoc/c_4819 http://aims.fao.org/aos/agrovoc/c_4188 http://aims.fao.org/aos/agrovoc/c_3081 U10 - Informatique, mathématiques et statistiques F62 - Physiologie végétale - Croissance et développement U30 - Méthodes de recherche modélisation des cultures modèle mathématique logiciel croissance physiologie végétale conception Triticum durum Pisum sativum http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_24008 http://aims.fao.org/aos/agrovoc/c_3394 http://aims.fao.org/aos/agrovoc/c_25189 http://aims.fao.org/aos/agrovoc/c_2208 http://aims.fao.org/aos/agrovoc/c_7955 http://aims.fao.org/aos/agrovoc/c_5933 http://aims.fao.org/aos/agrovoc/c_4819 http://aims.fao.org/aos/agrovoc/c_4188 http://aims.fao.org/aos/agrovoc/c_3081 |
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U10 - Informatique, mathématiques et statistiques F62 - Physiologie végétale - Croissance et développement U30 - Méthodes de recherche modélisation des cultures modèle mathématique logiciel croissance physiologie végétale conception Triticum durum Pisum sativum http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_24008 http://aims.fao.org/aos/agrovoc/c_3394 http://aims.fao.org/aos/agrovoc/c_25189 http://aims.fao.org/aos/agrovoc/c_2208 http://aims.fao.org/aos/agrovoc/c_7955 http://aims.fao.org/aos/agrovoc/c_5933 http://aims.fao.org/aos/agrovoc/c_4819 http://aims.fao.org/aos/agrovoc/c_4188 http://aims.fao.org/aos/agrovoc/c_3081 U10 - Informatique, mathématiques et statistiques F62 - Physiologie végétale - Croissance et développement U30 - Méthodes de recherche modélisation des cultures modèle mathématique logiciel croissance physiologie végétale conception Triticum durum Pisum sativum http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_24008 http://aims.fao.org/aos/agrovoc/c_3394 http://aims.fao.org/aos/agrovoc/c_25189 http://aims.fao.org/aos/agrovoc/c_2208 http://aims.fao.org/aos/agrovoc/c_7955 http://aims.fao.org/aos/agrovoc/c_5933 http://aims.fao.org/aos/agrovoc/c_4819 http://aims.fao.org/aos/agrovoc/c_4188 http://aims.fao.org/aos/agrovoc/c_3081 Adam, Myriam Wery, Jacques Leffelaar, Peter A. Ewert, Franck Corbeels, Marc Van Keulen, Herman A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth |
description |
The process of crop modelling to develop operational software requires different skills, from conceptualization of the biophysical system to computer programming, involving three main scientific disciplines: agronomy, mathematics, and software engineering. Model building implies transforming a conceptual model into sets of mathematical equations and then translating these equations into a computer program. Although recent crop modelling frameworks can technically support model building, the modelling process is not always well documented and difficult to repeat. The focus of this paper is therefore on developing and documenting an approach to re-assemble crop models, i.e. develop a new model from an existing one, using a crop modelling framework and crop physiological knowledge. Modifications to an initial crop model were classified according to three categories: (i) changes in parameter values, (ii) changes in equations, and (iii) changes in overall model structure. We illustrate the approach with a case study transforming a wheat crop model into a pea crop model. We discuss the role of each actor in the process to document diverse uncertainties related to the model (i.e. contextual situation, data, structure), and the general applicability of the approach for different crop modelling frameworks. We conclude that the use of our approach to re-assemble a crop model within a modelling framework facilitates integration of different disciplines around a modelling objective, and facilitates creating transparent and reproducible models. |
format |
article |
topic_facet |
U10 - Informatique, mathématiques et statistiques F62 - Physiologie végétale - Croissance et développement U30 - Méthodes de recherche modélisation des cultures modèle mathématique logiciel croissance physiologie végétale conception Triticum durum Pisum sativum http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_24008 http://aims.fao.org/aos/agrovoc/c_3394 http://aims.fao.org/aos/agrovoc/c_25189 http://aims.fao.org/aos/agrovoc/c_2208 http://aims.fao.org/aos/agrovoc/c_7955 http://aims.fao.org/aos/agrovoc/c_5933 http://aims.fao.org/aos/agrovoc/c_4819 http://aims.fao.org/aos/agrovoc/c_4188 http://aims.fao.org/aos/agrovoc/c_3081 |
author |
Adam, Myriam Wery, Jacques Leffelaar, Peter A. Ewert, Franck Corbeels, Marc Van Keulen, Herman |
author_facet |
Adam, Myriam Wery, Jacques Leffelaar, Peter A. Ewert, Franck Corbeels, Marc Van Keulen, Herman |
author_sort |
Adam, Myriam |
title |
A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth |
title_short |
A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth |
title_full |
A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth |
title_fullStr |
A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth |
title_full_unstemmed |
A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth |
title_sort |
systematic approach for re-assembly of crop models: an example to simulate pea growth from wheat growth |
publisher |
Elsevier |
url |
http://agritrop.cirad.fr/566785/ http://agritrop.cirad.fr/566785/1/document_566785.pdf |
work_keys_str_mv |
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1819042658766553088 |