Reference : Simulation de la croissance du blé à l’aide de modèles écophysiologiques : Synthèse bibl...
Scientific journals : Article
Life sciences : Agriculture & agronomy
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/129589
Simulation de la croissance du blé à l’aide de modèles écophysiologiques : Synthèse bibliographique des méthodes, potentialités et limitations.
English
[en] Wheat growth simulation using crop models: A review of the methods, potential and limitations.
Dumont, Benjamin mailto [Université de Liège - ULg > Sciences et technologie de l'environnement > Mécanique et construction >]
Vancutsem, Françoise [Université de Liège - ULg > Sciences agronomiques > Phytotechnie des régions tempérées >]
Seutin, Benoit [Université de Liège - ULg > Sciences agronomiques > Phytotechnie des régions tempérées >]
Bodson, Bernard mailto [Université de Liège - ULg > Sciences agronomiques > Phytotechnie des régions tempérées >]
Destain, Jean-Pierre mailto [Université de Liège - ULg > Sciences agronomiques > Phytotechnie des régions tempérées >]
Destain, Marie-France mailto [Université de Liège - ULg > Sciences et technologie de l'environnement > Mécanique et construction >]
2012
Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE]
Presses Agronomiques de Gembloux
16
3
376-386
Yes (verified by ORBi)
International
1370-6233
1780-4507
Gembloux
Belgique
[en] Crop model ; Wheat ; Parameter estimation
[en] Crop models describe the growth and development of a crop interacting with its surrounding agro-environmental conditions (soil, climate and close conditions of the plant). However, the implementation of such models remains difficult because of the high number of explanatory variables and parameters. It often happens that important discrepancies appear between measured and simulated values. This article aims to highlight the different sources of uncertainty related to the use of crop models, as well as the actual methods that allow to compensate or, at least, to consider these sources of error during the model result analysis.
This article presents a literature review that firstly synthetises the general mathematical structure of crop models. The main criteria for evaluating crop models are then described. Finally, several methods used for improving models are given. Parameter estimation methods, including frequentist and Bayesian approaches, are presented and data assimilation methods are reviewed.
DGO-3
Suivi en temps réel de l’environnement d’une parcelle agricole par un réseau de micro-capteurs en vue d’optimiser l’apport en engrais azotés
Researchers ; Students ; General public
http://hdl.handle.net/2268/129589

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