Some Parameter Estimation Issues in Functional-Structural Plant Modelling

P.-H. Cournède; V. Letort; A. Mathieu; M. Z. Kang; S. Lemaire; S. Trevezas; F. Houllier; P. de Reffye

Mathematical Modelling of Natural Phenomena (2011)

  • Volume: 6, Issue: 2, page 133-159
  • ISSN: 0973-5348

Abstract

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The development of functional-structural plant models has opened interesting perspectives for a better understanding of plant growth as well as for potential applications in breeding or decision aid in farm management. Parameterization of such models is however a difficult issue due to the complexity of the involved biological processes and the interactions between these processes. The estimation of parameters from experimental data by inverse methods is thus a crucial step. This paper presents some results and discussions as first steps towards the construction of a general framework for the parametric estimation of functional-structural plant models. A general family of models of Carbon allocation formalized as dynamic systems serves as the basis for our study. An adaptation of the 2-stage Aitken estimator to this family of model is introduced as well as its numerical implementation, and applied in two different situations: first a morphogenetic model of sugar beet growth with simple plant structure, multi-stage and detailed observations, and second a tree growth model characterized by sparse observations and strong interactions between functioning and organogenesis. The proposed estimation method appears robust, easy to adapt to a wide variety of models, and generally provides a satisfactory goodness-of-fit. However, it does not allow a proper evaluation of estimation uncertainty. Finally some perspectives opened by the theory of hidden models are discussed.

How to cite

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Cournède, P.-H., et al. "Some Parameter Estimation Issues in Functional-Structural Plant Modelling." Mathematical Modelling of Natural Phenomena 6.2 (2011): 133-159. <http://eudml.org/doc/222339>.

@article{Cournède2011,
abstract = {The development of functional-structural plant models has opened interesting perspectives for a better understanding of plant growth as well as for potential applications in breeding or decision aid in farm management. Parameterization of such models is however a difficult issue due to the complexity of the involved biological processes and the interactions between these processes. The estimation of parameters from experimental data by inverse methods is thus a crucial step. This paper presents some results and discussions as first steps towards the construction of a general framework for the parametric estimation of functional-structural plant models. A general family of models of Carbon allocation formalized as dynamic systems serves as the basis for our study. An adaptation of the 2-stage Aitken estimator to this family of model is introduced as well as its numerical implementation, and applied in two different situations: first a morphogenetic model of sugar beet growth with simple plant structure, multi-stage and detailed observations, and second a tree growth model characterized by sparse observations and strong interactions between functioning and organogenesis. The proposed estimation method appears robust, easy to adapt to a wide variety of models, and generally provides a satisfactory goodness-of-fit. However, it does not allow a proper evaluation of estimation uncertainty. Finally some perspectives opened by the theory of hidden models are discussed. },
author = {Cournède, P.-H., Letort, V., Mathieu, A., Kang, M. Z., Lemaire, S., Trevezas, S., Houllier, F., de Reffye, P.},
journal = {Mathematical Modelling of Natural Phenomena},
keywords = {functional-structural plant models; carbon allocation; GreenLab; maximum likelihood estimator; Aitken Estimator; hidden models; greenlab; Aitken estimator},
language = {eng},
month = {3},
number = {2},
pages = {133-159},
publisher = {EDP Sciences},
title = {Some Parameter Estimation Issues in Functional-Structural Plant Modelling},
url = {http://eudml.org/doc/222339},
volume = {6},
year = {2011},
}

TY - JOUR
AU - Cournède, P.-H.
AU - Letort, V.
AU - Mathieu, A.
AU - Kang, M. Z.
AU - Lemaire, S.
AU - Trevezas, S.
AU - Houllier, F.
AU - de Reffye, P.
TI - Some Parameter Estimation Issues in Functional-Structural Plant Modelling
JO - Mathematical Modelling of Natural Phenomena
DA - 2011/3//
PB - EDP Sciences
VL - 6
IS - 2
SP - 133
EP - 159
AB - The development of functional-structural plant models has opened interesting perspectives for a better understanding of plant growth as well as for potential applications in breeding or decision aid in farm management. Parameterization of such models is however a difficult issue due to the complexity of the involved biological processes and the interactions between these processes. The estimation of parameters from experimental data by inverse methods is thus a crucial step. This paper presents some results and discussions as first steps towards the construction of a general framework for the parametric estimation of functional-structural plant models. A general family of models of Carbon allocation formalized as dynamic systems serves as the basis for our study. An adaptation of the 2-stage Aitken estimator to this family of model is introduced as well as its numerical implementation, and applied in two different situations: first a morphogenetic model of sugar beet growth with simple plant structure, multi-stage and detailed observations, and second a tree growth model characterized by sparse observations and strong interactions between functioning and organogenesis. The proposed estimation method appears robust, easy to adapt to a wide variety of models, and generally provides a satisfactory goodness-of-fit. However, it does not allow a proper evaluation of estimation uncertainty. Finally some perspectives opened by the theory of hidden models are discussed.
LA - eng
KW - functional-structural plant models; carbon allocation; GreenLab; maximum likelihood estimator; Aitken Estimator; hidden models; greenlab; Aitken estimator
UR - http://eudml.org/doc/222339
ER -

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