Generalized linear mixed models: a practical guide for ecology and evolution, Trends in Ecology and Evolution, vol.24, issue.3, p.127135, 2009. ,
Soil and crop growth microvariability in the west african semi-arid tropics: a possible risk-reducing factor for subsistence farmers, Agriculture, Ecosystems and Environment, vol.45, pp.3-4, 1993. ,
Temperature and Daylength Interaction on Phyllochron in Wheat and Barley, Crop Science, vol.29, issue.4, p.1046, 1989. ,
DOI : 10.2135/cropsci1989.0011183X002900040045x
Statistical Inference., Thomson Learning, 2002. ,
DOI : 10.2307/2532634
Variability of phyllochron, plastochron and rate of increase in height in photoperiodsensitive sorghum varieties, Annals of Botany, vol.101, issue.4, p.57994, 2008. ,
URL : https://hal.archives-ouvertes.fr/hal-01192027
Modelling the inuence of MDR1 polymorphism on digoxin pharmacokinetic parameters, European journal of clinical pharmacology, vol.63, issue.5, p.43749, 2007. ,
Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models: The npde add-on package for R, Computer Methods and Programs in Biomedicine, vol.90, issue.2, pp.154-166, 2008. ,
DOI : 10.1016/j.cmpb.2007.12.002
URL : https://hal.archives-ouvertes.fr/inserm-00274332
Intra-specic variability and the competition-colonisation trade-o: coexistence, abundance and stability patterns, Theoretical Ecology, vol.5, issue.1, p.6171, 2012. ,
Structural Factorization of Plants to Compute Their Functional and Architectural Growth, SIMULATION, vol.82, issue.7, p.82427438, 2006. ,
DOI : 10.1177/0037549706069341
A Forest Growth Simulator Based on Functional-Structural Modelling of Individual Trees, 2009 Third International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications, 2009. ,
DOI : 10.1109/PMA.2009.55
Nonlinear Models for Repeated Measurement Data, 1995. ,
Nonlinear models for repeated measurement data: An overview and update, Journal of Agricultural, Biological, and Environmental Statistics, vol.16, issue.4, p.387419, 2003. ,
DOI : 10.1198/1085711032697
Modeling Inter-individual Variability in Sugar Beet Populations, 2009 Third International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications, 2009. ,
DOI : 10.1109/PMA.2009.56
Convergence of a stochastic approximation version of the EM algorithm. The Annals of Statistics, p.94128, 1999. ,
Capturing diversity and interspecific variability in allometries: A hierarchical approach, Forest Ecology and Management, vol.256, issue.11, p.1939, 1948. ,
DOI : 10.1016/j.foreco.2008.07.034
Nutrients for sugar beet production: Soil-plant relationships, 2003. ,
DOI : 10.1079/9780851996233.0000
Sugarbeet seedling growth from germination to rst leaf stage, Journal of Agricultural Science, vol.124, p.427435, 1995. ,
Canopy development and radiation use eciency of four forage brassica crops, Proceedings of the 16th Australian Agronomy Conference ,
Plant Growth Modelling and Applications: The Increasing Importance of Plant Architecture in Growth Models, Annals of Botany, vol.101, issue.8, p.10531063, 2008. ,
DOI : 10.1093/aob/mcn050
URL : https://hal.archives-ouvertes.fr/halsde-00281936
ADEL-maize: an L-system based model for the integration of growth processes from the organ to the canopy. Application to regulation of morphogenesis by light availability, Agronomie, vol.19, issue.3-4, pp.3-4313327, 1999. ,
DOI : 10.1051/agro:19990311
URL : https://hal.archives-ouvertes.fr/hal-00885933
Phyllochron dierences in wheat, barley and forage grasses, Crop Science, vol.35, issue.1, p.1923, 1995. ,
Modeling and prediction of forest growth variables based on multilevel nonlinear mixed models, Forest Science, vol.47, issue.3, p.311321, 2001. ,
Characterisation of the interactions between architecture and source:sink relationships in Winter Oilseed Rape (Brassica Napus L.) using the GreenLab model, Annals of Botany, vol.107, issue.5, p.765779, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00872374
Measuring phyllochrons in barley to use for seeding rate recommendations, 18th North American Barley Researchers Workshop, 2005. ,
Semiparametric Nonlinear Mixed-Effects Models and Their Applications, Journal of the American Statistical Association, vol.96, issue.456, pp.1272-1298, 2001. ,
DOI : 10.1198/016214501753381913
Coupling a stochastic approximation version of EM with an MCMC procedure, ESAIM: Probability and Statistics, vol.8, p.115131, 2004. ,
DOI : 10.1051/ps:2004007
Maximum likelihood estimation in nonlinear mixed eects models, Computational Statistics & Data Analysis, vol.49, issue.4, p.10201038, 2005. ,
Maximum Likelihood Estimation of Long-Term HIV Dynamic Models and Antiviral Response, Biometrics, vol.48, issue.1, 2010. ,
DOI : 10.1111/j.1541-0420.2010.01422.x
URL : https://hal.archives-ouvertes.fr/inserm-00486937
Eect of planting date and nitrogen fertility on appearance and senescence of sugarbeet leaves, Journal of Sugar Beet Research, vol.25, issue.1, p.2841, 1988. ,
A Morphogenetic Crop Model for Sugar-Beet (Beta vulgaris L.), International Symposium on Crop Modeling and Decision Support: ISCMDS 2008, 2008. ,
DOI : 10.1007/978-3-642-01132-0_14
URL : https://hal.archives-ouvertes.fr/inria-00336415
Analysis of the density eects on the source-sink dynamics in sugar-beet growth, 3rd international symposium on Plant Growth and Applications(PMA09), 2009. ,
Hierarchical segmented regression models with application to a wood density study, 2007. ,
Nonlinear Mixed Eects Models, Biometrics, vol.46, p.673687, 1990. ,
Response of corn grain yield to spatial and temporal variability in emergence, Crop Science, vol.854, issue.44, p.847854, 2004. ,
Using SAEM to estimate parameters of models of response to applied fertilizer, Journal of Agricultural, Biological, and Environmental Statistics, vol.11, issue.1, p.4560, 2006. ,
DOI : 10.1198/108571106X95728
An analysis of leaf growth in sugar beet. I. Leaf appearance and expansion in relation to temperature under controlled conditions, Annals of Applied Biology, vol.106, issue.1, p.163172, 1985. ,
An analysis of leaf growth in sugar beet. II. Leaf appearance in eld crops, Annals of Applied Biology, p.173185, 1985. ,
Uncertainty and sensitivity analysis for crop models, Working with Dynamic Crop Models, p.5596, 2006. ,
Estimating Unknown Transition Times Using a Piecewise Nonlinear Mixed-Eects Model in Men with Prostate Cancer, Journal of the American Statistical Association, issue.429, p.90, 1995. ,
Modelling juvenile-mature wood transition in Scots pine (Pinus sylvestris L.) using nonlinear mixedeects models, Annals of Forest Science, issue.8, p.61831841, 2004. ,
URL : https://hal.archives-ouvertes.fr/hal-00883821
A non-linear hierarchical mixed model to describe tree height growth, European Journal of Forest Research, vol.35, issue.1, pp.281289-1612, 2006. ,
DOI : 10.1007/s10342-006-0118-6
Mixed-Eects Models in S and S-PLUS ,
Phenology and reproductive eort of cultivated and wild forms of Pennisetum glaucum under experimental conditions in the Sahel : implications for the maintenance of polymorphism in the species, Canadian Journal of Botany, vol.74, p.959964, 1996. ,
Maximization of arable crop yields in the netherlands, Netherlands Journal of Agricultural Science, vol.25, p.278287, 1977. ,
Toward extension of a single tree functional???structural model of Scots pine to stand level: effect of the canopy of randomly distributed, identical trees on development of tree structure, Functional Plant Biology, vol.35, issue.10, p.35964975, 2008. ,
DOI : 10.1071/FP08077
A new look at some nitrogen relationships aecting the quality of sugar beets, J. Am. Soc. Sugar Beet Technol, vol.11, issue.5, p.388398, 1961. ,
Estimating leaf appearance rate and phyllochron in saower (Carthamus tinctorius L.). Ciència Rural, p.14481450, 2005. ,
Individual variability in tree allometry determines light resource allocation in forest ecosystems: a hierarchical Bayesian approach, Oecologia, vol.78, issue.4, pp.759-73, 2010. ,
DOI : 10.1007/s00442-010-1581-9
URL : https://hal.archives-ouvertes.fr/hal-01195099
Functional-structural plant modelling in crop production ,
An EM Algorithm for Nonlinear Random Eects Models, Biometrics, vol.52, issue.3, p.934944, 1996. ,
DOI : 10.2307/2533054
The virtual crop-modelling system VICA specied for barley ,
Importance of the Phyllochron in Studying Development and Growth in Grasses, Crop Science, vol.35, issue.1, p.13, 1995. ,
DOI : 10.2135/cropsci1995.0011183X003500010001x
Two Taylor-series approximation methods for nonlinear mixed models, Computational Statistics and Data Analysis, vol.25, p.465490, 1997. ,
Predicting leaf appearance in eld-grown winter wheat: evaluating linear and non-linear models, Ecological Modelling, vol.175, issue.3, p.261270, 2004. ,