COURSES

-> About this Resource
Scope *______
Map *____

-> Preliminary Courses
Contents & Objectives *__________________
Map *____
-> Botany
Contents & Objectives *__________________
Map *____
-> Axis Typology Patterns
Typology basis *___________
Pictograms *_________
Sexuality & development *___________________
Growth *______
Branching rhythms *______________
Branching delays *_____________
Branching positional *________________
Branching arrangement *__________________
Axis orientation *_____________
Architectural models *________________
-> Architectural Unit
About Arc. Models *______________
Models limitations *______________
Architectural Units *______________
Reiteration *_________
Sequence of development *___________________
Morphogenetic gradients *___________________
Physiological age *_____________
-> An Example
Wild Cherry (young) *_______________
Wild Cherry (adult) *______________
Wild Cherry (mature) *________________
Quiz *____
Case study Quiz *_____________
Supplementary resources *____________________

-> Eco-Physiology
Contents & Objectives *__________________
Map *____
-> Growth Factors
Factors affecting Growth *___________________
Endogenous Processes *_________________
Environmental Factors *_________________
Thermal Time *___________
-> Light interaction
P.A.R. *_____
Light absorption *_____________
Photosynthesis *___________
Respiration *_________
Maintenance respiration *__________________
L.U.E. Model *__________
Density effect *___________
Density effect on crop *__________________
-> Biomass
Biomass Pool *__________
Biomass Partitioning *_______________
Crop models *__________
A Crop model example *__________________
Quiz *____
Supplementary resources *___________________

-> Applied Mathematics
Contents & Objectives *__________________
Map *____
-> Probabilities
Section contents *____________
Discrete Random Variable *___________________
Expected value, Variance *___________________
Properties *________
-> Useful Laws
Bernoulli Trials *___________
Binomial Law *__________
Geometric Law *____________
Negative Binomial Law *_________________
-> Dynamic systems
Section contents *_____________
Useful functions *____________
Beta density *__________
Exercises *________
Negative Exponential *________________
Systems functions *______________
Discrete dynamic systems *___________________
Parameter Identification *__________________
Parameter estimation *________________
Supplementary Resources *____________________


-> GreenLab courses
GreenLab presentation *__________________
-> Overview
Presentation & Objectives *____________________
Map *____
Growth and components *___________________
Plant architecture *_______________
Biomass production *________________
Modelling - FSPM *______________
GreenLab principles *________________
Applications *__________
Supplementary resources *_____________________
-> Principles
Presentation & Objectives *____________________
Map *____
-> About modelling
Scientific disciplines *________________
Organs: tree components *___________________
Factors affecting growth *___________________
Model-simulation workflow *____________________
GreenLab inherits from *__________________
GreenLab positioning *_________________
The growth cycle *______________
Inside the growth cycle *___________________
Implementations *______________
Supplementary resources *____________________
-> Development
Presentation & Objectives *____________________
Map *____
Modelling Scheme *______________
Tree traversal modes *________________
-> Stochastic modelling
Principles *_______
-> Development
Growth Rhythm *____________
Damped growth *____________
Viability *______
Rhythmic axis *___________
Branching *________
Stochastic automaton *_________________
-> Organogenesis equations
Principles *_______
Organ cohorts *___________
Organ numbering *_____________
Substructure factorization *____________________
Stochastic case *____________
-> Structure construction
Construction modes *_______________
Construction basis *______________
Axis of development *________________
Stochastic reconstruction *___________________
Implicit construction *________________
Explicit construction *________________
3D construction *____________
Supplementary resources *____________________
-> Production-Expansion
Presentation & Objectives *____________________
Map *____
-> EcoPhysiology reminders
Relevant concepts *______________
Temperature *__________
Light interception *______________
Photosynthesis *___________
Biomass common pool *_________________
Density *______
-> Principals
Growth cycle *__________
Refining PbMs *___________
Organ cohorts *___________
GreenLab vs PbM & FSPM *___________________
-> GreenLab's equations
Summary *_______
Production equation *_______________
Plant demand *__________
Organ dimensions *______________
A dynamic system view *__________________
Equation terms *____________
Full Model *________
Model behaviour *______________
Supplementary resources *____________________
-> Applications
Presentation & Objectives *____________________
Map *____
-> Measurements
Agronomic traits *_____________
Mesurable/hidden param. *___________________
Fitting procedure *______________
-> Fitting structure
Principles *_______
-> Development
Simple development *_______________
Damped growth *____________
Rhythmic growth *_____________
Rhythmic growth samples *___________________
Mortality *_______
Branching *________
-> Crown analysis
Analysis principles *______________
Equations *________
Example / Exercise *_______________
-> Case study
Plant Architecture *______________
Development simulation *__________________
Introducing Biomass *_______________
Biomass partitioning *_______________
Equilibrium state *_____________
Supplementary resources *____________________

-> Tools (software)
Presentation & Objectives *_____________________
Map *____
Fitting, Stats *___________
Simulation *_________
Online tools *__________

Applications

Measurements

Fitting functional parameters


Overview

    Since plant growth can be modelled in the form of a dynamic system, classic methods of parameter estimation can be used, based on maximum likelihood criteria and Newtonian methods of optimization.

    The model outputs from which this identification can be achieved are the organ masses, as they can be easily measured on real plants and as they result from plant functioning and thus keep track of the whole history of source-sink balances.

    If we consider a monospecies population, several plants at different ages can be used simultaneously to form the observation vector.

    Fitting GreenLab parameters
    Fitting parameters from several growth stages (Zhang Zhighan, LIAMA/CAU 2008)
      Several growth stages of the same plant are fitted simultaneously at organ biomass level with an optimized common set of parameters that ensure biomass production and biomass partitioning.
      The organs of different types are fitted together because they share the same plant demand and production.
      Plant growth dynamics may be controlled by a small set of constant parameters.


    Complications can be induced if the population has strong intraspecific genetic variability and environmental variability.

    The amount of data collected is a compromise between the statistical accuracy of estimation and the heaviness of the measurements.
    In most cases, the simplifications used in the physiological model are justified by the comparison of the model with real plants, since a very small number of model parameters are sufficient to predict a large number of data.

    Even though all the complex phenomena underlying plant growth and development are not accounted for, the prediction ability of such models remains quite good.
    The reason is that the simple theoretical plant given by the model is such that its architectural trajectory is very close to that of the real complex plant.


    GreenLab simulated plants
    Simulations of 3-D plant architectures including growth and development
    (using versions of the GreenLab model: developed at INRIA, ECP, LIAMA, CIRAD)
          (a) Arabidopsis plant, LEPSE (Digiplante software: ECP)
          (b) Beetroot plant, Institut Tecnique de la Betterave (Digiplante software)
          (c) Wheat plant, Wageningen University (GreenScilab software: LIAMA)
          (d) Maize plant, Chinese Agricultural University (software CAU)
          (e) Sunflower plant: INRA/LEPSE (Digiplante software)
          (f) Chrysanthemum plant,Wageningen University (GreenScilab software)
          (g) Pine tree, Chinese Academy of Forestry (Digiplante software)
          (h) Coffee tree, CIRAD (Digiplante software)
          (i) Cucumber plant, CAU (Digiplante software)
          (j) Tomato plant, CAU (CornerFit software: LIAMA)


    Compared to structural simulations, the representations of the above simulations are more accurate, because the sizes of organs depend on biomass production and biomass partitioning and do not directly result from empirical data sets.