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LIAMA. Dec. 2002

ADVANCED PROGRAM
Program in pdf format
NEW
TUTORIAL SESSION PROGRAM (Monday, Oct.13rd
limited to 50 people)
 The simulation of organogenesis of plant architecture.
 Modelling the growth of cultivated plants based on the sourcesink relationships.
Both Courses do include botanical, ecophysiological and mathematical
basis relevant for these sessions
a CD is supplied for every registered participant containing
references and sofwares
SCIENTIFIC SESSIONS (Tuesday,
Oct. 14th, Wednesday 15th, Tuesday 16th)
Four Invited Talks: Barthelemy
D. (FR), Heuvelink E.(NL), De Reffye P.(FR), Honjo T.(JP)
Scientific sessions will be held in
single track according to the main three topics:
 Plant Models and
Simulations
 Modeling and simulation
of the environmental factors affecting plant growth
 Computer graphics,
3DVisualisation and Applications of modeling
EXHIBITION (Tuesday Oct. 16th)
Limited presentation of Posters, Laboratory visits.
Invited Talks. See Abstracts hereby
Barthelemy D. (INRA/CIRAD, France)
Botanical Background for Plant Architecture
Analysis and Modelling
Heuveulink E. (Wageningen University, Netherlands)
A photosynthesisDriven Tomato Model: Two
Case Studies
De Reffye P. (CIRAD/INRIA, France)
Relevant qualitative and quantitative
Choices for Building an Efficient Dynamic Plant Growth Model: GreenLab
Case
Honjo T. (Chiba University, Japan)
Visualization of Landscape by Using Plant
Modeling Technique
Detailled
Scientific Program Sessions (tentative) October 14th  October 16th
Plant Growth modeling  Structural models
Invited Talk: Botanical background for plant
architecture analysis and modelling. Barthelemy D.
GreenLab:
Towards A New Methodology of Plant Structural Functional Model Structural
Aspect. Hu B.G., De Reffye P., Zhao X., Yan H.P., Kang
M.Z.
D0Lsystems Described
by Production Tree. Wei M.Z., Xie Z.X.
PlantVR: An Algorithm for Generating Plant Shoot and Root
Growth Using Applied Lindenmayer Systems. ChuaiAree S., Jaeger
W., Bock H.G., Siripant S., Lursinsap C.
ADELWheat: A 3D Architectural Model of Wheat Development.
Fournier C., Andrieu B., Ljutovac S., SaintJean S.
Plant Growth modeling  Functional models  Physiology
Phenological effects on photosynthesis: suggestions
for modelling. Urban L., Lechaudel M., Lu P.
Modelling asynchronous flowering. Normand F., Chadoeuf J., Habib R.
Plant Growth modeling  Functional and Structural
models
Invited Talk: Relevant qualitative
and quantitative Choices for Building an Efficient Dynamic Plant Growth
Model: GreenLab Case. P. De Reffye P., Hu B.G.
The Dynamic Equations of the
Tree Morphogenesis GreenLab Model. De Reffye P., Goursat M., Quadrat
J.P., Hu B.G.
Study on Plant Growth Behaviors Simulated by the Functionalstructural
Plant ModelGreenLab. Yan H.P., De Reffye P., Leroux J., Hu B.G.
Simulation and visualization  Simulation
Could virtual plants be considered
as Lambertian objects in dense canopies ? Chelle M.
A Method To Create Plant Based on Component Technique. Ding
W.L., Xiong F.L.
Interactive Simulation of Plant Architecture Based on a DualScale
Automaton Model. Zhao X., De Reffye P., Barthelemy D., Hu B.G.
Stochastic 3D Tree Simulation using Substructure Instancing.
Kang M.Z., De Reffye P., Barczi J.F., Hu B.G., Houllier
F.
Simulation and visualization
 Visualisation
Tree and Plant Volume
imaging. An introductive study towards voxelized functional landscapes.
Jaeger M., Teng J.
Progressive Polygon Foliage Simplification. Zhang X.P.,
Blaise F.
High Performance Computing and Visualisation for Forestry
Applications  Project SILVES. F. Blaise F. , Cavin X. , Paul J.C.
Accurate Graphical Representation of Plant Leaves. Franzke
O., Deussen O.
Particle Systems for plant modeling. Rodkaew Y., Chongstitvatana
P., Siripant S., Lursinsap C.
3D digitisation and modeling of flower mutants of Arabidopsis
thaliana. De Visser P.H.B., Marcelis L.F.M., Van der Heijden
G.W.A.M., Angenent G.C.
Applications  Agronomy
Invited Talk:A photosynthesisdriven
tomato model: Two case studies. Heuvelink E.,
Bakker M.J.
Fitting a StructuralFunctional
Model with Plant Architectural Data. Zhan Z.G., De Reffye P.,
Houllier F., Hu B.G.
Study on Modeling Tomato Growth Based on interaction of Its
StructureFunction. Dong Q.X., Wang Y.M., Barczi J.F.,
De Reffye P., Hou J.L.
Greenhouse Tomato Model and Its Simulation System. Sun
Z.F., Chen R.J.
Modeling of Biomass Acquisition and Biomass Partitioning in
the Architecture of Sunflower. Guo Y., De Reffye P., Song Y.H.,
Zhan Z.G., Li B.G., Dingkuhn M.
Maize fruit sink reference based on GreenLab Model. Wu
L., de Reffye P., Le Dimet F.X., Hu B.G.
Influence of morphometric characteristics of the Hybrid Walnut
tree crown (Juglans nigra x Juglans regia) on its radiative balance.
Parveaud C.E.
Assimilation of high temporal frequency SPOT data to describe
canopy functioning. Lauvernet C., Le Dimet F.X., Baret
F.
Modeling yield and grain protein of Japanese wheat by DSSAT
Cropping System Model. Anwar M.R., Takahashi S., Itoh S., Nakatsuji
T.
Analysis and modelling of the root system architecture of
winter wheat seedlings. Zhang B.G., De Reffye P., Liu
L., Kang M.Z., Li B.G.
Modelling tillering in wheat (Triticum aestivum L.) using
Lsystems. Evers J.B., Vos J., Fournier C., Chelle M.,
Andrieu B.
A process & componentbased wheat growth simulation system.
Cao W.X., Pan J., Zhu Y., Hu JH., Zhuang H.Y.
Applications  Forestry
Modelling and Sawing Simulation
of Sugar Maple Logs: Application of Computer Tomography Images. Tong
Q.J., Zhang S.Y., Levesque Y.
Tree shape measurement at the stand level for biomass, volume
and wood properties assessment. Badia M., Hapca A., Constant T.,
Mothe F., Leban J.M., SaintAndré L., Daquitaine R., Blaise F.
Sawing of Logs in Virtual Trees using 3DIntersection Algorithms.
Szafran N., Despreaux S., Biard L., Blaise F.
Application of Plant Models to Biomechanics. Fourcaud T., Dupuy L., Sellier D., Ancelin P., Lac P.
Applications  Land Use
Invited Talk:Visualization of Landscape by Using
Plant Modeling Technique. Honjo T., Lim E.M.
Coupling process models
with GIS: two case studies in two scales. Huang Y.F.
Graphic modeling and realistic computer approach, Visualization
of periurban landscape. Alinat S., Carrie C., Auclair D.
Plant Modeling for Landscape Changes Visualization Application
to a PeriUrban Agricultural Area. Borne F., Satornkich
J., Pages J., Anwar S.M.
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INVITED
TALKS  ABSTRACTS
Botanical background for plant architecture
analysis and modelling.
Dr Daniel Barthélémy.
Programme modélisation des plantes du
Ciradamis, Unité Mixte CiradCnrsInraIrdUniversité
Montpellier 2 Montpellier (France)
The architecture of a plant
depends on the nature and on the relative arrangement of each of its
parts ; it is, at any given time, the expression of an equilibrium between
endogenous growth processes and exogenous constraints exerted by the environment.
The aim of architectural analysis is to identify and understand these
endogenous processes by means of observation and sometimes experimentation.
Considering the plant as a whole, from germination to death, architectural
analysis is essentially a detailed, comprehensive and dynamic approach of
plant development. Despite their recent origin, architectural concepts
provide a powerful tool for studying plant form. Completed by precise morphological
observations, recent researches in this field have deeply increased our
understanding of plant structure and development and led to the establishment
of a real conceptual and methodological framework for plant form study
and modelling. This paper is a brief and summarised update of our knowledge
on plant architecture and morphology.
Keyswords : plant morphology, plant architecture,
level of organisation, differentiation, morphogenetical gradient, physiological
age, meristem
A PhotosynthesisDriven
Tomato Model: Two Case Studies.
Dr Ep Heuvelink and Menno J. Baker.
Wageningen University, Horticultural Production
Chain Group, (The Netherlands)
A photosynthesisdriven model
for potenial crop growth and yield in tomato, TOMSIM, was used in two case
studies: (1) determination of the number of fruits per truss that results
in maximum fruit yield for different greenhouse climatic conditions, cultivation
practices and crop characteristics, and (2) studying the effect of salinity
stress on optimum fruit number for maximum yield. Crop growth rate is
simulated as daily crop gross assimilation rate minus maintenance respiration
rate, multiplied by a conversion factor for assimilates to dry mass. Dry
matter distribution is simulated based on the sink strength (demand for
assimilates) of the plant organs, which is quantified by their potential
growth rate, relative to the total sink strength of all sinks together.
Within the plant, individual fruit trusses and vegetative units (three
leaves and stem internodes between two trusses) are distinguished. Leaf
area is simulated, based on simulated leaf dry mass and specific leaf
area (SLA). SLA depends on the day of the year, being lowest in summer.
Number of fruits per truss is an input to the model, hence, flower and/or
fruit abortion is not simulated. Fruit yield is expected to show an optimum
response to fruit load, as a higher fruit load increases partitioning to
the fruit, possibly at the expense of total crop growth, because of reduced
leaf area index (LAI). Optimum fruit number per truss was lower at reduced
global radiation level, when no CO2enrichment was applied, with earlier
leaf picking, reduced SLA and larger potential fruit size. Salinity stress
was implemented in the model as a reduction in SLA with increased salinity.
Yield was strongly reduced as LAI was reduced. Optimum fruit number per
truss decreased linearly with increasing salinity. At higher salinity levels
maintaining optimum fruit numbers (less than seven) resulted in a reduction
in yield loss, compared to maintaining a fixed number of seven fruits per
truss. The model enables to quantify the relations between fruit load, total
dry mass production and fruit yield under different conditions. It can evaluate
conditions that cannot be attained experimentally, which may be important
in theoretical studies.
The model enables to quantify the relations between fruit
load, total dry mass production and fruit yield under different conditions.
It can evaluate conditions that cannot be attained experimentally, which
may be important in theoretical studies.
Keyswords : model, leaf, extension, leaf picking
strategy, simulation, tomato fruit yield, TOMSIM, optimum fruit number,
salinity, salt stress, specific leaf aera
Relevant qualitative and quantitative Choices for Building
an Efficient Dynamic Plant Growth Model: GreenLab Case
Dr
Philippe de Reffye(1) and Prof. Baogang HU(2)
(1)CiradAmis
Montpellier and INRIA Rocquencourt, Metalau Project, (France). (2)LIAMA,
Institute of Automation of CAS, Beijing (China).
Plant growth modelling rigorous study
is a real challenge for researchers and scientists, due to the high level
of multidisciplinary aspects to be integrated in. Through a mathematical
formalism, a plant functionalstructural model needs to be developped based
on knowledge from botany, agronomy, forestry, ecophysiology and computer
sciences. Specialists in each discipline have proposed variety models,
but most of these models are limited to their own field. It is well recognized
that the unfunctioning and the limitation of these models are due to their
monodisciplinary aspects. A dialogue between the various scientific domains
involved in plant modelling is not obvious. It needs to chose, simplify
and adapt the relevant knowledge from each other that is necessary and
sufficient to build a plant structuralfunctional model. This needs also
to define a right level of observations. Each notion is simplified, but
the interactions between them give new theoritical results and applications.
Several questions are discussed in this work. How can botany give keys
to organize the multi level information inside the plant topological structure
and eventually speed up the growth computing ? What kind of mathematical
formalism is needed to introduce powerful tools of automatic control into
plant modelling ? The goal of this paper is to propose some simple choices,
from both biological and mathematical viewpoints, and adapt them to build
an efficient dynamical model. With this model, it is possible to insure
optimisation and control that are needed in agronomy.
Keyswords : plant growth, modeling, dynamic
process, botany, agronomy, mathematics, relevant study
Visualization of Landscape
by Using Plant Modeling Technique.
Dr Tsuyoshio Honjo and EmMi Lim
Department of Environmental Science and Landscape
Architecture, of Chiba University (Japan)
Recent progress of plant
modeling technique enables the realistic modeling of plant shape and
the realistic landscaping. In this study, applications of plant modeling
technique on making realistic images for landscape planning are reviewed.
Simulation of landscape by linking GIS (Geographic Information System)
and plant modeling technique and application of VRML (Virtual Reality
Modeling Language) for realtime walkthrough in a virtual landscape are
also explained.
Keywords: plant modeling, computer graphics,
landscape simulation, virtual reality, VRML
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