AOBPreview originally published online on March 31, 2004
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Annals of Botany 93: 591-602, 2004
© 2004 Annals of Botany Company
A Dynamic, Architectural Plant Model Simulating Resource-dependent Growth
1 NLPR, Institute of automation, CAS, 2728, 100081, Beijing, China, 2 INRIA-Rocquencourt B.P. 105, 78153 Le Chesnay Cedex (France) and 3 Cirad-amis,TA 40/01 Ave Agropolis, 34398 Montpellier, France Cedex 5
* For correspondence. E-mail: dingkuhn{at}cirad.fr
Received: 12 September 2003; Returned for revision: 24 October 2003; Accepted: 7 January 2004 Published electronically: 31 March 2004
• Background and Aims Physiological and architectural plant models have originally been developed for different purposes and therefore have little in common, thus making combined applications difficult. There is, however, an increasing demand for crop models that simulate the genetic and resource-dependent variability of plant geometry and architecture, because man is increasingly able to transform plant production systems through combined genetic and environmental engineering.
• Model GREENLAB is presented, a mathematical plant model that simulates interactions between plant structure and function. Dual-scale automaton is used to simulate plant organogenesis from germination to maturity on the basis of organogenetic growth cycles that have constant thermal time. Plant fresh biomass production is computed from transpiration, assuming transpiration efficiency to be constant and atmospheric demand to be the driving force, under non-limiting water supply. The fresh biomass is then distributed among expanding organs according to their relative demand. Demand for organ growth is estimated from allometric relationships (e.g. leaf surface to weight ratios) and kinetics of potential growth rate for each organ type. These are obtained through parameter optimization against empirical, morphological data sets by running the model in inverted mode. Potential growth rates are then used as estimates of relative sink strength in the model. These and other ‘hidden’ plant parameters are calibrated using the non-linear, least-square method.
• Key Results and Conclusions The model reproduced accurately the dynamics of plant growth, architecture and geometry of various annual and woody plants, enabling 3D visualization. It was also able to simulate the variability of leaf size on the plant and compensatory growth following pruning, as a result of internal competition for resources. The potential of the model’s underlying concepts to predict the plant’s phenotypic plasticity is discussed.
Key words: Plant architecture, phenotypic plasticity, demand functions, competition among sinks, source–sink relationships, structural-functional models.
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