Combinatorial analysis of ramified patterns and computer imagery of trees
SIGGRAPH '89 Proceedings of the 16th annual conference on Computer graphics and interactive techniques
Voxel space automata: modeling with stochastic growth processes in voxel space
SIGGRAPH '89 Proceedings of the 16th annual conference on Computer graphics and interactive techniques
An introduction to the analysis of algorithms
An introduction to the analysis of algorithms
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Approximate and probabilistic algorithms for shading and rendering structured particle systems
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Development models of herbaceous plants for computer imagery purposes
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Plant models faithful to botanical structure and development
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Plants, fractals, and formal languages
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Mathematics and Computers in Simulation - Special issue: Selected papers of the IMACS/IFAC fourth international symposium on mathematical modelling and simulation in agricultural and bio-industries
Functional-Structural Plant Modelling in Crop Production
Functional-Structural Plant Modelling in Crop Production
Computers and Electronics in Agriculture
Mathematics and Computers in Simulation
Modeling plant plasticity from a biophysical model: biomechanics
Proceedings of the 12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
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A stochastic functional-structural model simulating plant development and growth is presented. The number of organs (internodes, leaves and fruits) produced by the model is not only a key intermediate variable for biomass production computation, but also an indicator of model complexity. To obtain their mean and variance through simulation is time-consuming and the results are approximate. In this paper, based on the idea of substructure decomposition, the theoretical mean and variance of the number of organs in a plant structure from the model are computed recurrently by applying a compound law of generating functions. This analytical method provides fast and precise results, which facilitates model analysis as well as model calibration and validation with real plants. Furthermore, the mean and variance of the biomass production from the stochastic plant model are of special interest linked to the prediction of yield. In this paper, through differential statistics, their approximate results are computed in an analytical way for any plant age. A case study on sample trees from this functional-structural model shows the theoretical moments of the number of organs and the biomass production, as well as the computation efficiency of the analytical method compared to a Monte-Carlo simulation method. The advantages and the drawbacks of this stochastic model for agricultural applications are discussed.