Quasi-Monte Carlo simulation of the light environment of plants

Article

<< Previous

Next >>

Contents Vol 35(10)

doi:10.1071/FP08082

Quasi-Monte Carlo simulation of the light environment of plants

Mikolaj Cieslak ^A ^E ^F, Christiane Lemieux ^B, Jim Hanan ^C, Przemyslaw Prusinkiewicz ^D

^A The University of Queensland, School of Physical Sciences, Qld 4072, Australia.
^B Department of Statistics and Actuarial Science, University of Waterloo, ON N2L 3G1, Canada.
^C The University of Queensland, Centre for Biological Information Technology, Qld 4072, Australia.
^D Department of Computer Science, University of Calgary, AB T2N 1N4, Canada.
^E The Horticulture and Food Research Institute of New Zealand Limited, Palmerston North Research Centre, Palmerston North 4474, New Zealand.
^F Corresponding author. Email: cieslak@maths.uq.edu.au
This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.





	PDF (1.7 MB) $25



	Export Citation

Print

Functional Plant Biology 35(10) 837–849 http://dx.doi.org/10.1071/FP08082
Submitted: 17 March 2008 Accepted: 22 September 2008 Published online: 11 November 2008

Abstract

The distribution of light in the canopy is a major factor regulating the growth and development of a plant. The main variables of interest are the amount of photosynthetically active radiation (PAR) reaching different elements of the plant canopy, and the quality (spectral composition) of light reaching these elements. A light environment model based on Monte Carlo (MC) path tracing of photons, capable of computing both PAR and the spectral composition of light, was developed by Měch (1997), and can be conveniently interfaced with virtual plants expressed using the open L-system formalism. To improve the efficiency of the light distribution calculations provided by Měch’s MonteCarlo program, we have implemented a similar program QuasiMC, which supports a more efficient randomised quasi-Monte Carlo sampling method (RQMC). We have validated QuasiMC by comparing it with MonteCarlo and with the radiosity-based CARIBU software (Chelle et al. 2004), and we show that these two programs produce consistent results. We also assessed the performance of the RQMC path tracing algorithm by comparing it with Monte Carlo path tracing and confirmed that RQMC offers a speed and/or accuracy improvement over MC.

Keywords: light simulation, open L-system, PAR, path tracing, red/far red ratio, (randomised) quasi-Monte Carlo sampling, variance reduction, virtual plant modelling.