TY - JOUR T1 - Three-dimensional plant architecture and sunlit-shaded dynamics: a stochastic model to enable high-throughput physiological analysis JF - bioRxiv DO - 10.1101/147553 SP - 147553 AU - Renata Retkute AU - Alexandra J. Townsend AU - Erik H. Murchie AU - Oliver E. Jensen AU - Simon P. Preston Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/06/08/147553.abstract N2 - • Background and Aims Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture results in highly variable and dynamic light patterns within the plant canopy. This influences productivity because photosynthesis is highly responsive to changes in light intensity. Current methods to characterise light dynamics, such as ray tracing, are able to produce data with excellent spatio-temporal resolution but are computationally intensive and the resultant data are complex and high dimensional. This necessitates development of more economical models to simulate realistic light patterns over the course of the day.• Methods High-resolution reconstructions of field-grown wheat canopies were assembled in various configurations using digital imaging methods. A forward ray-tracing algorithm was employed to compute canopy light dynamics at high (1 minute) temporal resolution. The output was used to designate leaf sections as sunlit or shaded at each time interval. A stochastic model for sunlit-shaded patterns was developed and fitted using maximum likelihood estimation. Principal component analysis was used to study the similarities and differences in dynamic light distribution between different canopies.• Key Results A two-state Markov chain model sufficiently replicates key features of the light dynamics, as achieved via ray-tracing data, provided that the rates of switching (from sunlit to shaded, and vice versa) are assumed to be distinct and to be functions of the time of day and the height within the canopy.• Conclusions The Markov chain model captures the essential features of light dynamics within a canopy and enables a clear understanding of how position, time of day, and canopy characteristics affect light patterns. Furthermore, the model provides a cheap way to simulate realistic light patterns, which we anticipate being important for feeding into larger scale photosynthesis models for calculating how light dynamics affects the photosynthetic productivity of a canopy. ER -