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Simulation of the three‐dimensional distribution of the red:far‐red ratio within crop canopies
Author(s) -
Chelle Michaël,
Evers Jochem B.,
Combes Didier,
VarletGrancher Claude,
Vos Jan,
Andrieu Bruno
Publication year - 2007
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/j.1469-8137.2007.02161.x
Subject(s) - canopy , sensitivity (control systems) , photomorphogenesis , extrapolation , environmental science , biological system , signal (programming language) , field (mathematics) , remote sensing , computer science , mathematics , ecology , biology , statistics , engineering , geography , arabidopsis , biochemistry , electronic engineering , gene , mutant , pure mathematics , programming language
Summary• It is widely recognized that the red:far‐red ratio (ζ) acts as a signal that triggers plant morphogenesis. New insights into photomorphogenesis have been gained through experiments in controlled environments. Extrapolation of such results to field conditions requires characterization of the ζ signal perceived by plant organs within canopies. This paper presents a modeling approach to characterize this signal. • A wheat ( Triticum aestivum ) architectural model was coupled with a three‐dimensional light model estimating the irradiances of virtual sensors. Architectural parameters and ζ values were measured on two contrasting spring wheat canopies under outdoor conditions. Light simulations were compared with measurements, and an analysis of sensitivity to measurement conditions was carried out. • The model results agreed well with measurements and previously published data. The sensitivity analysis showed that ζ strongly depends on canopy development as well as on sky conditions, sensor orientation, and sensor field of view. • This paper shows that modeling enables investigation of ζ distribution in a canopy over space and time. It also shows that the characterization of light quality strongly depends on measurement conditions, and that any discrepancies in results are likely attributable to different experimental set‐ups. The usefulness of this modeling approach for crop photomorphogenesis studies is discussed.