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Interpreting three-dimensional spore concentration measurements and escape fraction in a crop canopy using a coupled Eulerian–Lagrangian stochastic model

Publication ,  Journal Article
Gleicher, SC; Chamecki, M; Isard, SA; Pan, Y; Katul, GG
Published in: Agricultural and Forest Meteorology.
August 2014

Plant disease epidemics caused by pathogenic spores are common threat to agricultural crops. Pathogenic spores are often produced and released inside plant canopies but are transported out of the canopy region by turbulent motions and advected longitudinally over long distances so as to infect other fields. Hence, the fraction of spores that “escape” the canopy sets the effective source strength that determines how fast and far plant diseases can spread. To explore the governing variables of this escape and spatial spread of spores, extensive spore release and recapture experiments were conducted in a maize field and interpreted using a coupled Eulerian–Lagrangian stochastic model (LSM). Spores were released from point sources located at three prototypical depths inside the canopy. Concentration measurements were obtained inside and above the canopy with a 3-dimensional grid of spore collectors. The experimental measurements of mean spore concentration were then used to evaluate an LSM for spore dispersion. The drift and dispersion terms of the LSM were predicted employing a conventional second-order closure model of turbulence within plant canopies thereby allowing this combined Eulerian–Lagrangian formulation to be applied to a broad set of agricultural crops. The dispersion model includes spore deposition on and rebound from canopy elements. The combination of experimental and numerical simulations was then used to quantify the fraction of spores that escape the canopy. Effects of release height and friction velocity on the escape fraction of spores were explored with the LSM.

Duke Scholars

Published In

Agricultural and Forest Meteorology.

DOI

ISSN

0168-1923

Publication Date

August 2014

Volume

194

Start / End Page

118 / 131

Related Subject Headings

  • Meteorology & Atmospheric Sciences
  • 37 Earth sciences
  • 31 Biological sciences
  • 30 Agricultural, veterinary and food sciences
  • 07 Agricultural and Veterinary Sciences
  • 06 Biological Sciences
  • 04 Earth Sciences
 

Citation

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MLA
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Gleicher, S. C., Chamecki, M., Isard, S. A., Pan, Y., & Katul, G. G. (2014). Interpreting three-dimensional spore concentration measurements and escape fraction in a crop canopy using a coupled Eulerian–Lagrangian stochastic model. Agricultural and Forest Meteorology., 194, 118–131. https://doi.org/10.1016/j.agrformet.2014.03.020
Gleicher, Simone C., Marcelo Chamecki, Scott A. Isard, Ying Pan, and Gabriel G. Katul. “Interpreting three-dimensional spore concentration measurements and escape fraction in a crop canopy using a coupled Eulerian–Lagrangian stochastic model.” Agricultural and Forest Meteorology. 194 (August 2014): 118–31. https://doi.org/10.1016/j.agrformet.2014.03.020.
Gleicher SC, Chamecki M, Isard SA, Pan Y, Katul GG. Interpreting three-dimensional spore concentration measurements and escape fraction in a crop canopy using a coupled Eulerian–Lagrangian stochastic model. Agricultural and Forest Meteorology. 2014 Aug;194:118–31.
Gleicher, Simone C., et al. “Interpreting three-dimensional spore concentration measurements and escape fraction in a crop canopy using a coupled Eulerian–Lagrangian stochastic model.” Agricultural and Forest Meteorology., vol. 194, Aug. 2014, pp. 118–31. Epmc, doi:10.1016/j.agrformet.2014.03.020.
Gleicher SC, Chamecki M, Isard SA, Pan Y, Katul GG. Interpreting three-dimensional spore concentration measurements and escape fraction in a crop canopy using a coupled Eulerian–Lagrangian stochastic model. Agricultural and Forest Meteorology. 2014 Aug;194:118–131.
Journal cover image

Published In

Agricultural and Forest Meteorology.

DOI

ISSN

0168-1923

Publication Date

August 2014

Volume

194

Start / End Page

118 / 131

Related Subject Headings

  • Meteorology & Atmospheric Sciences
  • 37 Earth sciences
  • 31 Biological sciences
  • 30 Agricultural, veterinary and food sciences
  • 07 Agricultural and Veterinary Sciences
  • 06 Biological Sciences
  • 04 Earth Sciences