Show simple item record

contributor authorAylor, Donald E.
contributor authorFlesch, Thomas K.
date accessioned2017-06-09T14:07:56Z
date available2017-06-09T14:07:56Z
date copyright2001/07/01
date issued2001
identifier issn0894-8763
identifier otherams-13014.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4148418
description abstractPractical problems in predicting the spread of plant diseases within and between fields require knowledge of the rate of release Q of pathogenic spores into the air. Many plant pathogenic fungus spores are released into the air from plant surfaces inside plant canopies, where they are produced, or from diseased plant debris on the ground below plant canopies, where they have survived from one growing season to the next. There is no direct way to specify Q for naturally released microscopic fungus spores. It is relatively easy to measure average concentrations of spores above a source, however. A two-dimensional Lagrangian stochastic (LS) simulation model for the motion of spores driven by atmospheric turbulence in and above a plant canopy is presented. The model was compared 1) with measured concentration profiles of Lycopodium spores released from line sources at two heights inside a wheat canopy and 2) with concentration profiles of V. inaequalis ascospores measured above ground-level area sources in a grass canopy. In both cases, there was generally good agreement between the shapes of the modeled and measured concentration profiles. Modeled and measured concentrations were compared to yield estimates of spore release rates. These, in turn, were compared to release rates estimated independently from direct measurements. The two estimates of spore release rate were in good agreement both for 1) the 30-min artificial releases of Lycopodium spores [significance level P = 0.02 (upper source) and P = 0.02 (lower source)] and for 2) the daily total release of V. inaequalis ascospores (P < 0.002). These results indicate that the LS model can yield accurate values of Q (or, conversely, of concentration). Thus, LS models allow a means of attacking a nearly intractable problem and can play an important role in predicting disease spread and in helping to reduce pesticide use in disease-management decisions.
publisherAmerican Meteorological Society
titleEstimating Spore Release Rates Using a Lagrangian Stochastic Simulation Model
typeJournal Paper
journal volume40
journal issue7
journal titleJournal of Applied Meteorology
identifier doi10.1175/1520-0450(2001)040<1196:ESRRUA>2.0.CO;2
journal fristpage1196
journal lastpage1208
treeJournal of Applied Meteorology:;2001:;volume( 040 ):;issue: 007
contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record