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    Estimating Spore Release Rates Using a Lagrangian Stochastic Simulation Model

    Source: Journal of Applied Meteorology:;2001:;volume( 040 ):;issue: 007::page 1196
    Author:
    Aylor, Donald E.
    ,
    Flesch, Thomas K.
    DOI: 10.1175/1520-0450(2001)040<1196:ESRRUA>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: Practical 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.
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      Estimating Spore Release Rates Using a Lagrangian Stochastic Simulation Model

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4148418
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    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
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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