YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • AMS
    • Journal of Applied Meteorology and Climatology
    • View Item
    •   YE&T Library
    • AMS
    • Journal of Applied Meteorology and Climatology
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Modeling Soybean Rust Spore Escape from Infected Canopies: Model Description and Preliminary Results

    Source: Journal of Applied Meteorology and Climatology:;2009:;volume( 048 ):;issue: 004::page 789
    Author:
    Andrade, David
    ,
    Pan, Zaitao
    ,
    Dannevik, William
    ,
    Zidek, Jeremy
    DOI: 10.1175/2008JAMC1917.1
    Publisher: American Meteorological Society
    Abstract: Asian soybean rust, caused by Phakopsora pachyrhizi, an airborne fungal pathogen, is an annual threat to U.S. soybean production. The disease is spread during the growing season by fungal spores that are transported from warm southern locations where they overwinter. Current models of long distance spore transport treat spore sources as constant emitters. However, evidence suggests that the spore escape rate depends on 1) the interaction between spores and turbulence within and above an infected canopy and 2) the filtering capacity of the canopy to trap upward-traveling spores. Accordingly, a theoretically motivated yet computationally simple forecast model for escape rate is proposed using a simple turbulence closure method and a parameterization of the canopy porosity. Preliminary escape-rate forecasts were made using the friction velocity, an estimate of initial spore concentrations inside an infected canopy, and the canopy?s leaf area distribution. Sensitivity tests were conducted to determine which biological and meteorological variables and parameters most impact modeled spore escape rates. The spore escape model was integrated with a large-scale spore transport model that was used to forecast spore deposition over U.S. soybean production regions. Preliminary results suggest that varying meteorological conditions significantly impact escape rates and the spread of the disease.
    • Download: (1.696Mb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Modeling Soybean Rust Spore Escape from Infected Canopies: Model Description and Preliminary Results

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4208043
    Collections
    • Journal of Applied Meteorology and Climatology

    Show full item record

    contributor authorAndrade, David
    contributor authorPan, Zaitao
    contributor authorDannevik, William
    contributor authorZidek, Jeremy
    date accessioned2017-06-09T16:22:25Z
    date available2017-06-09T16:22:25Z
    date copyright2009/04/01
    date issued2009
    identifier issn1558-8424
    identifier otherams-66681.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4208043
    description abstractAsian soybean rust, caused by Phakopsora pachyrhizi, an airborne fungal pathogen, is an annual threat to U.S. soybean production. The disease is spread during the growing season by fungal spores that are transported from warm southern locations where they overwinter. Current models of long distance spore transport treat spore sources as constant emitters. However, evidence suggests that the spore escape rate depends on 1) the interaction between spores and turbulence within and above an infected canopy and 2) the filtering capacity of the canopy to trap upward-traveling spores. Accordingly, a theoretically motivated yet computationally simple forecast model for escape rate is proposed using a simple turbulence closure method and a parameterization of the canopy porosity. Preliminary escape-rate forecasts were made using the friction velocity, an estimate of initial spore concentrations inside an infected canopy, and the canopy?s leaf area distribution. Sensitivity tests were conducted to determine which biological and meteorological variables and parameters most impact modeled spore escape rates. The spore escape model was integrated with a large-scale spore transport model that was used to forecast spore deposition over U.S. soybean production regions. Preliminary results suggest that varying meteorological conditions significantly impact escape rates and the spread of the disease.
    publisherAmerican Meteorological Society
    titleModeling Soybean Rust Spore Escape from Infected Canopies: Model Description and Preliminary Results
    typeJournal Paper
    journal volume48
    journal issue4
    journal titleJournal of Applied Meteorology and Climatology
    identifier doi10.1175/2008JAMC1917.1
    journal fristpage789
    journal lastpage803
    treeJournal of Applied Meteorology and Climatology:;2009:;volume( 048 ):;issue: 004
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian