Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/3400
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dc.contributor.authorDevadas, Rakheshen
dc.contributor.authorLamb, Daviden
dc.contributor.authorSimpfendorfer, Sen
dc.contributor.authorBackhouse, Daviden
dc.date.accessioned2009-11-26T16:34:00Z-
dc.date.issued2009-
dc.identifier.citationPrecision Agriculture, 10(6), p. 459-470en
dc.identifier.issn1573-1618en
dc.identifier.issn1385-2256en
dc.identifier.urihttps://hdl.handle.net/1959.11/3400-
dc.description.abstractTen, widely-used vegetation indices (VIs), based on mathematical combinations of narrow-band optical reflectance measurements in the visible/near infrared wavelength range were evaluated for their ability to discriminate leaves of 1 month old wheat plants infected with yellow (stripe), leaf and stem rust. Narrow band indices representing changes in non-chlorophyll pigment concentration and the ratio of non-chlorophyll to chlorophyll pigments proved more reliable in discriminating rust infected leaves from healthy plant tissue. Yellow rust produced the strongest response in all the calculated indices when compared to healthy leaves. No single index was capable of discriminating all three rust species from each other. However the sequential application of the Anthocyannin Reflectance Index to separate healthy, yellow and mixed stem rust/leaf rust classes followed by the Transformed Chlorophyll Absorption and Reflectance Index to separate leaf and stem rust classes would provide for the required species discrimination under laboratory conditions and thus could form the basis of rust species discrimination in wheat under field conditions.en
dc.languageenen
dc.publisherSpringer New York LLCen
dc.relation.ispartofPrecision Agricultureen
dc.titleEvaluating ten spectral vegetation indices for identifying rust in individual wheat leavesen
dc.typeJournal Articleen
dc.identifier.doi10.1007/s11119-008-9100-2en
dc.subject.keywordsPhotogrammetry and Remote Sensingen
local.contributor.firstnameRakheshen
local.contributor.firstnameDaviden
local.contributor.firstnameSen
local.contributor.firstnameDaviden
local.subject.for2008090905 Photogrammetry and Remote Sensingen
local.subject.seo2008820507 Wheaten
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolOffice of Faculty of Science, Agriculture, Business and Lawen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emailrdevadas@une.edu.auen
local.profile.emaildlamb@une.edu.auen
local.profile.emaildbackhou@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordpes:6770en
local.publisher.placeUnited States of Americaen
local.format.startpage459en
local.format.endpage470en
local.identifier.scopusid84894240293en
local.peerreviewedYesen
local.identifier.volume10en
local.identifier.issue6en
local.contributor.lastnameDevadasen
local.contributor.lastnameLamben
local.contributor.lastnameSimpfendorferen
local.contributor.lastnameBackhouseen
dc.identifier.staffune-id:rdevadasen
dc.identifier.staffune-id:dlamben
dc.identifier.staffune-id:dbackhouen
local.profile.orcid0000-0003-0663-6002en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:3487en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleEvaluating ten spectral vegetation indices for identifying rust in individual wheat leavesen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorDevadas, Rakheshen
local.search.authorLamb, Daviden
local.search.authorSimpfendorfer, Sen
local.search.authorBackhouse, Daviden
local.uneassociationUnknownen
local.identifier.wosid000271803600001en
local.year.published2009en
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