Precision Agriculture

, Volume 10, Issue 6, pp 459–470 | Cite as

Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves

  • R. Devadas
  • D. W. Lamb
  • S. Simpfendorfer
  • D. Backhouse
Article

Abstract

Ten, 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 Anthocyanin 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.

Keywords

Wheat rust Vegetation index Remote sensing Hyperspectral 

Notes

Acknowledgement

This work was partly conducted within the CRC for Spatial Information (CRCSI), established and supported under the Australian Governments Cooperative Research Centres Programme. The authors gratefully acknowledge Prof. Robert Park (University of Sydney, Cereal Rust Laboratory, Cobbitty, NSW Australia) for provision of the laboratory and plant material used for collection of spectral data, Mr. Graham Hyde (UNE Physics Technical Officer) for ongoing technical support and staff of UNE’s Science and Engineering Workshop (SEW) for construction of the leaf reflectance spectrometer. One author (RD) gratefully acknowledges the receipt of Postgraduate Funding (RD) from the University of New England (UNE) and a ‘Top-up’ Postgraduate Research Scholarship from the CRCSI.

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • R. Devadas
    • 1
    • 2
  • D. W. Lamb
    • 1
    • 2
  • S. Simpfendorfer
    • 3
  • D. Backhouse
    • 4
  1. 1.Cooperative Research Centre for Spatial InformationCarltonAustralia
  2. 2.Precision Agriculture Research Group, School of Science and TechnologyUniversity of New EnglandArmidaleAustralia
  3. 3.New South Wales Department of Primary IndustriesTamworth Agricultural InstituteTamworthAustralia
  4. 4.School of Environmental and Rural ScienceUniversity of New EnglandArmidaleAustralia

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