Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves
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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.
KeywordsWheat rust Vegetation index Remote sensing Hyperspectral
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.
- Allen, R. (1928). A cytological study of Puccinia glumarum on Bromus marginatus and Triticum vulgare. Journal of Agricultural Research, 36, 487–513.Google Scholar
- Aparicio, N., Villegas, D., & Casadesus, J. (2000). Spectral vegetation indices as non-destructive tools for determining durum wheat yield. Agronomy Journal, 92, 83–91.Google Scholar
- Bushnell, W. R. (1985). Structural and physiological alterations in susceptible host tissue. In A. P. Roelfs & W. R. Bushnell (Eds.), The cereal rusts, vol. 2, diseases, distribution, epidemiology, control (pp. 477–500). Orlando, FL, USA: Academic Press.Google Scholar
- Campbell, J. B. (1996). Introduction to remote sensing (2nd ed.). New York: The Guilford Press.Google Scholar
- Filella, I., Serrano, L., Serra, J., & Penuelas, J. (1995). Evaluating wheat nitrogen status with canopy reflectance indices and discriminant analysis. Crop Science, 35, 1400–1405.Google Scholar
- Franke, J., Menz, G., Oerke, E.-C., & Rascher, U. (2005). Comparison of multi- and hyperspectral imaging data of leaf rust infected wheat plants. In G. D. U. Manfred Owe (Ed.), SPIE-volume 5976 remote sensing for agriculture, ecosystems, and hydrology VII p 59761D. Washington, USA: SPIE - The International Society for Optical Engineering.Google Scholar
- GRDC (2006). The rust diseases of winter cereals-diagnosis, epidemiology and determining economic thresholds. GRDC. Retrieved April 10, 2006 from http://www.grdc.com.au/growers/res_upd/south/s04s/wellings.htm.
- Haboudane, D., Miller, J. R., Tremblay, N., Zarco-Tejada, P. J., & Dextraze, L. (2002). Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sensing of Environment, 81(2–3), 416–426. doi:10.1016/S0034-4257(02)00018-4.CrossRefGoogle Scholar
- Hansen, P. M., & Schjoerring, J. K. (2003). Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression. Remote Sensing of Environment, 86(4), 542–553. doi:10.1016/S0034-4257(03)00131-7.CrossRefGoogle Scholar
- Lamb, D. W. (1999). Airborne digital imaging- the monitoring tool in conservation farming beyond 2000. In J. Kent (Ed.), 26th Riverina Outlook Conference, Australia: Wagga Wagga.Google Scholar
- Lillesand, T. M., & Kiefer, R. W. (1994). Remote sensing and image interpretation (3rd ed.). New York, USA: John Wiley & Sons, Inc.Google Scholar
- Moldenhauer, J., Moerschbacher, B. M., & van der Westhuizen, A. J. (2006). Histological investigation of stripe rust (Puccinia striiformis f.sp.tritici) development in resistant and susceptible wheat cultivars. Plant Pathology, 65, 469–474. doi:10.1111/j.1365-3059.2006.01385.x.CrossRefGoogle Scholar
- Murray, G., Wellings, C., Simpfendorfer, S., & Cole, C. (2005). Stripe rust: Understanding the disease in wheat. New South Wales Department of Primary Industries. Retrieved April 10, 2006 from http://www.ricecrc.org/reader/winter-cereals/stripe-rust-in-wheat.pdf?MIvalObj=25431&doctype=document&MItypeObj=application/pdf&name=/stripe-rust-in-wheat.pdf.
- Myers, V. I. (1983). Remote sensing applications in agriculture. In N. R. Colwell, J. E. Estes, & G. A. Thorley (Eds.), Manual of remote sensing- second edition: Volume II-interpretation, applications (pp. 2111–2228). Virginia, USA: American Society of Photogrammetry.Google Scholar
- NSW DPI (2008). Winter crop variety sowing guide 2008-Part 2. NSW DPI. Retrieved April 28, 2008 from http://www.dpi.nsw.gov.au/__data/assets/pdf_file/0003/108633/wcvsg-Part2.pdf.
- O’Connor. (2003). Cropping systems for enduring productivity in solutions for a better environment. In 11th Australian Agronomy Conference, Australian Society for Agronomy.Google Scholar
- Penuelas, J., Baret, F., & Filella, I. (1995a). Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance. Photosynthetica, 31, 221–230.Google Scholar
- Roelfs, A. P. (1985). Wheat and rye stem rust. In A. P. Roelfs & W. R. Bushnell (Eds.), The cereal rusts, vol. 2, diseases, distribution, epidemiology, control (pp. 4–33). Orlando, FL, USA: Academic Press.Google Scholar
- Saari, E. E., & Prescott, J. M. (1985). World distribution in relation to economic losses. In A. P. Roelfs & W. R. Bushnell (Eds.), The cereal rusts, vol. 2, diseases, distribution, epidemiology, control (pp. 259–298). Orlando, FL, USA: Academic Press.Google Scholar
- Samborski, D. J. (1985). Wheat leaf rust. In A. P. Roelfs & W. R. Bushnell (Eds.), The cereal rusts, vol. 2, diseases, distribution, epidemiology, control (pp. 39–55). Orlando, FL, USA: Academic Press.Google Scholar
- Singh, R. P., Huerta-Espino, J., & Roelfs, A. P. (2002). The wheat rusts. In B. C. Curtis, S. Rajaram, and H.G. Macherson (Eds.), Bread wheat-improvement and production vol. 30. Rome: Plant Production and Protection Series, Food and Agriculture Organisation of the United Nations. Retrieved October 30, 2008 from http://www.fao.org/documents/show_cdr.asp?url_file=/docrep/006/y4011e/y4011e00.HTM.
- Trotter, G. M., Whitehead, D., & Pinkney, E. J. (2002). The photochemical reflectance index as a measure of photosynthetic light use efficiency for plants of varying foliar nitrogen contents. International Journal of Remote Sensing, 23(6), 1207–1212. doi:10.1080/01431160110106096.CrossRefGoogle Scholar
- USDA (2006). Importance of cereal rust disease in American agriculture. Cereal Disease Laboratory, Agricultural Research Service, United States Department of Agriculture. Retrieved March 25, 2006 from http://www.ars.usda.gov/Main/docs.htm?docid=9854.
- Watkins, J. E. (2006). Leaf, stem and stripe rust diseases of wheat. Neb Guide: University of Nebraska-Lincoln. Retrieved March 23, 2006 from http://elkhorn.unl.edu/epublic/pages/publicationD.jsp?publicationId=310#top.
- Wellings, C. R., & Kandel, K. R. (2004). Pathogen dynamics associated with historic stripe (yellow) rust epidemics in Australia in 2002 and 2003. In 11th International Cereal Rusts and Powdery Mildews Conference, John Innes Centre, Norwich, UK. European and Mediterranean Cereal Rust Foundation, Wageningen, Netherlands-2004. Cereal Rusts and Powdery Mildews Bulletin, Abstr. A2.74.Google Scholar
- Young, A., & Britton, G. (1990). Carotenoids and stress. In R. G. Alscher & J. R. Cumming (Eds.), Stress responses in plants: Adaptation, acclimation mechanisms (pp. 87–112). New York: Wiley.Google Scholar
- Zhang, M., Qin, Z., Liu, X., & Ustin, S. L. (2003). Detection of stress in tomatoes induced by late blight disease in California, USA, using hyperspectral remote sensing. International Journal of Applied Earth Observation and Geoinformation, 4(4), 295–310. doi:10.1016/S0303-2434(03)00008-4.CrossRefGoogle Scholar