Abstract |
Sugarcane infected with Sugarcane yellow leaf virus (SCYLV) rarely produces visual symptoms until late in the growing season. High-resolution, hyperspectral reflectance data from SCYLV-infected and non-infected leaves of two cultivars, LCP 85-384 and Ho 95-988, were measured and analyzed on 13 July, 12 October, and 4 November 2005. All plants were asymptomatic. Infection was determined by reverse transcriptase-polymerase chain reaction (RT-PCR) analysis. Results from discriminant analysis showed that leaf reflectance was effective at predicting SCYLV infection in 73% of the cases in both cultivars using resubstitution and 63% and 62% in LCP 85-384 and Ho 95-988, respectively, using cross-validation. Predictive equations were improved when data from sampling dates were analyzed individually. SCYLV infection influenced the concentration of several leaf pigments including violaxanthin, beta-carotene, neoxanthin, and chlorophyll a. Pigment data were effective at predicting SCYLV infection in 80% of the samples in the combined data set using the derived discriminant function with resubstitution, and 71% with cross-validation. Although further research is needed to improve the accuracy of the predictive equations, the results of this study demonstrate the potential application of hyperspectral remote sensing as a rapid, field-based method of identifying SCYLV-infected sugarcane plants prior to symptom expression.
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Authors | Michael P Grisham, Richard M Johnson, Paul V Zimba |
Journal | Journal of virological methods
(J Virol Methods)
Vol. 167
Issue 2
Pg. 140-5
(Aug 2010)
ISSN: 1879-0984 [Electronic] Netherlands |
PMID | 20362003
(Publication Type: Journal Article)
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Copyright | Published by Elsevier B.V. |
Chemical References |
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Topics |
- Luteoviridae
(isolation & purification)
- Pigments, Biological
(analysis)
- Plant Diseases
(virology)
- Plant Leaves
(chemistry, virology)
- Saccharum
(chemistry, virology)
- Spectrum Analysis
(methods)
- Virology
(methods)
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