Use of imaging spectroscopy to discriminate symptoms caused by Heterodera schachtii and Rhizoctonia solani on sugar beet

Use of imaging spectroscopy to discriminate symptoms caused by Heterodera schachtii and... Diseases caused by nematodes and non-sporulating soil-borne fungi have low mobility and are likely to be suitable targets for precision agriculture applications. Sensors which assess the reflectance of plant leaves may be useful tools to detect soil-borne pathogens. The development of symptoms caused by the plant parasitic nematode Heterodera schachtii and the fungal pathogen Rhizoctonia solani anastomosis group 2-2IIIB alone or in combination was studied by leaf reflectance recorded with a hyperspectral imaging system (range 400–1000 nm) for 9 weeks twice per week. Three image processing methods were tested for their suitability to generate the most sensitive spectral information for disease detection. Nine spectral vegetation indices were calculated from spectra to correlate them to leaf symptom recordings. Supervised classification by spectral angle mapper was tested for the discrimination of leaf symptoms caused by the diseases. The symptoms of Rhizoctonia crown and root rot caused by R. solani and symptoms caused by H. schachtii induced modifications that could be detected by hyperspectral image analysis. Rhizoctonia crown and root rot symptom development in mixed inoculations was faster and more severe than in single inoculations, indicating complex interactions among fungus, nematode and plant. The results from this study under controlled conditions are currently used to transfer the sensor technology to the field. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Use of imaging spectroscopy to discriminate symptoms caused by Heterodera schachtii and Rhizoctonia solani on sugar beet

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Publisher
Springer US
Copyright
Copyright © 2011 by Springer Science+Business Media, LLC
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-011-9237-2
Publisher site
See Article on Publisher Site

Abstract

Diseases caused by nematodes and non-sporulating soil-borne fungi have low mobility and are likely to be suitable targets for precision agriculture applications. Sensors which assess the reflectance of plant leaves may be useful tools to detect soil-borne pathogens. The development of symptoms caused by the plant parasitic nematode Heterodera schachtii and the fungal pathogen Rhizoctonia solani anastomosis group 2-2IIIB alone or in combination was studied by leaf reflectance recorded with a hyperspectral imaging system (range 400–1000 nm) for 9 weeks twice per week. Three image processing methods were tested for their suitability to generate the most sensitive spectral information for disease detection. Nine spectral vegetation indices were calculated from spectra to correlate them to leaf symptom recordings. Supervised classification by spectral angle mapper was tested for the discrimination of leaf symptoms caused by the diseases. The symptoms of Rhizoctonia crown and root rot caused by R. solani and symptoms caused by H. schachtii induced modifications that could be detected by hyperspectral image analysis. Rhizoctonia crown and root rot symptom development in mixed inoculations was faster and more severe than in single inoculations, indicating complex interactions among fungus, nematode and plant. The results from this study under controlled conditions are currently used to transfer the sensor technology to the field.

Journal

Precision AgricultureSpringer Journals

Published: Jun 15, 2011

References

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