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Remote Sensing for Assessing Rhizoctonia Crown and Root Rot Severity in Sugar Beet

April 2012 , Volume 96 , Number  4
Pages  497 - 505

Gregory J. Reynolds, Department of Plant Pathology, University of California, Davis 95616; Carol E. Windels, Department of Plant Pathology and Northwest Research and Outreach Center and Ian V. MacRae, Department of Entomology and Northwest Research and Outreach Center, University of Minnesota, Crookston 56716; and Soizik Laguette, Department of Earth System Science and Policy, University of North Dakota, Grand Forks 58202

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Accepted for publication 19 November 2011.

Rhizoctonia crown and root rot (RCRR), caused by Rhizoctonia solani AG-2-2, is an increasingly important disease of sugar beet in Minnesota and North Dakota. Disease ratings are based on subjective, visual estimates of root rot severity (0-to-7 scale, where 0 = healthy and 7 = 100% rotted, foliage dead). Remote sensing was evaluated as an alternative method to assess RCRR. Field plots of sugar beet were inoculated with R. solani AG 2-2 IIIB at different inoculum densities at the 10-leaf stage in 2008 and 2009. Data were collected for (i) hyperspectral reflectance from the sugar beet canopy and (ii) visual ratings of RCRR in 2008 at 2, 4, 6, and 8 weeks after inoculation (WAI) and in 2009 at 2, 3, 5, and 9 WAI. Green, red, and near-infrared reflectance and several calculated narrowband and wideband vegetation indices (VIs) were correlated with visual RCRR ratings, and all resulted in strong nonlinear regressions. Values of VIs were constant until at least 26 to 50% of the root surface was rotted (RCRR = 4, wilting of foliage starting to develop) and then decreased significantly as RCRR ratings increased and plants began dying. RCRR also was detected using airborne, color-infrared imagery at 0.25- and 1-m resolution. Remote sensing can detect RCRR but not before initial appearance of foliar symptoms.

© 2012 The American Phytopathological Society