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Reynolds, G. J., Windeis, C. E., MacRae, I. V., and Laguette, S. 2012. Remote sensing for assessing Rhizoctonia crown and root rot severity in sugar beet. Plant Dis. 96:497-505.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 (O-to-7 scale, where 0 = healthy and 7 = 1009Í-rotted, foliage dead). Remote sensing was evaluated as an alternative method to assess RCRR. Field plots of sugar beet were inoculated with /?. 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 507f of the root surface was rotted (RCRR = 4, wilting of tbliage 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. Rctnotc sensing can detect RCRR but not before initial appearance of foliar symptoms.The soilbome fungus Rhizoctonia soiani Kühn AG-2-2 inttaspeciftc groups IIIB and IV cause Rhizoctonia crown and root rot (RCRR) of sugar beet (Beta vutgaris L.) ( 11,73,74). Since the early 1990s, these pathogens have become widespread in sugar beetgrowing regions of Minnesota and North Dakota because of wet weather (40), planting of susceptible sugar beet cultivars (Al Cattanach, personal communication), and increased production of soybean, edible bean, and corn (69), which are alternate hosts of R. solani 20,32,73,74). Production of these susceptible rotation crops in the sugar beet cropping systetn allows R. solani inoculutn to build up in soil and contribute to disease outbreaks, Managetnent of RCRR is achieved through rotations of three or more years with non-host plants (57,58,75), early planting (10), and application of fungicides (22,27,28,67,72), Symptoms of RCRR include a dark-brown to gray rot that typically begins near the crown and spreads over the root surface, eventually causing cracking and sunken lesions (75). Petioles are black and rotted at the point of attachment to the crown. Sometimes, infections occur on the root tip or laterally on the root surface (75). Aboveground, foliage may show sudden and severe wilting and then chlorosis: severely infected plants eventually die. Disease severity typically is assessed by a visual rating scale based on the atnount of rot on the tap root (45). This rating system, however, is destructive and requires removal of roots from soil. Furthennore, visual disease assessments are subjective i...

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Remote sensing for assessing Rhizoctonia crown and root rot severity in sugar beet. 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 (0-7 scale; 0=healthy; 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 a range of inoculum densities at the 10-leaf stage in 2008 and 2009. Data were collected for 1) hyperspectral reflectance from the sugar beet canopy and 2) 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) correlated with visual ratings of RCRR, and all resulted in strong non-linear regressions. Values of VIs were constant until 25 to 50% of the root surface rotted and then decreased significantly as disease severity increased. RCRR also was detected using airborne, color-infrared imagery at 0.25 m and 1 m resolution. Remote sensing can detect RCRR but not before initial appearance of foliar symptoms.

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