Using spectral reflectance in soybean breeding: evaluating genotypes for soybean sudden death disease resistance and grain yield.

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dc.contributor.author Menke, Ethan J.
dc.date.accessioned 2017-12-12T20:57:40Z
dc.date.available 2017-12-12T20:57:40Z
dc.date.issued 2018-05-01 en_US
dc.identifier.uri http://hdl.handle.net/2097/38542
dc.description.abstract Sudden Death Syndrome (SDS) in soybean, (Glycine max ( L.) Merr.) caused by Fusarium virguliforme, is an increasing problem in commercial soybean production due to the yield loss associated with the disease. Screening for genetic resistance requires extensive visual evaluations. Canopy spectral reflectance may be an indirect tool for selection of SDS resistance as well as grain yield in large segregating populations. The objective of this study was to estimate SDS resistance and seed yield in large diverse soybean populations using canopy spectral reflectance. Spectral reflectance, disease index, maturity and yield were measured on two populations consisting of 160 nested association mapping recombinant inbred lines and checks; and 140 commercial cultivars with checks. Populations were grown in three environments in 2015 and 2016 with historic SDS disease pressure. Entry, environment, and entry by environment sources of variation were significant for disease index, yield, maturity and spectral reflectance. Changes in season average reflectance were correlated to disease index, yield and maturity. Estimation models of disease index, yield and maturity were created with season averages as well as individual day readings for both populations. Season average and individual day models accounted for 11% to 77% of the phenotypic variation in disease and 41% to 93% of yield variation when measurements were taken at the height of disease pressure. Models for disease index and yield models were able to predict significant portions of the phenotypic variation between entries at most environments. These results suggest that it may be possible to estimate resistance to SDS and grain yield in soybeans using spectral reflectance in breeding populations. en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Spectral reflectance en_US
dc.subject Soybean breeding
dc.subject Disease resistance
dc.title Using spectral reflectance in soybean breeding: evaluating genotypes for soybean sudden death disease resistance and grain yield. en_US
dc.type Thesis en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Agronomy en_US
dc.description.advisor William T. Schapaugh Jr en_US
dc.date.published 2018 en_US
dc.date.graduationmonth May en_US


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