Resolving Disease Severity in Rice within a Multi-Year, Multi-Cropping System Experiment.

False smut (<i>Ustilaginoidea virens</i>) and kernel smut (<i>Neovossia horrida</i>) are diseases of rice (<i>Oryza sativa</i> L.) that reduce both grain yield and quality.  As part of a larger multi-year rotation study, this experiment was conducted to determine the effects of crop management practices (rotation, tillage, variety, and fertility) on grain yield and disease severity.  False smut, kernel smut, and yield data was collected for two years from this large-scale field experiment designed using a randomized split-strip plot design.  The example discussed here will spotlight building an appropriate and useful statistical model for analysis where the dependant variable is non-normal, and the inclusion of several fixed and random effects and their corresponding errors is necessary.  Additionally, selection of an appropriate covariance structure for correlated errors will be addressed.  Analyses examples will be presented using the GLIMMIX procedure in SAS.  It will also be illustrated how the researchers are using the information identified through these analyses to identify cropping systems that can be employed to minimize the severity of smut diseases and maintain maximum yield potential from available rice varieties.