Adjusting for Spatial Effects in Genomic Prediction


Phenotypes measured on plants grown in fields can be spatially correlated.  Such correlation can arise because plants growing near each other may share a common microenvironment that differs from the microenvironment experienced by plants in other parts of the field.  This microenvironmental variation can induce phenotypic similarity among neighboring plants.  When such spatial effects exist but are unaccounted for in analysis, decisions about which plant genotypes are expected to perform best with regard to one or more phenotypic traits can be adversely affected.  Baker Center personnel (Mao, Dutta, Wong, and Nettleton) are working to develop methods for genomic prediction that properly adjust for spatial effects when using phenotype data from the field to identify the best genotypes.