Spatial analysis of multi-environment early generation variety trials

A fully efficient approach for the analysis of multi-environment early stage variety trials is considered that accommodates a general spatial covariance structure for the errors of each trial. The analysis simultaneously produces best linear unbiased predictors of the genotype and genotype by environment interaction effects and residual maximum likelihood estimates of the spatial parameters and variance components. Two motivating examples are presented and analyzed, and the results suggest that the previous approximate analyses can seriously affect estimation of the genetic merit of breeding lines, particularly for models with more complex variance structures.