We successfully applied the GLIMMIX procedure for this purpose. Data from a progeny test trial was available to identify parents with high breeding values for resistance. actinidiae is a serious disease of kiwifruit in New Zealand and other kiwifruit-producing countries. Bacterial canker (Psa) caused by Pseudomonas syringae pv. Binary data that fits the GLMM framework is commonly encountered in breeding experiments, such as when evaluating individuals for resistance by observing the presence or absence of disease. This is particularly so for Proc GLIMMIX because, unlike ASReml software, it is not specifically tailored for analysis of breeding data and some pre-procedure coding is necessary.

Applications of GLMMs to genetic analysis have been limited, probably because of the complexity of the models used. The GLIMMIX procedure in SAS® is becoming popular for fitting GLMMs in various disciplines. Although the theoretical aspects for extending LMM to generalised linear mixed models (GLMMs) have been around for some time, suitable software has been developed only within the last decade or so.

Linear Mixed models (LMMs) that incorporate genetic and spatial covariance structures have been used for many years to estimate genetic parameters and to predict breeding values in animal and plant breeding.