UTILITY OF REPEATED CHECKS FOR HIERARCHICAL-CLASSIFICATION OF DATA FROM PLANT-BREEDING TRIALS

The investigation of genotypic performance in plant breeding trials is often complicated by genotype X environment (G x E) Interaction. Clustering techniques can be applied to facilitate the investigation of genotypic performance when G x E interaction is a major contributor to the variation. However, the determination of an appropriate number of groups in such applications is often subjective. A simple and practical guideline for determining an appropriate group number in clustering performance-trial data is outlined. The method utilizes repeats of check tines (genotypes) which are grown in each block in each environment within the trial. Application of the method is demonstrated using a relatively small data set consisting of the grain yield of 15 wheat lines and four repeats of a check cultivar, each evaluated in 14 environments in Queensland, Australia. This guideline for group number determination can be used as a stopping rule in hierarchical classification. This approach also highlights the confidence thal can be drawn from any particular partition and dramatizes the effects experimental error has on group composition.