Enhanced interpretation of pattern analyses of environments: the use of blocks

Abstract

Pattern analysis, involving the joint use of classification and ordination, has been applied in plant breeding trials to find relationships among environments according to their discrimination among test genotypes (clones). However, rationalisation of the number of test environments from such analyses has often been subjective. A method which alleviates this subjectivity involves considering the blocks (experimental replicates) within environments as different environments and conducting a pattern analysis of blocks. The method is demonstrated using three sugarcane ( Saccharum spp. hybrids) genotype × environment data sets, which contained clones representative of specific selection stages in the breeding program. The first data set contained 54 relatively unselected clones evaluated in two randomised complete blocks (replicates) at each of nine environments in south-eastern Queensland (Qld.) and north-eastern New South Wales (N.S.W.), Australia. The second data set contained 52 moderately selected clones, evaluated in two replicates at each of six environments in south-eastern Qld. The last data set contained information on six highly selected clones present in the same trials from which the second data set was collected. The two blocks within each environment were considered to be different environments and a pattern analysis of the blocks present in each data set was conducted. Results confirmed that an appropriate group number following hierarchical classification could be found for the first data set by truncating the hierarchy when both blocks from each environment were grouped together. For the other two data sets an appropriate group number was found when the blocks from five of the six environments grouped together. Reasons for the non-grouping of the blocks from that environment are discussed. Similarly, an indication of the proximity among blocks necessary for them to be considered similar was made by examining the distance between blocks from the same environment on the first three vectors from a principal component analysis.