ENHANCED INTERPRETATION OF PATTERN ANALYSES OF ENVIRONMENTS - THE USEOF BLOCKS

Pattern analysis, involving the joint use of classification and ordina tion, has been applied in plant breeding trials to find relationships among environments according to their discrimination among test genoty pes (clones). However, rationalisation of the number of test environme nts from such analyses has often been subjective. A method which allev iates this subjectivity involves considering the blocks (experimental replicates) within environments as different environments and conducti ng a pattern analysis of blocks. The method is demonstrated using thre e sugarcane (Saccharum spp. hybrids) genotype X environment data sets, which contained clones representative of specific selection stages in the breeding program. The first data set contained 54 relatively unse lected clones evaluated in two randomised complete blocks (replicates) at each of nine environments in southeastern Queensland (Qld.) and no rth-eastern New South Wales (N.S.W.), Australia. The second data set c ontained 52 moderately selected clones, evaluated in two replicates at each of six environments in south-eastern Qld. The last data set cont ained information on six highly selected clones present in the same tr ials from which the second data set was collected. The two blocks with in 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 hierarc hical classification could be found for the first data set by truncati ng the hierarchy when both blocks from each environment were grouped t ogether. For the other two data sets an appropriate group number was f ound when the blocks from five of the six environments grouped togethe r. Reasons for the non-grouping of the blocks from that environment ar e discussed. Similarly, an indication of the proximity among blocks ne cessary for them to be considered similar was made by examining the di stance between blocks from the same environment on the first three vec tors from a principal component analysis.