MIXED DATA-TYPES AND THE USE OF PATTERN-ANALYSIS ON THE AUSTRALIAN GROUNDNUT GERMPLASM DATA

Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these d ata, the pattern analysis methods of classification and ordination hav e been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification an d ordination techniques, is often specific to particular data types. T he use of a combined resemblance matrix has an advantage over data typ e specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descri ptors are partitioned into their data types and an appropriate proximi ty measure is used on each. The separate proximity matrices, after ran ge standardisation, are added as a weighted average and the combined r esemblance matrix is then used for classification and ordination. Germ plasm evaluation data for 831 accessions of groundnut (Arachis hypogae a L,) from the Australian Tropical Field Crops Genetic Resource Centre , Biloela, Queensland were examined. Data for four binary, five ordere d multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal w eighting of data types to obtain a combined resemblance matrix - was i nvestigated by using principal co-ordinate analysis (ordination) and h ierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater i nsight into the patterns of variability available in the Australian gr oundnut germplasm collection. The complementary nature of pattern anal ysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This a dditional information may provide plant breeders with a more defined e ntry point into the germplasm collection for identifying sources of va riability for their plant improvement program, thus improving the util isation of germplasm resources.