A statistical approach to multivariate evaluation of diversity with respect to quantitative characteristics in cereal germplasm collections

The aim of this paper is to undertake the problem of adapting some multivariate statistical methods (MANOVA, cluster analysis with simultaneous test procedures T 2 based on Roy's union-intersection rule and canonical variate analysis) max and describing their possible usage in the evaluation and interpretation of the phenotypic diversity with regard to quantitative traits in cereal collections. The presented procedures are used in a case where experimental data have been obtained from single-replicated trials conducted at the same location over a few years. In such cases, data can be nonorthogonal connected accessions x years cross-classification with none or one observation in a given subclass. The application of the suggested procedures is illustrated by a numerical example of a winter rye collection from the Plant Breeding and Acclimatization Institute in Radzikow near Warsaw (Poland).