Multivariate diversity of Polish winter triticale cultivars for spike and other traits.
Wanda Kociuba
Iinstitute of Genetics, Breeding and Plant Biotechnology, University of Life Sciences, Lublin, Poland (Poland)
Wiesław Mądry
Department of Experimental Dcsign and Bioinformatics, University of Life Sciences, Warsaw, Poland (Poland)
Aneta Kramek
Iinstitute of Genetics, Breeding and Plant Biotechnology, University of Life Sciences, Lublin, Poland (Poland)
Krzysztof Ukalski
Department of Experimental Dcsign and Bioinformatics, University of Life Sciences, Warsaw, Poland (Poland)
Marcin Studnicki
Department of Experimental Dcsign and Bioinformatics, University of Life Sciences, Warsaw, Poland (Poland)
Abstract
The objective of the present study was to determine the extent and pattern of genotypic diversity for six spike quantitative characters and two other traits in 36 winter triticale cultivars released in Poland, to classify the cultivars into similarity groups (clusters) and to identify those traits, among the studied ones, which mostly discriminated distinguished groups of cultivars. The 36 cultivars, released in the period from 1982 to 1999, were evaluated across three years 2002-2004 at the Experimental Field Station in Czesławice near Nałęczów, Poland. The experiments were carried out on the brown soil with loess subsoil. In each year the one-replicated experimental design was used with 2 m2 plots, rows 20 cm apart, and dense sowing using about 2 cm spacing of seeds. Analyses of variance for each trait data according to the random model (both cultivars and years were assumed to be random factors) were done. To classify and characterize genotypic diversity of the cultivars for the eight traits, the pattern analysis was used. It involved both cluster analysis using Ward’s procedure with a measure of the multivariate similarity among cultivars being Squared Euclidean Distance and canonical variate analysis (CVA) on the basis of cultivar BLUPs for the original traits. Quite different groups of cultivars for the studied traits were found, specially one group was substantially distanced to the others. As it was shown by CVA, spike length and number of spikelets per spike as negatively correlated with number of grains per spikelet in the studied set of the cultivars relatively largest contributed to overall differentiation of the distinguished eight groups and then, these traits best discriminated among the eight cultivar groups in the term of Mahalanobis distance for the considered traits. The 1000 grain weight and grain protein content much less contributed to overall discrimination of the cultivar groups than the previous four traits. The most important agronomic traits characterizing productivity of the spike grain weight and its two components, e.g. number of grains per spikelet and number of grains per spike had least discriminating power for the groups of cultivars. Grain yield per unit area of cereals is a result of spike grain yield and the number of spikes per unit area. In these studies of winter triticale cultivar diversity only grain spike yield and its components were included. Thus, the presented study are a primary evaluating of phenotypic diversity in the cultivars. The further study on the cultivar diversity evaluation for grain yield per unit area and its components is necessary...
Keywords:
canonical variate analysis, cluster analysis, cultivars, principal component analysis, spike traits, winter triticaleAuthors
Wanda KociubaIinstitute of Genetics, Breeding and Plant Biotechnology, University of Life Sciences, Lublin, Poland Poland
Authors
Wiesław MądryDepartment of Experimental Dcsign and Bioinformatics, University of Life Sciences, Warsaw, Poland Poland
Authors
Aneta KramekIinstitute of Genetics, Breeding and Plant Biotechnology, University of Life Sciences, Lublin, Poland Poland
Authors
Krzysztof UkalskiDepartment of Experimental Dcsign and Bioinformatics, University of Life Sciences, Warsaw, Poland Poland
Authors
Marcin StudnickiDepartment of Experimental Dcsign and Bioinformatics, University of Life Sciences, Warsaw, Poland Poland
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