Pakistan Journal of Biological Sciences · 2007 · 11 citations · 16 references
AgriculturePlant BreedingPlant SciencesGermplasm EvaluationPlant GeneticsPlant MorphologyGermplasm CharacterizationGermplasm CollectionMorphological CharacterizationCluster AnalysisCrop Genetic ResourcesMahalanobis DistanceMorphological Variation AssessmentMultivariate Classification Of GermplasmPrincipal ComponentsQuantitative CharactersStem Diameter Variation
Principal component and cluster analyses were used to evaluate the pattern of morphological variation in 122 accessions of Aegilops crassa for 14 quantitative characters. With the principal component analysis, the first five principal components with eigenvalues more than 1 contributed 69.5% of the variability amongst accessions, whereas PC6 to PC14 were less than unity. Plant height, stem diameter, spike length and number of spikelets per spike were the most important characters in the first principal component. The germplasm was grouped into five clusters using cluster analysis. Although each cluster had some specific characteristics of its own, but clusters were not clearly separated when plotted by the first two principal components. Mahalanobis distances (D2) determined that plant height, stem diameter, spike length, number of spikelets per spike, node width, seed length, seed width and flowering date characters as the most important characters in differentiating the accessions. The morphological variation of Aegilops crassa accessions obtained in this study provides useful information for the future collection and makes these genetic resources more accessible to breeders.
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TrAC Trends in Analytical Chemistry · 1991 · 808 citations
Applied Multivariate Statistical Analysis
Charles L. Dunn · Technometrics · 1989 · 507 citations