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Maize Germplasm Characterization Using Principal Component and Cluster Analysis

Abstract

In Ethiopian Biodiversity Institute Gene bank, huge collections of maize germplasm are not yet characterized for the magnitude of genetic variability from each other. Though knowing the contribution of individual characters is essential to focus on particular characters in cultivar development. Hence, this experiment was conducted on 92 maize accessions which were not yet characterized and 2 local checks to estimate the magnitude of genetic diversity among the genotypes and to identify the major agro-morphological characters contributing for the observed variations. The experiment was arranged in Augmented Design in seven blocks at Arsi-Negele in 2016 main cropping season. The characters used for analysis were days to flowering, plant height, ear height, ear per plant, days to maturity, ear length, kernel rows per ear, thousand grain weight and yield per plot. The 94 genotypes were grouped into four clusters where cluster I, II, III and IV comprised 30, 21, 23 and 20 genotypes respectively. Early matured and short genotypes were grouped in cluster IV, late matured in cluster II and high yielding and tall genotypes in cluster I. The principal component analysis indicated that the first principal component (PC1) had an eigenvalue of 4.4 and reflects 48.85% of the total variation, this represents the equivalent of two individual variables and the two variables that weighted higher than the other variables are plant height and ear length. The second principal component (PC2) was recorded eigenvalue of 1.63 and maintaining 18.11% of the total variation and related to diversity among genotype due to ear per plant (EPP). Moreover, principal components 3 to 9 were showed more than one eigenvalue, thus they represent equivalent of one individual variable each accounted for 0.98%, 0.78%, 0.68%, 0.35%, 0.15%, 0.03% and 0% respectively toward the variation observed among genotypes. The result ensures the existence of high genetic divergence among the studied maize genotypes.

Solomon Mengistu

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