Abstract
In Ethiopian Biodiversity Institute Gene bank, large collections of maize germplasm are not yet characterized for the magnitude of genetic variability from each other. Although, knowing the contribution of individual a character 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 an Augmented Design in seven blocks at Arsi Negele in the 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, a 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 a recorded eigenvalue of 1.63 and maintained 18.11% of the total variation and related to diversity among genotypes due to ear per plant (EPP). Moreover, principal components 3 to 9 were shown to have 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.
Highlights
Maize (Zea mays L.) is one of the popular crops grown in the world, ranking second to wheat and followed by rice [1]
Twenty randomly selected plants were used for recording observations on days to flowering, plant height, ear height, ear per plant, days to maturity, ear length and kernel rows per ear, a thousand grain weight, and yield per plot
Simple correlation coefficients confirmed that yield per plot recorded highly significant positive correlations among plant height, ear length, and thousand grain weight, and maintained positive significant correlation among days to flower, ear height, days to maturity, and kernel rows per ear
Summary
Maize (Zea mays L.) is one of the popular crops grown in the world, ranking second to wheat and followed by rice [1]. It occupies an important position in the world economy as food, feed, and industrial grain crop. Bringing improvement over existing crop varieties is a continuous process in plant breeding To achieve this objective, the breeder has to identify diverse parents having superior genetic variability for combining desirable characters. Principal component analysis (PCA) and cluster analysis have been shown to be very useful in selecting genotypes for breeding programs that meet the objective of a plant breeder [4]. Cluster analysis is commonly used to study genetic diversity and for Solomon Mengistu: Maize Germplasm Characterization Using Principal
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