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Mariotti, J.A., Chavanne, E.R., and Cuenya, M.I. (1990) Estimation of Number of Effective Factors (“Loci”) which Determine the Genotype Variability of Brix in Sugarcane (Saccharum spp.). Sugarcane, 3, 7-11.

has been cited by the following article:

  • TITLE: Genetic Diversity of Quantitative Traits of Sugarcane Genotypes in Ethiopia

    AUTHORS: Esayas Tena, Firew Mekbib, Amsalu Ayana

    KEYWORDS: ANOVA, Cluster Analysis, Local and Introduced Sugarcane Genotypes, PCA

    JOURNAL NAME: American Journal of Plant Sciences, Vol.7 No.10, July 29, 2016

    ABSTRACT: Information about the amount and distribution of genetic variation in germplasm collections is important for their efficient management and effective utilization in plant breeding. Therefore this study was conducted to assess genetic diversity of sugarcane germplasm in Ethiopia. An experiment comprising of 400 sugarcane genotypes (174 local and 226 introduced) was conducted between March 2012 and October 2013 at Wonji and Metehara Sugar Estates using partial balanced lattice design with two replications. Data was recorded on 21 quantitative characters which included cane yield and its components, sugar yield and sugar quality traits. ANOVA portrayed highly significant differences (P 2 values ranging from 2.16 - 10.60 and inter cluster from 7.24 - 5864. There were six principal components accounting for 79.26% of the total variation in the tested materials. Millable stalk count, single cane weight, stalk diameter, cane yield, sugar yield and sugar quality traits showed high positive loading on the first two PCs and accounted for most of the variation observed among the genotypes. Therefore, this study suggested that the important characters responsible for diversity in the sugarcane genotypes could be grouped in two principal components namely “Yield” and “Quality” with “Yield” traits being comparatively more important than “Quality”. Genotypes clustered for high mean values of various traits could be exploited for further improvement of the crop either through selection or through hybridization. The clusters having high mean value for yield could be selected for yield per se as well.