Application of principal component analysis to yield and yield related traits to identify sweet potato breeding parents 01

During phenotypic evaluation of crop plants many traits are simultaneously evaluated. These traits are often highly interrelated, evaluation of all these traits is costly and may not enhance selection response. The objectives of this study were to use Principal Component Analysis (PCA) to identify representative traits for phenotypic characterization of sweet potato, and thereby to identify superior clones for breeding. Fifty four sweet potato genotypes were field evaluated using 26 phenotypic traits under a 9 x 6 unbalanced alpha lattice design with three replications at the Karama and Rubona Research Stations in Rwanda. The PCA identified seven principal components (PC) that explained 77.83% of total variation present in the genotypes. Nineteen useful traits were identified as the main traits for effective phenotypic characterization of sweet potato, showing high correlations with the seven PCs. Genotypic variance had the greatest contribution to the total sources of variation for flowering rate (65.3%), yield of storage root (52.4%), vine yields (62.8%), total biomass (56.3%), harvest index (61.1%), weight of biggest root (50.6%) and dry matter content (57.5%). Genotypes 8-1038, Kwezikumwe and K513261 were identified as high yielding with the greatest flowering ability, while OTADA 70, 9-486, Purple 297, 2005-146, 8-1039, NASPOT 9, 2005-020, Newkaogo, 440163 and OTADA 24 were all high yielders of both storage roots and vines. The identified principal traits and genotypes may be useful in sweet potato breeding in Rwanda and similar agro-ecologies.