Open AccessANALYSIS OF VARIATION AMONG GENOTYPES OF FLUTED PUMPKIN (TELFAIRIA OCCIDENTALIS HOOK. F) USING FACTOR ANALYSIS AND PRINCIPAL COMPONENT ANALYSIS (PCA)
Author(s) -
Ifeoma Sussan Ezenwata,
Regland Michael Onyemeka,
Sunday Clement Olubunmi Makinde,
Chiamaka Frances Anyaegbu,
Rachael Chinweoke Ogbuoka,
O. S. Oyetunji
Publication year - 2019
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2019.v04i07.035
Subject(s) - principal component analysis , hook , component analysis , biology , variation (astronomy) , pumpkin seed , genotype , botany , mathematics , statistics , food science , engineering , genetics , gene , physics , structural engineering , astrophysics
This study aimed at investigating genetic divergence in twenty genotypes of fluted pumpkin (Telfairia occidentalis) and determines the characters responsible for the variation. The twenty genotypes were collected from different locations within southern Nigeria (Anambra, Enugu, Lagos, Ondo and Ogun). The experiment was carried out at the Lagos State University Botanical Garden using a Randomized Block Design (RBD) with three replications. The collected data were subjected to Principal Component Analysis (PCA) and Factor Analysis to evaluate the patterns of variation in these genotypes. Two out of the twenty four principal components had eigen values greater than 2.0. The first five principal component jointly accounted for 88.61% of the total variation among the genotypes. Twenty factors were identified. The first two factors had eigen value of 5.28 and 2.05 respectively while only four factors accounted for 81.47% of the total variance. The two analysis methods indicated vine length, leaf size, number of branches, vine diameter, number of leaves, petiole length as traits that contributed more to the total variation observed and as such can be used in discriminating among the genotypes. Configurations of the 20 genotypes along the first three principal component axes shows that L4, N4, N3, O1, E1, A1, N1 and A3 were most distant from all other genotypes and are high yielding in terms of vine length, number of branches and leaf size therefore can be selected directly. The complementarity effect of the principal component analysis and factor analysis, suggest the existence of genetic variability among the genotypes. Keywords— Multivariate, variability, Principal Component Analysis, Factor Analysis.