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Use of factor scores for determining the relationship between body measurements and semen traits of cocks

Author(s): Udeh Ifeanyichukwu

Journal: Advances in Molecular Imaging
ISSN 2161-6728

Volume: 02;
Issue: 01;
Start page: 41;
Date: 2012;
Original page

Keywords: Cocks | Factor Scores | Multiple Regression | Semen Traits

Semen evaluation is required to predict fertility. In most rural African communities, facilities for microscopic evaluation of semen are not available. Therefore, an indirect method of predicting semen traits of cocks is required by poultry farmers. The objective of this study was to use factor scores derived from factor analysis of body measurements to predict some semen traits of cocks. Correlation matrix was obtained by calculating the correlations between body measurements and semen traits of cocks. Kais-er-Meyer-Olkin (KMO) measure of sampling adequacy and Bartletts test of sphericity were used to test the appropriateness of factor analysis on the data. The extraction of the factors was done by calculating the eigenvalues of the correlation matrix. Variance maximizing rotation of the transformation matrix was done to facilitate the interpretation of the factor loadings. Two factors with eigenvalues greater than 1 were extracted which accounted for 76.96% of the variations present in the original variables. The two factors were used to obtain the factor score coefficients. When utilized as independent variables in multiple regression analysis, the two factors explained 53.20% and 40.80% of the variations in sperm motility and sperm concentration respectively. Factor 1 had more impact on sperm motility than factor 2 as it was significantly related to it. Factor 2 was significantly more related to sperm concentration than factor 1. The relationship between body measurements and semen volume, live sperm and abnormal sperm were weak and mostly negative. Therefore, they were not predicted using factor scores.

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