Principal Component Analysis of Major Biometric Traits and Indices of Indigenous Sheep Ewe Populations, and Relationships with their Body Weights

The field data collection was performed before the war (before October 2020) in Tigray Region, Ethiopia. The principal component analysis (PCA) is a grouping of variables or dimension reduction technique. The objective of this study was to characterize and identify the most underlying biometric traits and biometric indices of the indigenous sheep ewe populations, and determine the relationships of morphometric traits and morphometric indices with the body weights of the ewe populations. Sample animals of Begait (160), Rutanna (129) and Arado (156) ewe populations which totaled 445 with permanent pair of incisors (1PPI-4PPI) were randomly involved in the field data collection. Statistical Package for Social Sciences software was used for statistical data analysis. The PCA of the morphometric traits (09) extracted two principal components (PCs) in Begait ewes, two PCs in Rutanna ewes and one PC in Arado ewes, and the PCA of the morphometric indices (20) extracted five PCs in Begait ewes, six PCs in Rutanna ewes and five PCs in Arado ewes. The compact index mainly indicated that Rutanna and Begait ewes are larger in size and suitable for mutton production whilst Arado ewes are suitable for milk production. The correlations among the biometric traits and the body weights of the ewe populations were highly significantly (P<0.01) different except the correlation between body weight and rump length of Rutanna ewes (P<0.05). The biometric indices which consisted of height index, cephalic index, longitudinal pelvic index, height slope, over increase index, body ratio, foreleg length of the three ewe populations and their body weights were with little or no correlations (P>0.05). Genetic characterizations of the indigenous (Begait and Arado) and the transboundary (Rutanna) sheep populations should be complemented to confirm and distinguish the purpose of the populations.