Principal Component Analysis of Morphometric Traits in Kashmir Merino Sheep
Olympica Sarma, Mubashir Ali Rather, Syed Shahnaz, R S Barwal
Journal of Advances in Biology & Biotechnology · pp. 362–369 · Published 28 Aug 2024
10.9734/jabb/2024/v27i91306Abstract
Aims: To study the principal component analysis (PCA) of morphometric traits in Kashmir Merino sheep Place and Duration of Study: Sheep Breeding Farm, Kralpathri, Kashmir, India and 2019. Methodology: This study was preformed to evaluate the morphometric traits of 518 Kashmir Merino sheep in Jammu & Kashmir under a multivariate approach. The body measurements included in the study were face length (FL), ear length (EL), ear width (EW), body length (BL), body height (BH), chest girth (CG), paunch girth (PG), tail length (TL), horn length (HL) and body weight (BW). Principal component analysis (PCA) was performed to define body shape upon the correlation matrix of the ten body measurements. Results: Principal component analysis with varimax rotation method was applied and extracted four principal components with a total variation of 64.29 %. The first principal component accounted for 28.28% of the total variance and was interpreted as a measure of CG, PG, BL and BH. The second factor which explained 12.56 % of the generalized variance tended to describe TL and HL, while the third factor explained 11.88 % of total variance which showed high loadings for BW. The fourth factor was influenced by FL and EW which explained 11.56 % of total variance. Conclusion: Therefore, these findings suggest that incorporating PCA in breeding programs could significantly enhance the genetic improvement of Kashmir Merino sheep, leading to better growth performance, increased body size, and improved productivity.
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