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Aims: To study the principal component analysis (PCA) of morphological traits in Udaipuri goats. Place and Duration of Study: Pauri, Garhwal, Uttarakhand, India. Methodology: Eight traits were measured in 407 adult (doe) and (buck) goats over a period of 2021-2022. The traits considered in the study were Horn Length (HL), Face length (FL), Ear Length (EL), Height at Withers (HW), Body Length (BL), Chest Girth (CG), Tail Length (TL) and Body Weight (BW). The data were analyzed for the estimation of mean, coefficient of variation (CV %), phenotypic correlation and PCA by using the software SPSS version 24. Results: The descriptive statistics including the mean and CV % were estimated which revealed the lowest average and the highest average for horn length and chest girth, respectively. The horn length and ear length showed the highest and lowest CV %, respectively, and the phenotypic correlations were significant (P<0.01) for all the characters included in the study. Principal component analysis (PCA) with varimax rotation method was applied and extracted a total variation of 66.01%. In all adult males and females, HL, HW, BL and CG were loaded as first component while FH, EL, TL and BW were loaded as second component. Conclusion: Therefore, these findings indicated that PCA could serve as a valuable tool in breeding programmes, allowing for a significant reduction in the number of traits while still effectively capturing morphometric trends in Udaipuri goats.
Sarma et al. (Mon,) studied this question.