The identification of livestock breed is a necessity for its long-term maintenance and utilisation. Principal component analysis of morphometric traits has proved successful for reduction in the number of features needed for morphological evaluation in livestock species, which keeps costs down and saves time and efforts. Eighteen body biometric traits, viz. Height at withers, Leg length, Neck length, Neck circumference, Body length, Chest girth, Abdominal girth, Face length, Face width, Ear length, Horn length, Horn base circumference, Distance between horns, Hip-bone distance, Pin-bone distance, Distance between hip and Pubis bone, Rump length and Tail length of 103 Marathwadi buffaloes were analysed by using Promax rotated PCA with Kaiser Normalization to explain body conformation. Highest correlation was observed between HW × LEG (0.77), KMO Measure of Sampling Adequacy was 0.794 while Bartlett’s test of Sphericity was significant with chi-square value of 640.494. PCA revealed five components which explained about 61.91% of the total variation. First component explained 31.05% describing general body conformation with highest loadings for BH, CG, LEG and HB. The communality ranged from 0.43 (HC) to 0.78 (FW). Total variance explained by second, third, fourth and fifth component was 10.83%, 7.34%, 6.75% and 5.92% respectively. The rotated pattern matrix showed higher loadings of NC, PG, FL for Marathwadi buffaloes. Traits having high loadings in pattern matrix had high correlation with the components under structure matrix. Present study suggested that PCA can successfully reduce the dimensionality and first PC can be used in the evaluation and comparison of body conformation in Marathwadi buffaloes.
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