Characterization of Beef from Cross-bred Cows Using Principal Component Analysis

The current study was undertaken to evaluate various quality attributes of beef from cross-bred dairy cows and to characterize it using principal component analysis (PCA). Ten different muscles each from six culled cross-bred cows (Holstein Friesian x Jersey, four to six years old) were analysed for 22 variables including physico-chemical, compositional and sensory attributes. The coefficients of variation of different attributes were found to range from 0.9 to 58.41 per cent. PCA transformed the variables into eight principal components (PCs) which explained more than 79.53 per cent of total variability. PC1 accounted for 19.37 per cent of total variability and it comprised of sensory attributes (excluding appearance and flavour), shear force, collagen content and collagen solubility. PC2 was characterized by b* and chroma. Loading plots of the first two PCs revealed high correlation between most of the eating quality attributes. Shear force, myofibril fragmentation index and collagen content formed another group of highly correlated variables. The study has revealed that PCA can be effectively used for interpretation of large amount of data generated in studies like quality profiling of beef from cross-bred dairy cows.