Abstract

The present study was aimed at reduction in dimensionality using principal component analysis of 16 linear udder type traits and to identify those components having strongest relationship with milk production traits and clinical mastitis in Karan Fries cattle. Kaiser statistic for sampling adequacy with a lower limit of 0.50, and Bartlett’s sphericity test was used to determine the adequacy of variables for use in factor analysis. Components were chosen based on auto values greater than one and scree test. The relationship of these principal components with milk production traits was analysed using the general linear model and effect of the components on the incidence of clinical mastitis were analysed through binomial logistic regression model. The general mean value of KMO was obtained as 0.695, indicated the existence of true factors. Five principal components were extracted using Kaiser Rule criterion contributing 70.11% of the cumulative variance between the linearudder type traits. The communality ranged from 0.277 (udder balance) to 0.879 (distance between rear teats) for all these 16different udder type traits. The relation between principal component 1 and 305-day milk yield was positive and significant with a non-significant effect for 305-day milk-fat (305 DF), milk-protein (305 DP) and Solids not fat yield (305 DSNF). The principal component 1 was also found to have a significant effect on incidence of clinical mastitis. Results of PCA suggest that the use of orthogonal synthetic variables principal component one(PC1), two (PC2) and three (PC3) provided a means of reduction in the number of linear udder type traits to be recorded in Karan Fries cattle which could explain the whole udder biometric traits. The PC1 can be used in breeding programmes as a means to explain the mammary system for better milk production with lesser incidence of clinical mastitis in Karan Fries dairy cows.

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