APPLICATION OF PRINCIPAL COMPONENT ANALYSIS FOR EVALUATING FIRST LACTATION TRAITS IN CROSSBRED CATTLE

Selection based on lifetime performance is not realistically practicable due to the lengthy generation interval, hence it is desired to select animals based on the performance of earlier lactations rather than attributes that appear later in life [1].Similarly, the suitability of breeding animals in an organized herd is essentially decided by their productivity and reproductive efficiency.Due to their strong correlation, first lactation attributes are indicative of subsequent lactation outcome in both cattle and buffaloes [2].In order to effectively plan selection programme and provide information about trait variations, it is important to measure the phenotypic traits in dairy ABSTRACT: This study aimed to reduce redundancy among first lactation traits and identify key factors influencing production and reproduction in crossbred cows.Measurements were taken on 529 crossbred cattle (62.5% HF37.5% Sahiwal) over a 30-year period (1990-2019) for ten traits for first lactation (age at first calving, lactation length, milk yield for first lactation, milk yield up to 305 days, first service period, date of dry, calving interval for first lactation, peak yield, days to reach peak yield and milk yield for up to 300 days).For the traits under study, phenotypic correlations were found, and significant positive correlations varied between 0.11 to 0.81.To explain the production and reproduction of crossbred cows, varimax rotational PCA with Kaiser Normalization was applied to all ten first lactation variables.The principal component analysis yielded four components that explained 77.495% of total variance, with the first component accounting for 34.374%.The PCA results indicated that milk production traits (MY305D, MY300D, FLMY, PY) were strongly associated with Component 1, while reproductive traits (FCI, DDRY) influenced Component 2. Traits like AFC and LL defined Component 3, highlighting early maturity and lactation performance, and Component 4 reflected peak production and service period efficiency.The communality of ten distinct first lactation traits varied from 0.997 (first calving interval) to 0.470 (first service period).Hence, PCA was found to be effective in properly capturing performance patterns in crossbred cows while lowering the amount of variables required to explain reproductive and productive efficiency.