Vol. 10, Special Issue 11 (2021)

Author(s):
Kapil Dev, Manjeet, SS Dhaka, AS Yadav and CS Patil

Abstract:
Data from 1997 to 2016, pertaining to production performance traits and test day milk record from TD1 TO TD10 on 862 Hadhenu cattle sired by 63 were collected from history cum pedigree sheets maintained at Cattle Breeding Farm (CBF), Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar over a period of 20 years from 1997 to 2016. Analysis of variance done by restricted maximum likelihood method of Harvey (1990) using mixed linear model in which fixed effect of period, season of calving and random effect of parity was taken into consideration. The genetic and phenotypic correlations among production performance traits were low to high ranged from -0.70 (LL and DP) to 0.99 (LMY-305 and SP) and -0.55 (MSC and DP) to 0.96 (LMY and LMY-305). The genetic and phenotypic correlations of MSC with all production performance traits were moderate to high ranged from 0.28 (SP) to 0.90 (LMY) and 0.28 (SP) to 0.90 (AMY), respectively barring some exceptions. The genetic and phenotypic correlations among test day milk yields ranged were positive and high. The highest correlations were found between contiguous test day milk records and the correlations decreased as interval between tests days increased. Genetic correlations between test day milk records and production performance traits were positive and low to high ranged from 0.01 to 0.99 except negative association ship of AFC with all test day milk records ranged from -0.38 to -0.16. Estimates of phenotypic correlations of test day milk records with all production performance traits (LMY, LMY-305, LL, PY, AMY, MCI and MSC) were significant (p<0.01), high and positive barring few exceptions. Critical appraisal among genetic and phenotypic correlations between production performance traits, it may be inferred that selection based on milk yield per day of age at second calving that had high estimates of heritability (0.50) and appreciably high genetic and phenotypic correlations with production performance traits, would not only improve production performance but also take care of reproductive performance.