Comparison of heritability estimates of first lactation traits by different methods in Phule Triveni cattle

G S AMBHORE; AVTAR SINGH; D K DEOKAR; A K GUPTA; A K CHAKRAVARTY; R K SINGH; MANVENDRA SINGH

doi:10.56093/ijans.v86i6.59203

Authors

G S AMBHORE Cattle Breeding Farm and Dangi Cow Research Station, Igatpuri, (MAFSU)
AVTAR SINGH ICAR- National Dairy Research Institute, Karnal, Haryana 132 001 India
D K DEOKAR RCDP on cattle MPKV, Rahuri
A K GUPTA ICAR- National Dairy Research Institute, Karnal, Haryana 132 001 India
A K CHAKRAVARTY ICAR- National Dairy Research Institute, Karnal, Haryana 132 001 India
R K SINGH Bihar Veterinary College, Patna
MANVENDRA SINGH ICAR- National Dairy Research Institute, Karnal, Haryana 132 001 India

https://doi.org/10.56093/ijans.v86i6.59203

Keywords:

Heritability, LSML, Phule Triveni cattle, ST-AM, ST-SM, WOMBAT software

Abstract

The first lactation records of 493 Phule Triveni cows sired by 55 sires on production traits viz. FL300DMY, FLL, FDP and reproduction traits like AFC, FCI and FSP were collected/generated from RCDP on cattle, MPKV, Rahuri. The effect of season of calving was found significant on FL300DMY and nonsignificant on FLTMY, FLL, FDP, AFC, FCI and FSP. The effect of period of calving had highly significant effect on all the first lactation traits except FSP. The effect of age groups on FLL was found significant and nonsignificant on rest of the first lactation traits. On AFC the effect of season of birth was found nonsignificant and the period of birth had highly significant effect. The heritability estimates of FLTMY by LSML, ST-SM and ST-AM were 0.35±0.16, 0.15±0.11 and 0.18±0.07; for FL300DMY0.32±0.15, 0.23±0.12 and 0.29±0.07; for FLL 0.07±0.11,0.02±0.04 and 0.06±0.02; for FDP0.22±0.13,0.18±0.14 and 0.30±0.10; for AFC0.48±0.19, 0.07±0.08 and 0.36±0.06 ; for FCI 0.28±0.17,0.05±0.06 and 0.04±0.03; for FSP 0.25±0.17, 0.06±0.03 and 0.17±0.02, respectively. The heritability estimates of first lactation traits from single-trait animal model (ST-AM) were found more accurate and less biased than corresponding single- trait sire model (ST-SM) and LSML.

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