Fitting random regression model to analyze test day milk yield in Sahiwal cattle

Abstract

The present research was carried out for analyzing test day milk yield in Sahiwal cattle using random regression model (RRM). First lactation 3953 monthly test day milk yield (MTDMY) records over a period of 31 years (1986-2017) were collected on 392 cows from history cum pedigree sheets and daily milk yield register maintained at NDRI, Karnal, Haryana. The records were taken at an interval of 30 days, with first record on 6^th day and last on 305^th day. The test day milk yield data was modeled using RRM (WOMBAT) considering different order of Legendre polynomial (LP). 4^th order and 6^th order LP for the additive genetic effect and the permanent environmental effect respectively was found to be the best. The highest and lowest additive genetic variance was observed for 125^th day milk yield (2.57 kg²) and 35^th day milk yield (1.02 kg²) respectively. Its magnitude was found to be lower in the beginning and towards the end of lactation and relatively higher in the midlactation. The permanent environmental variance was observed higher during initial test days. The residual variance was lower than the permanent environment variance for all the test day milk yields. The heritability of monthly test day milk yields was found to be highest (0.33 ± 0.04) for 125^th day milk yield and the lowest (0.15 ± 0.03) for 6^th and 35^th day milk yield. The estimates of genetic correlations and permanent environment correlations between different test day milk yields ranged from 0.02 to 0.98 and from 0.27 to 0.98 respectively. The study highlights the usage of test day model analyzed through random regression model to be utilized for selecting animals at an early age.