ESTIMATION OF GENETIC PARAMETERS OF FIRST LACTATION TEST-DAY MILK YIELD USING RANDOM REGRESSION MODELS IN IRANIAN HOLSTEIN COWS Authors: M. R. B. Behzadi, Z. Mehrpoor Journal: Journal of Animal and Plant Sciences (JAPS) ISSN: 1018-7081 (Print), 2309-8694 (Online) Volume: 28 Issue: 1 Pages: 24-32 Year: 2018 DOI: NA URL: https://doi.org/NA Publisher: Pakistan Agricultural Scientists Forum Abstract:

The objective of the present study was to estimate variance components and genetic parameters for milk yield in Iranian Holstein cows, applying Legendre polynomials func­tions in random regression models (RRM). A total of 34818 test-day (TD) records from 4033 Holstein cows in their first lactation were analyzed. The genetic parameters were estimated by restricted maximum likelihood method and average information algorithm using the WOMBAT software. Varying order of Legendre polynomials (LP) were used in random regression models. The model considering a 6th-order LP for additive genetic effect, a 5th-order LP for permanent environmental effect and a step function with 10 heterogeneous classes for residual variances (Leg65_10) is more appropriate. Heritability estimates for TD records were highest in the second half part of the lactation, ranging from 0.13 to 0.66. Genetic correlations between TD records were high for consecutive records and decreased as the interval between tests increased, and ranged from -0.41 to 0.99. Genetic correlation estimates of TD records with corresponding lactation yield were highest for mid-lactation. The first eigenfunction suggests that milk yield is mainly controlled by genes with dissimilar effects between early and late stages of lactation. The results suggested that TD yields especially in the second half part of lactation may be used for genetic evaluation.

Keywords: Genetic parameters, Holstein cows, Legendre polynomial, Random regression