Random regression models for genetic analysis of milk, fat, and protein yields in the Murciano-Granadina goats with the Legendre polynomials and B-spline functions
摘要
In the present study, test-day records of milk yield (TDMY), fat yield (TDFY), and protein yield (TDPY) of first-parity Murciana-Granadina goats, collected from 2017 to 2024 in the southern part of Kerman province of Iran, were used. The traits were analyzed by applying random regression models (RRMs) with the Legendre polynomials (LEG) and B-spline (BSP) functions. The RRM with order 3 for direct genetic and animal permanent environmental effects under the LEG function was the best for TDMY. The RRMs employing quadratic BSP functions with 5 and 4 knots were determined as the most suitable models for TDFY and TDPY, respectively. The heritability