Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle

Area of Science:

• Animal Breeding and Genetics
• Dairy Science
• Quantitative Genetics

Background:

• Test-day milk yield (TDMY) is crucial for dairy cattle genetic evaluations.
• Understanding genetic parameters for milk yield and persistency is vital for improving dairy herds.
• Girolando cattle present unique genetic characteristics for dairy production.

Purpose of the Study:

• To estimate genetic parameters for test-day milk yield (TDMY) in Girolando cows.
• To evaluate different measures of milk yield persistency (PSi) and their genetic trends.
• To determine the optimal random regression model (RRM) for genetic analysis of milk production traits.

Main Methods:

• Utilized 32,817 TDMY records from 4,056 Girolando cows across 118 herds (2000-2011).
• Employed random regression models (RRM) with Legendre's polynomial functions (orders 3-5) to model lactation curves.
• Evaluated nine persistency measures (PSi) and genetic trends for 305-day milk yield (305MY).

Main Results:

• The best RRM used Legendre's polynomial orders 3 and 5 for additive genetic and permanent environmental effects.
• Heritability for TDMY ranged from 0.18 to 0.23; genetic correlations varied from -0.03 to 1.00.
• Heritability for persistency and 305MY ranged from 0.10 to 0.33; genetic correlations ranged from -0.98 to 1.00.
• PS7 was identified as the most suitable measure for milk persistency evaluation in Girolando cattle.
• Significant positive genetic trends were observed for 305MY in sires and cows.

Conclusions:

• The selected RRM provides accurate genetic parameter estimates for Girolando milk yield.
• PS7 is recommended for selection indices to improve milk persistency in Girolando cattle.
• Selection indices are advised for genetic improvement of both milk yield and persistency in this breed.