Estimation of genetic parameters related to eggshell strength using random regression models.

Area of Science:

• Animal Genetics
• Poultry Science
• Quantitative Genetics

Background:

• Eggshell quality is crucial for poultry production, impacting profitability.
• Understanding genetic parameters of eggshell strength over time is vital for breeding programs.

Purpose of the Study:

• To investigate changes in eggshell strength throughout a hen's laying period.
• To estimate genetic parameters for eggshell strength using random regression models (RRMs).
• To assess the potential of RRMs for improving eggshell quality in breeding plans.

Main Methods:

• Utilized data from 2260 crossbred hens (2011-2014) with repeated eggshell strength measurements.
• Applied random regression models with Legendre polynomials to estimate genetic and environmental effects.
• Modeled residual effects with heterogeneous variance across test weeks.

Main Results:

• Heritability estimates for eggshell strength ranged from 0.26 to 0.43.
• Repeatability estimates varied between 0.47 and 0.69.
• High genetic correlations (> 0.67) were observed between test weeks, with the first eigenvalue explaining 97% of genetic covariance.

Conclusions:

• Random regression models offer a flexible and powerful approach for analyzing eggshell strength dynamics.
• RRMs can effectively estimate genetic parameters, aiding in the selection for improved eggshell quality.
• Implementing RRM in breeding plans can help reduce economic losses associated with cracked eggs.