A segmented line regression procedure to describe growth in beef cows

Area of Science:

• Animal Science
• Quantitative Genetics
• Beef Cattle Production

Background:

• Understanding cattle growth dynamics is crucial for optimizing breeding and management strategies.
• Polled Hereford females exhibit complex growth patterns influenced by multiple factors.

Purpose of the Study:

• To model the growth curve of Polled Hereford female cattle using segmented linear regression.
• To identify key factors affecting growth traits and rates of gain throughout development.

Main Methods:

• Simultaneous fitting of three segmented linear regression lines to model weight as a function of age.
• Analysis of sire and year of birth effects on growth parameters.
• Calculation of genetic correlations between weights and degrees of maturity at different ages.

Main Results:

• Sire and year of birth significantly impacted early growth traits before 17 months of age.
• Genetic correlations for weight and maturity were positive across all ages.
• Animals with slower growth rates achieved greater mature weights.
• Degree of maturity and weight showed a positive correlation at a given age, becoming negative with increasing age intervals.

Conclusions:

• Early life factors like sire and birth year are critical for initial growth in Polled Hereford heifers.
• Growth rate and mature weight are inversely related; slower development leads to larger mature size.
• Maturity and weight relationships evolve with age, indicating distinct growth phases.