Abstract
Accurate estimates of genetic parameters are essential for genetic improvement of milk yield in dairy cattle and for setting up breeding programmes. Estimates of genetic parameters from test-day models, particularly for Holstein Friesian cattle maintained in tropical environments, are scant in the literature. The objective of this study was therefore to estimate genetic parameters for milk yield by fitting a multiple-lactation random regression animal model (RRM) based on data from Ethiopian Holstein Friesian herds. Data were used from the first three lactations of cows that calved between 1997 and 2013. The data comprised 13 421 test-day milk yield records from 800 cows from two large dairy herds. Variance components were estimated using the average information restricted maximum likelihood method fitting an RRM. Heritability estimates for first, second, and third lactations ranged from 0.20 to 0.26, 0.15 to 0.27, and 0.17 to 0.28, respectively. Heritability estimates ranging from 0.15 to 0.28 indicate that effective genetic improvement should be accompanied by a corresponding improvement of the production environment. Across-lactation genetic correlations between first and second, second and third, and first and third lactations, expressed on a 305-day yield basis, were 0.88, 0.83, and 0.70, respectively. These genetic correlations, less than or equal to 0.88, indicate that different lactations are different traits. For an accurate evaluation of the genetic merit of animals for milk yield, lactations should be treated as different, but correlated traits in a multiple-lactation analysis.Keywords: Genetic correlation, heritability, Legendre polynomial, test-day model
Highlights
Multiple observations scored on a cow during lactation form a classical example of longitudinal data (Diggle et al, 1994)
Test-day records result in fewer measurements of milk yield as opposed to daily recording, and reduce the cost of milk recording compromising the accuracy of animal evaluation
Estimates of genetic parameters are essential for genetic improvement of milk yield in dairy cattle and for setting up sustainable dairy breeding programmes
Summary
Multiple observations scored on a cow during lactation form a classical example of longitudinal data (Diggle et al, 1994). Test-day records result in fewer measurements of milk yield as opposed to daily recording, and reduce the cost of milk recording compromising the accuracy of animal evaluation. This is partly because the correlation between test-day measurements of milk yield decreases as time between the measurements increases (Bilal & Khan, 2009). It allows greater flexibility in milk recording programmes (Schaeffer et al, 2000)
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