Genetic parameters of estimated net energy efficiencies for milk production, maintenance, and body weight change in dairy cows.
Net efficiencies of converting intake energy into energy for maintenance, milk production, and body weight change in a lactation were estimated for each of 79 Holstein cows by a two-stage multiple regression model. Cows were from 16 paternal half-sib families, which each had members in at least two of the six herds. Each cow was recorded for milk yield, net energy intake, and three efficiency traits. These were analyzed in a multitrait model containing the same 14 fixed subclasses of herd by season by parity and a random factor of sires for each of the five traits. Restricted maximum likelihood estimates of sire and residual (co)variance components were obtained by an expectation maximization algorithm with canonical transformations. Between milk yield and net energy intake, net energy efficiencies for milk yield, maintenance, and body weight change, the estimated phenotypic correlations were .36, -.02, .08, and -.06, while the genetic correlations were .92, .56, .02, and -.32, respectively. Both genetic and phenotypic correlations were zero between net energy efficiency of maintenance and that of milk yield and .17 between net energy efficiency of body weight change and that of milk yield. The estimated genetic correlation between net efficiency for lactation and milk yield is approximately 60% of that between gross efficiency and milk yield. With a heritability of .32 equivalent.49, net energy efficiency for milk yield may be worth consideration for genetic selection in certain dairy cattle populations.
Buttazzoni
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Department of Animal Science, Michigan State University, East Lansing 48824-1225.
Mao
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D000818:Animals; D001835:Body Weight; D002417:Cattle / Q000235:genetics* / Q000502:physiology; D004435:Eating; D004734:Energy Metabolism; D005260:Female; D007774:Lactation; D008954:Models, Biological; D015233:Models, Statistical; D010641:Phenotype; D011247:Pregnancy; D012044:Regression Analysis