title: Estimation of genetic parameters for milk yield across lactations in mixed-breed dairy goats.
abstract: Currently, breeding values for dairy goats in the United Kingdom are not estimated and selection is based only on phenotypes. Several studies from other countries have applied various methodologies to estimate breeding values for milk yield in dairy goats. However, most of the previous analyses were based on relatively small data sets, which might have affected the accuracy of the parameter estimates. The objective of this study was to estimate genetic parameters for milk yield in crossbred dairy goats in lactations 1 to 4. The research was based on data provided by 2 commercial goat farms in the United Kingdom comprising 390,482 milk yield records on 13,591 dairy goats kidding between 1987 and 2012. The population was created by crossing 3 breeds: Alpine, Saanen, and Toggenburg. In each generation, the best-performing animals were selected for breeding and, as a result, a synthetic breed was created. The pedigree file contained 28,184 individuals, of which 2,414 were founders. The data set contained test-day records of milk yield, lactation number, farm, age at kidding, and year and season of kidding. Data on milk composition was unavailable. Covariance components were estimated with the average information REML algorithm in the ASReml package (VSN International Ltd., Hemel Hempstead, UK). A random regression animal model for milk yield with fixed effects of herd test day, year-season, and age at kidding was used. Heritability was the highest at 200 and 250d in milk (DIM), reaching 0.45 in the first lactation and between 0.34 and 0.25 in subsequent lactations. After 300 DIM, the heritability started decreasing to 0.23 and 0.10 at 400 DIM in the first and subsequent lactations, respectively. Genetic correlation between milk yield in the first and subsequent lactations was between 0.16 and 0.88. This study found that milk yields in first and subsequent lactations are highly correlated, both at the genetic and phenotypic level. Estimates of heritability for milk yield were higher than most of the values reported in the literature, although they were in the range reported in this species. This should facilitate genetic improvement for the population studied as part of a broader multi-trait breeding program.
authors.affiliation: Animal & Veterinary Sciences, Scotland's Rural College, Easter Bush, Midlothian EH25 9RG, United Kingdom. Electronic address: sebastian.mucha@sruc.ac.uk.
authors.forename: S
authors.initials: S
authors.lastname: Mucha
authors.affiliation: Animal & Veterinary Sciences, Scotland's Rural College, Easter Bush, Midlothian EH25 9RG, United Kingdom.
authors.forename: R
authors.initials: R
authors.lastname: Mrode
authors.affiliation: Animal & Veterinary Sciences, Scotland's Rural College, Easter Bush, Midlothian EH25 9RG, United Kingdom.
authors.forename: M
authors.initials: M
authors.lastname: Coffey
authors.affiliation: Animal & Veterinary Sciences, Scotland's Rural College, Easter Bush, Midlothian EH25 9RG, United Kingdom.
authors.forename: J
authors.initials: J
authors.lastname: Conington
mesh_terms: D000822:Animal Husbandry; D000818:Animals; D001947:Breeding; D003433:Crosses, Genetic; D003612:Dairying; D005260:Female; D006041:Goats / Q000235:genetics* / Q000502:physiology; D007774:Lactation / Q000235:genetics*; D008892:Milk / Q000378:metabolism*; D010641:Phenotype; D012044:Regression Analysis; D012621:Seasons; D006113:United Kingdom
keywords: dairy goat; milk yield; random regression