title: Modeling genetic and nongenetic variation of feed efficiency and its partial relationships between component traits as a function of management and environmental factors.
abstract: Feed efficiency (FE), characterized as the fraction of feed nutrients converted into salable milk or meat, is of increasing economic importance in the dairy industry. We conjecture that FE is a complex trait whose variation and relationships or partial efficiencies (PE) involving the conversion of dry matter intake to milk energy and metabolic body weight may be highly heterogeneous across environments or management scenarios. In this study, a hierarchical Bayesian multivariate mixed model was proposed to jointly infer upon such heterogeneity at both genetic and nongenetic levels on PE and variance components (VC). The heterogeneity was modeled by embedding mixed effects specifications on PE and VC in addition to those directly specified on the component traits. We validated the model by simulation and applied it to a joint analysis of a dairy FE consortium data set with 5,088 Holstein cows from 13 research stations in Canada, the Netherlands, the United Kingdom, and the United States. Although no differences were detected among research stations for PE at the genetic level, some evidence was found of heterogeneity in residual PE. Furthermore, substantial heterogeneity in VC across stations, parities, and ration was observed with heritability estimates of FE ranging from 0.16 to 0.46 across stations.
authors.affiliation: Department of Animal Science, Michigan State University, East Lansing 48824.
authors.forename: Y
authors.initials: Y
authors.lastname: Lu
authors.affiliation: Department of Animal Science, Michigan State University, East Lansing 48824.
authors.forename: M J
authors.initials: MJ
authors.lastname: Vandehaar
authors.affiliation: Department of Animal Science, Iowa State University, Ames 50011.
authors.forename: D M
authors.initials: DM
authors.lastname: Spurlock
authors.affiliation: Department of Dairy Science, University of Wisconsin, Madison 53706.
authors.forename: K A
authors.initials: KA
authors.lastname: Weigel
authors.affiliation: Department of Dairy Science, University of Wisconsin, Madison 53706.
authors.forename: L E
authors.initials: LE
authors.lastname: Armentano
authors.affiliation: Department of Animal Sciences, University of Florida, Gainesville 32611.
authors.forename: C R
authors.initials: CR
authors.lastname: Staples
authors.affiliation: Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705.
authors.forename: E E
authors.initials: EE
authors.lastname: Connor
authors.affiliation: Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5 Canada.
authors.forename: Z
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Animal and Veterinary Sciences Group, Scottish Agricultural College (SAC), Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG, United Kingdom.
authors.forename: M
authors.initials: M
authors.lastname: Coffey
authors.affiliation: Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH Wageningen, the Netherlands.
authors.forename: R F
authors.initials: RF
authors.lastname: Veerkamp
authors.affiliation: Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH Wageningen, the Netherlands.
authors.forename: Y
authors.initials: Y
authors.lastname: de Haas
authors.affiliation: Department of Animal Science, Michigan State University, East Lansing 48824. Electronic address: tempelma@msu.edu.
authors.forename: R J
authors.initials: RJ
authors.lastname: Tempelman
mesh_terms: D000821:Animal Feed / Q000191:economics; D000818:Animals; D001499:Bayes Theorem; D002417:Cattle; D005260:Female; D007774:Lactation / Q000235:genetics*; D008892:Milk / Q000378:metabolism; D010298:Parity; D010641:Phenotype
keywords: dry matter intake; genetic correlation; heritability; hierarchical Bayesian modeling