title: Genetic associations between feed efficiency measured in a performance test station and performance of growing cattle in commercial beef herds.
abstract: Interest in selection for improved feed efficiency is increasing, but before any steps are taken toward selecting for feed efficiency, correlations with other economically important traits must first be quantified. The objective of this study was to quantify the genetic associations between feed efficiency measured during performance testing and linear type traits, BW, live animal value, and carcass traits recorded in commercial herds. Feed efficiency data were available on 2,605 bulls from 1 performance test station. There were between 10,384 and 93,442 performance records on type traits, BW, animal value, or carcass traits from 17,225 commercial herds. (Co)variance components were estimated using linear mixed animal models. Genetic correlations between the muscular type traits in commercial animals and feed conversion ratio (-0.33 to -0.25), residual feed intake (RFI; -0.33 to -0.22), and residual BW gain (RG; 0.24 to 0.27) suggest that selection for improved feed efficiency should increase muscling. This is further evidenced by the genetic correlations between carcass conformation of commercial animals and feed conversion ratio (-0.46), RFI (-0.37), and residual BW gain (0.35) measured in performance-tested animals. Furthermore, the genetic correlations between RFI and both ultrasonic fat depth and carcass fat score (0.39 and 0.33, respectively) indicated that selection for improved RFI will result in leaner animals. It can be concluded from the genetic correlations estimated in this study that selection for feed efficiency will have no unfavorable effects on the performance traits measured in this study and will actually lead to an improvement in performance for some traits, such as muscularity, animal price, and carcass conformation. Conversely, this suggests that genetic selection for traits such as carcass quality, muscling traits, and animal value might also be indirectly selecting for more efficient animals.
authors.affiliation: Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland.
authors.forename: J J
authors.initials: JJ
authors.lastname: Crowley
authors.forename: R D
authors.initials: RD
authors.lastname: Evans
authors.forename: N
authors.initials: N
authors.lastname: Mc Hugh
authors.forename: T
authors.initials: T
authors.lastname: Pabiou
authors.forename: D A
authors.initials: DA
authors.lastname: Kenny
authors.forename: M
authors.initials: M
authors.lastname: McGee
authors.forename: D H
authors.initials: DH
authors.lastname: Crews
authors.forename: D P
authors.initials: DP
authors.lastname: Berry
mesh_terms: D000818:Animals; D001823:Body Composition / Q000235:genetics / Q000502:physiology; D001835:Body Weight / Q000235:genetics / Q000502:physiology; D002417:Cattle / Q000235:genetics / Q000502:physiology*; D004435:Eating / Q000235:genetics / Q000502:physiology*; D005838:Genotype; D008297:Male; D008460:Meat / Q000191:economics*; D018482:Muscle, Skeletal / Q000000981:diagnostic imaging / Q000502:physiology*; D010641:Phenotype; D019655:Quantitative Trait, Heritable; D012044:Regression Analysis; D012641:Selection, Genetic; D014463:Ultrasonography