title: Breeding for profit: synergism between genetic improvement and livestock production (a review).
abstract: Fifty years of research in animal breeding and genetics are examined from four perspectives: 1) genetic prediction, 2) animal testing and selection schemes, 3) dissemination of genetic improvement, and 4) definition of breeding objectives in economic form. Breeding in all classes of livestock has moved from a purebred appearance orientation to a performance (either purebred or crossbred) orientation. Unfortunately, the evolution from a performance orientation to an economic orientation is incomplete, especially for some livestock classes. Placing breeding objectives into a mathematical form on a sound economic basis is key to integrating modern developments in animal breeding into more purposeful industry programs. Procedures used to develop such objectives are reviewed with attention to common approaches. Where consensus is reached about a breeding objective (in economic form) for a class of livestock, this objective can be used in conjunction with genetic predictions to rank animals within a breeding population. Ranking without undue attention to herd of origin facilitates a pyramid-shaped hierarchy of animals that can be fundamental to the functioning of breeding enterprises contributing improvements to operations concerned with production. Genetic improvements should flow from proven genetically superior animals to improved production systems. The tiers of the pyramid need to be organized relative to animals with differing levels of economic evaluation.
authors.affiliation: ARS, USDA, Roman L. Hruska U.S. Meat Animal Research Center, Clay Center, NE 68933-0166.
authors.forename: D L
authors.initials: DL
authors.lastname: Harris
authors.forename: S
authors.initials: S
authors.lastname: Newman
mesh_terms: D000822:Animal Husbandry / Q000191:economics*; D000818:Animals; D000829:Animals, Domestic / Q000235:genetics* / Q000502:physiology; D001947:Breeding / Q000191:economics*; D005838:Genotype; D012106:Research; D012641:Selection, Genetic