Optimal allocation of resources considering two sexes and selection in two stages [mass selection, multi-stage selection, two-stage selection]

• Published in: Genetics selection evolution (Paris) Vol. 28; no. 1; pp. 3 - 21
• Main Authors: Wade, C.M. (University of Queensland, Brisbane (Australie). Department of Farm Animal Medicine and Production), James, J.W
• Format: Journal Article
• Language: English
• Published: Les Ulis EDP Sciences 15.03.1996; BioMed Central Ltd; BioMed Central
• Subjects: ANIMAL DOMESTIQUE; ANIMALES DOMESTICOS; Animals; Biological and medical sciences; Classical genetics, quantitative genetics, hybrids; COSTOS; COSTS; COUT; DOMESTIC ANIMALS; Fundamental and applied biological sciences. Psychology; Genetics of eukaryotes. Biological and molecular evolution; REPONSE A LA SELECTION; REPUESTA A LA SELECCION; SELECCION; SELECTION; SELECTION RESPONSES; SEX; SEXE; SEXO; Vertebrata; Genetic gain; Animal; Genetic improvement; Sex; Artificial selection; Method; Mass selection; Statistical simulation; Optimization
• ISSN: 0999-193X; 1297-9686; 1297-9686
• DOI: 10.1186/1297-9686-28-1-3

The distribution of limited testing resources between sexes and stages of selection was optimised for breeding structures employing one- or two-stage selection. The use of incomplete sampling was considered. Measurement expenditure generally favoured the sex subject to the highest selection intensity. Within a sex, the optimal intensity of measurement was dependent upon the proportion of available candidates required for breeding and on the level of available funding. It was optimal to test all of the available candidates when more than 40% was required for breeding. Single-stage selection was favoured when selection intensity was low and when the funding limit was high. The allocation of resources between stages of selection was complex. Results are expressed graphically for different relationships between measurement cost and selection accuracy, for a range of selection intensities in each sex, and for a range of funding limitations. The methods are applicable to any livestock industry where multi-stage selection is utilised and where a relationship between measurement cost and accuracy can be ascertained. A numerical illustration pertinent to a wool sheep breeding scheme is examined.