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Predicting genetic gain when rates of inbreeding are constrained to pre-defined values
Published online by Cambridge University Press: 20 November 2017
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Dynamic selection algorithms using quadratic indices to optimise the contributions of selection candidates for maximising rates of genetic gain (ΔG) while constraining the rate of inbreeding (ΔF) in the long-term to pre-defined values, are available (Grundy et al, 1998). Avendaño et al (2001 a,b) applied these optimal selection algorithms on the UK Meatlinc (sheep) and Aberdeen Angus (beef cattle) pedigree breeds and found substantial expected increases (of at least 17%) in the average index score at the observed ΔF. Although these algorithms constitute powerful operational tools for breeding schemes, the framework for deterministically predicting ΔG under optimal selection with restricted ΔF is not yet available. This study presents a novel approach to this problem.
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- Copyright © The British Society of Animal Science 2003