HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Ducroco, V. Articles by Quaas, R. L. Search for Related Content PubMed Articles by Ducroco, V. Articles by Quaas, R. L.

Prediction of Genetic Response to Truncation Selection Across Generations

Department of Animal Science, Cornell University, Ithaca, NY 14853

ABSTRACT

When generations overlap, a relationship exists between the age of the parents and their average genetic merit. Therefore, prediction of genetic gains should not be computed as if all parents belonged to a homogenous distribution. When an optimal selection rule of truncation selection across distributions is applied in this case, a simple method described in this paper can be used to compute adequate selection differentials. Possible applications of this method are the calculation of the asymptotic yearly genetic gain and yearly prediction of average genetic values for all age groups—or"cohorts"—following the implementation of a new selection scheme. To illustrate these two points, a typical dairy AI breeding plan was modelled. The numerical example shows that the population inventory approach is a more powerful tool than the asymptotic genetic gain for comparisons of breeding plans.

¹ Permanent address: Station de Génétique Quantitative et Appliquée, C.N.R.Z., Institut National de la Recherche Agronomique, 78350 Jouy-en-Josas, France.

This article has been cited by other articles:

				M. J. M. Rutten, P. Bijma, J. A. Woolliams, and J. A. M. van Arendonk SelAction: Software to Predict Selection Response and Rate of Inbreeding in Livestock Breeding Programs J. Hered., November 1, 2002; 93(6): 456 - 458. [Full Text] [PDF]