Skip to Main Content
Monte Carlo simulation models of breeding-population advancement.Author(s): J.N. King; G.R. Johnson
Source: Silvae Genetica. 42(2-3): 68-78
Publication Series: Scientific Journal (JRNL)
PDF: Download Publication (1.01 MB)
DescriptionFive generations of population improvement were modeled using Monte Carlo simulations. The model was designed to address questions that are important to the development of an advanced generation breeding population. Specifically we addressed the effects on both gain and effective population size of different mating schemes when creating a recombinant population for recurrent selection. Five different mating schemes were modeled with recurrent selection, 4 control-pollinated (CP) and one open-pollinated (OP) scheme. The CP schemes were: 2 random mating (RM) designs, 1 with 2 crosses per parent and 1 with 8 crosses per parent; and imbalanced parental contribution schemes including assortative mating (AM), and random mating with an 'elite' nucleus (EN). Genetic gain is maximized in the mating scheme that uses random mating and increases the selection differential for recombinant cross selection. The imbalanced designs (AM and EN) increased gain only slightly over random mating. The model was also used to look at the erosion of the breeding population base when applying different restrictions on selection to the CP treatments. RM offered the highest levels of gain for a given effective population size. AM was little different to RM but there was quite rapid attrition of the genetic base for on-going breeding with the EN scheme. The trade-off between maximizing short-term gain with family selection and maintaining genetic diversity for long-term potential within the framework of a fixed resource is discussed.
- Visit PNW's Publication Request Page to request a hard copy of this publication.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationKing, J.N.; Johnson, G.R. 1993. Monte Carlo simulation models of breeding-population advancement. Silvae Genetica. 42(2-3): 68-78
KeywordsAssortative mating, computer modeling, Monte Carlo simulation, genetic gain, genetic diversity
- Genetic variation in susceptibility to fusiform rust in seedlings from a wild population of loblolly pine
- Evaluating hybrid poplar rooting. II. backcross breeding method exhibits exceptional promise
- Unstable aneuploid progenies of Phytophthora ramorum
XML: View XML