Skip to Main Content
Parameter-based stochastic simulation of selection and breeding for multiple traitsAuthor(s): Jennifer Myszewski; Thomas Byram; Floyd Bridgwater
Source: Gen. Tech. Rep. SRS-92. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 357
Publication Series: Miscellaneous Publication
PDF: Download Publication (34 KB)
DescriptionTo increase the adaptability and economic value of plantations, tree improvement professionals often manage multiple traits in their breeding programs. When these traits are unfavorably correlated, breeders must weigh the economic importance of each trait and select for a desirable aggregate phenotype. Stochastic simulation allows breeders to test the effects of different breeding and selection strategies without the costs associated with empirical tests. However, most available simulation programs have limited applicability because they only model the management of a single trait. To solve this problem, we are developing a parameter-based stochastic simulation program that can model a variety of multiple-trait tree improvement strategies.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- 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.
CitationMyszewski, Jennifer; Byram, Thomas; Bridgwater, Floyd. 2006. Parameter-based stochastic simulation of selection and breeding for multiple traits. Gen. Tech. Rep. SRS-92. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 357
- A spatial stochastic programming model for timber and core area management under risk of fires
- Family indices for seed-orchard selection
- A Strategy for the Third Breeding Cycle of Loblolly Pine in the Southeastern U.S.
XML: View XML