Literature DB >> 24226125

Selection system efficiencies for computer simulated progeny test field designs in loblolly pine.

J A Loo-Dinkins1, C G Tauer, C C Lambeth.   

Abstract

Six simulated progeny test field designs in combination with three within-family selection systems were tested on three loblolly pine (Pinus taeda L.) progeny test sites in southeastern Oklahoma and southwestern Arkansas, to compare genetic gains for the single trait, height. Residual deviations obtained by subtraction of family and plantation mean effects for each plantation were combined with simulated genetic effects with known family variance structure. The simulated genetic populations, arranged in the following progeny test field designs - large square or almost square plots, five- and ten-tree row plots, five-tree noncontiguous plots, two tree row plots, and single-tree plots - were superimposed on the residual data for each plantation. Within-family selection methods based on deviations from block means, deviations from neighborhood means and deviations from plot means were built into the model. Realized genetic gain attained by each design - selection system combination was compared with the genetic gain theoretically possible if selection accuracy were perfect, and with expected gain estimated using the general linear model. In general, average realized genetic gain compared well with expected gain. Differences between designs with large versus small plots were generally lower than expected, although the single-tree plot design always yielded highest realized gain. Realized gain was generally higher than expected when within-family selection was based on deviations from block or neighborhood means, but equal to or lower than expected when selection was based on deviations from plot means.

Entities:  

Year:  1990        PMID: 24226125     DOI: 10.1007/BF00223792

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  5 in total

1.  Comment on "Selection system efficiencies for computer-simulated progeny test field designs in loblolly pine" J. A. Loo-Dinkins, C. G. Tauer and C. C. Lambeth.

Authors:  R D Burdon
Journal:  Theor Appl Genet       Date:  1991-01       Impact factor: 5.699

2.  Bias in genetic variance estimates due to spatial autocorrelation.

Authors:  S Magnussen
Journal:  Theor Appl Genet       Date:  1993-04       Impact factor: 5.699

3.  Variance component estimation techniques compared for two mating designs with forest genetic architecture through computer simulation.

Authors:  D A Huber; T L White; G R Hodge
Journal:  Theor Appl Genet       Date:  1994-05       Impact factor: 5.699

4.  Estimating the potential of sugarcane families to produce elite genotypes using univariate cross prediction methods.

Authors:  Y S Chang; S B Milligan
Journal:  Theor Appl Genet       Date:  1992-08       Impact factor: 5.699

5.  Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model.

Authors:  Julio G Velazco; María Xosé Rodríguez-Álvarez; Martin P Boer; David R Jordan; Paul H C Eilers; Marcos Malosetti; Fred A van Eeuwijk
Journal:  Theor Appl Genet       Date:  2017-04-03       Impact factor: 5.699

  5 in total

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