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Theoretical and Applied Genetics

, Volume 114, Issue 8, pp 1319–1332 | Cite as

Joint modeling of additive and non-additive (genetic line) effects in multi-environment trials

  • Helena OakeyEmail author
  • Arūnas P. Verbyla
  • Brian R. Cullis
  • Xianming Wei
  • Wayne S. Pitchford
Original Paper

Abstract

A statistical approach for the analysis of multi-environment trials (METs) is presented, in which selection of best performing lines, best parents, and best combination of parents can be determined. The genetic effect of a line is partitioned into additive, dominance and residual non-additive effects. The dominance effects are estimated through the incorporation of the dominance relationship matrix, which is presented under varying levels of inbreeding. A computationally efficient way of fitting dominance effects is presented which partitions dominance effects into between family dominance and within family dominance line effects. The overall approach is applicable to inbred lines, hybrid lines and other general population structures where pedigree information is available.

Keywords

Dominance Effect Relationship Matrix Selection Index Pedigree Information Dominance Relationship 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

Thanks to the Grain Research Development Corporation (GRDC) who fund the research of Helena Oakey through a Grains Industry Research Scholarship. Arūnas Verbyla and Brian Cullis also thank GRDC for support through the National Statistics Program, key program 3. We would also like to thank the Associate Editor and two anonymous referees for their constructive comments and suggestions.

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Helena Oakey
    • 1
    Email author
  • Arūnas P. Verbyla
    • 1
  • Brian R. Cullis
    • 2
  • Xianming Wei
    • 3
  • Wayne S. Pitchford
    • 4
  1. 1.School of Agriculture, Food and WineThe University of AdelaideGlen OsmondAustralia
  2. 2.Biometrics, NSW Department of Primary IndustriesWagga Wagga Agricultural InstituteWagga WaggaAustralia
  3. 3.BSES LtdMackay Central Sugar Experiment StationMackay Mail CentreAustralia
  4. 4.School of Agriculture, Food and WineThe University of AdelaideRoseworthyAustralia

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