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The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials

Journal Article


Abstract


  • Modeling of cultivar × trial effects for multienvironment

    trials (METs) within a mixed model

    framework is now common practice in many

    plant breeding programs. The factor analytic

    (FA) model is a parsimonious form used to

    approximate the fully unstructured form of the

    genetic variance–covariance matrix in the model

    for MET data. In this study, we demonstrate that

    the FA model is generally the model of best fi t

    across a range of data sets taken from early generation

    trials in a breeding program. In addition,

    we demonstrate the superiority of the FA model

    in achieving the most common aim of METs,

    namely the selection of superior genotypes.

    Selection is achieved using best linear unbiased

    predictions (BLUPs) of cultivar effects at each

    environment, considered either individually or

    as a weighted average across environments. In

    practice, empirical BLUPs (E-BLUPs) of cultivar

    effects must be used instead of BLUPs since

    variance parameters in the model must be estimated

    rather than assumed known. While the

    optimal properties of minimum mean squared

    error of prediction (MSEP) and maximum correlation

    between true and predicted effects possessed

    by BLUPs do not hold for E-BLUPs, a

    simulation study shows that E-BLUPs perform

    well in terms of MSEP.

Publication Date


  • 2007

Citation


  • Kelly, A. M.., Smith, A. B., Eccleston, J. A.. & Cullis, B. R. (2007). The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials. Crop Science, 47 (3), 1063-1070.

Scopus Eid


  • 2-s2.0-34248378510

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/2100

Has Global Citation Frequency


Number Of Pages


  • 7

Start Page


  • 1063

End Page


  • 1070

Volume


  • 47

Issue


  • 3

Place Of Publication


  • United States

Abstract


  • Modeling of cultivar × trial effects for multienvironment

    trials (METs) within a mixed model

    framework is now common practice in many

    plant breeding programs. The factor analytic

    (FA) model is a parsimonious form used to

    approximate the fully unstructured form of the

    genetic variance–covariance matrix in the model

    for MET data. In this study, we demonstrate that

    the FA model is generally the model of best fi t

    across a range of data sets taken from early generation

    trials in a breeding program. In addition,

    we demonstrate the superiority of the FA model

    in achieving the most common aim of METs,

    namely the selection of superior genotypes.

    Selection is achieved using best linear unbiased

    predictions (BLUPs) of cultivar effects at each

    environment, considered either individually or

    as a weighted average across environments. In

    practice, empirical BLUPs (E-BLUPs) of cultivar

    effects must be used instead of BLUPs since

    variance parameters in the model must be estimated

    rather than assumed known. While the

    optimal properties of minimum mean squared

    error of prediction (MSEP) and maximum correlation

    between true and predicted effects possessed

    by BLUPs do not hold for E-BLUPs, a

    simulation study shows that E-BLUPs perform

    well in terms of MSEP.

Publication Date


  • 2007

Citation


  • Kelly, A. M.., Smith, A. B., Eccleston, J. A.. & Cullis, B. R. (2007). The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials. Crop Science, 47 (3), 1063-1070.

Scopus Eid


  • 2-s2.0-34248378510

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/2100

Has Global Citation Frequency


Number Of Pages


  • 7

Start Page


  • 1063

End Page


  • 1070

Volume


  • 47

Issue


  • 3

Place Of Publication


  • United States