Genetic Gain Optimization

Genetic Gain Optimization is a computational or statistical framework designed to maximize the rate of improvement in desirable traits through selective breeding by optimally balancing selection intensity, genetic diversity, and prediction accuracy in plant and animal breeding programs.

232

Publications

11.4K

Citations

903

Authors

332

Institutions

Publications per year

2017–2026

105

Authors

903

  1. GG
    Gregor Gorjanc

    Roslin Institute, United Kingdom

    11 publications · 794 citations

    11

    h-index

  2. JW
    John Woolliams

    Roslin Institute, United Kingdom

    11 publications · 280 citations

    11

    h-index

  3. TM
    T.H.E. Meuwissen

    Norwegian University of Life Sciences, Norway

    11 publications · 1.3K citations

    10

    h-index

  4. BV
    Beatriz Villanueva

    Scottish Agricultural Science Agency, United Kingdom

    8 publications · 195 citations

    8

    h-index

  5. BJ
    Ben J. Hayes

    The University of Queensland, Australia

    7 publications · 441 citations

    7

    h-index

1–5 of 903

Venues

  1. Crop Science

    13 publications · 1.5K citations

    13

    h-index

  2. Theoretical and Applied Genetics

    13 publications · 633 citations

    12

    h-index

  3. Genetics Selection Evolution

    GSE · 14 publications · 413 citations

    12

    h-index

  4. G3 Genes Genomes Genetics

    11 publications · 472 citations

    11

    h-index

  5. Journal of Dairy Science

    JDS · 10 publications · 468 citations

    10

    h-index

1–5