Feed Prediction Models

Feed Prediction Models is a computational framework within precision feeding systems that uses empirical data and algorithmic techniques to forecast individual animal feed intake and nutritional requirements, distinguishing it from general feeding guidelines by enabling personalized, real-time dietary recommendations based on dynamic physiological and environmental indicators.

51

Publications

1.8K

Citations

177

Authors

84

Institutions

Publications per year

2017–2026

15

Authors

177

  1. DP
    Dolores Pérez‐Marín

    University of Córdoba, Spain

    4 publications · 87 citations

    4

    h-index

  2. AG
    Ana Garrido‐Varo

    University of Córdoba, Spain

    4 publications · 87 citations

    4

    h-index

  3. JE
    J. E. Guerrero

    University of Córdoba, Spain

    3 publications · 71 citations

    3

    h-index

  4. LC
    L.E. Chase

    Cornell University, United States

    3 publications · 345 citations

    3

    h-index

  5. TF
    Tom Fearn

    University College London, United Kingdom

    3 publications · 48 citations

    3

    h-index

1–5 of 177

Venues

  1. Journal of Dairy Science

    JDS · 7 publications · 504 citations

    7

    h-index

  2. Animal Feed Science and Technology

    4 publications · 184 citations

    4

    h-index

  3. The Journal of Agricultural Science

    3 publications · 106 citations

    3

    h-index

  4. Poultry Science

    3 publications · 64 citations

    3

    h-index

  5. Agricultural Systems

    2 publications · 79 citations

    2

    h-index

1–5