Bayesian Fertilizer Response Modeling

Bayesian Fertilizer Response Modeling is a statistical modeling framework that applies Bayesian inference to quantify uncertainty and estimate parameters in crop yield responses to fertilizer inputs, distinguishing itself from classical approaches by incorporating prior knowledge and producing probabilistic predictions of fertilizer effects.

6

Publications

186

Citations

23

Authors

16

Institutions

Publications per year

2017–2026

3

Authors

23

  1. MT
    Mike Talbot

    University of Edinburgh, United Kingdom

    1 publications · 20 citations

    1

    h-index

  2. AA
    Adrián A. Correndo

    Kansas State University, United States

    1 publications · 45 citations

    1

    h-index

  3. PV
    P. V. Vara Prasad

    Kansas State University, United States

    1 publications · 45 citations

    1

    h-index

  4. DN
    David Nash

    Ellinbank Observatory, Australia

    1 publications · 60 citations

    1

    h-index

  5. CD
    Carlos D. Messina

    Corteva (United States), United States

    1 publications · 45 citations

    1

    h-index

1–5 of 23

Venues

  1. Field Crops Research

    1 publications · 23 citations

    1

    h-index

  2. 1

    h-index

  3. American Journal of Agricultural Economics

    1 publications · 17 citations

    1

    h-index

  4. 1

    h-index

  5. Environmental Modelling & Software

    1 publications · 60 citations

    1

    h-index

1–5