Yield Data Quality Control

Yield Data Quality Control is a data management process that systematically evaluates, filters, and corrects crop yield measurements from monitoring systems to detect, quantify, and mitigate errors and inconsistencies, thereby ensuring their accuracy, consistency, and suitability for subsequent agronomic and statistical analyses.

43

Publications

2.2K

Citations

169

Authors

76

Institutions

Publications per year

2017–2026

12

Authors

169

  1. PG
    Patricio Grassini

    University of Nebraska–Lincoln, United States

    3 publications · 174 citations

    3

    h-index

  2. RE
    Richard E. Plant

    University of California, Davis, United States

    2 publications · 52 citations

    2

    h-index

  3. SM
    Spyridon Mourtzinis

    University of Wisconsin–Madison, United States

    2 publications · 158 citations

    2

    h-index

  4. SP
    Shawn P. Conley

    University of Wisconsin–Madison, United States

    2 publications · 158 citations

    2

    h-index

  5. AB
    Alex B. McBratney

    The University of Sydney, Australia

    2 publications · 147 citations

    2

    h-index

1–5 of 169

Venues

  1. Agronomy Journal

    6 publications · 349 citations

    6

    h-index

  2. Precision Agriculture

    5 publications · 275 citations

    5

    h-index

  3. Field Crops Research

    3 publications · 129 citations

    3

    h-index

  4. Agricultural Systems

    2 publications · 128 citations

    2

    h-index

  5. Nuclear Physics B - Proceedings Supplements

    2 publications · 65 citations

    2

    h-index

1–5