Yield Monitor Data Cleaning

Yield Monitor Data Cleaning is a data preprocessing methodology that systematically identifies, corrects, and removes spatial, temporal, and sensor-related inaccuracies in raw yield monitor datasets to ensure agricultural productivity data integrity for downstream analysis.

6

Publications

285

Citations

21

Authors

12

Institutions

Publications per year

2017–2026

2

Authors

21

  1. TP
    Tulsi P. Kharel

    Agricultural Research Service, United States

    1 publications · 38 citations

    1

    h-index

  2. SN
    Sheryl N. Swink

    Cornell University, United States

    1 publications · 38 citations

    1

    h-index

  3. AD
    Achim Dobermann

    University of Nebraska–Lincoln, United States

    1 publications · 87 citations

    1

    h-index

  4. KC
    Karl Czymmek

    Cornell University, United States

    1 publications · 38 citations

    1

    h-index

  5. LF
    Leonardo Felipe Maldaner

    Universidade de São Paulo, Brazil

    1 publications · 37 citations

    1

    h-index

1–5 of 21

Venues

  1. Agronomy Journal

    2 publications · 125 citations

    2

    h-index

  2. Precision Agriculture

    1 publications · 55 citations

    1

    h-index

  3. 2012 Dallas, Texas, July 29 - August 1, 2012

    1 publications · 43 citations

    1

    h-index

  4. Scientia Agricola

    1 publications · 37 citations

    1

    h-index

  5. SSRN Electronic Journal

    Repository · 1 publications · 25 citations

    1

    h-index

1–5