Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy
Type:
Title:
Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy
Creator:
Silva, J.V.;
Heerwaarden, J. van;
Reidsma, P.;
Laborte, A.G.;
Fantaye, K.T.;
https://orcid.org/0000-0002-7201-8053
Scopus ID
Mendeley
Items in this Repository
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van Ittersum, M.K.

Heerwaarden, J. van;
Reidsma, P.;
Laborte, A.G.;
Fantaye, K.T.;

Fantaye, K.T.



View
van Ittersum, M.K.
Year:
2023
Copyright:
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Journal:
Field Crops Research
Journal volume:
302
Article number:
109063
Place of Publication:
Amsterdam (Netherlands)
Publisher:
Elsevier B.V.
Citation:
Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy. 2023. 302 DOI: 10.1016/j.fcr.2023.109063 Elsevier B.V..
CGIAR Initiatives
Initiative:
Excellence in Agronomy
Impact Area:
Nutrition, health & food security
Poverty reduction, livelihoods & jobs
Poverty reduction, livelihoods & jobs
Action Area:
Resilient Agrifood Systems
Donor or Funder:
Netherlands Science Foundation
Bill & Melinda Gates Foundation
Bill & Melinda Gates Foundation
CGSpace URL: