Random forest regression for optimizing variable planting rates for corn and soybean using topographical and soil data-Reference-Cited by-同舟云学术

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Random forest regression for optimizing variable planting rates for corn and soybean using topographical and soil data

Published:2020-10-25 Issue:6 Volume:112 Page:5045-5066
ISSN:0002-1962
Container-title:Agronomy Journal
language:en
Short-container-title:Agron.j.

Author:

Krause Margaret R.¹²^ORCID,Crossman Savanna³,DuMond Todd³,Lott Rodman³,Swede Jason³,Arliss Scott³,Robbins Ron³,Ochs Daniel³,Gore Michael A.¹^ORCID

Affiliation:

1. Plant Breeding and Genetics Section, School of Integrative Plant Science Cornell University Ithaca NY 14853 USA

2. Global Wheat Program International Maize and Wheat Improvement Center (CIMMYT) Texcoco Edo. de México 56237 México

3. New York Corn and Soybean Growers Association PO Box 133 Silver Springs NY 14550 USA

Publisher

Wiley

Subject

Agronomy and Crop Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/agj2.20442

Reference75 articles.

1. Branch development responses to planting density and yield stability in soybean cultivars

2. Nonlinear regression models and applications in agricultural research;Archontoulis S. V.;Agronomy Journal,2014

3. Uncertainty analysis for soil‐terrain models

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