Author

M. R. Krause

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Plant Biology· 1

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Approach:machine learning (classical)· 1

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D. Ochs· 1 shared J. Swede· 1 shared M. A. Gore· 1 shared R. Lott· 1 shared R. Robbins· 1 shared S. Arliss· 1 shared S. Crossman· 1 shared T. DuMond· 1 shared

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1 shared paperPlant Biology

D. Ochs

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1 paper

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Plant BiologybioRxivFeb 17, 2020

Random Forest Regression for Optimizing Variable Planting Rates for Corn and Soybean Using High-Resolution Topographical and Soil Data

M. R. Krause, S. Crossman, T. DuMond…·M. A. Gore

The paper develops a random forest regression model to optimize corn and soybean planting rates using topographical and soil data, finding that yield responses depend on complex site-specific interactions.

DOI 10.1002/agj2.20442

machine learning (classical)

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