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Machine Learning-Based Modeling of Spatio-Temporally Varying Responses of Rainfed Corn Yield to Climate, Soil, and Management in the U.S. Corn Belt

Overview of attention for article published in Frontiers in Artificial Intelligence, May 2021
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Title
Machine Learning-Based Modeling of Spatio-Temporally Varying Responses of Rainfed Corn Yield to Climate, Soil, and Management in the U.S. Corn Belt
Published in
Frontiers in Artificial Intelligence, May 2021
DOI 10.3389/frai.2021.647999
Pubmed ID
Authors

Tianfang Xu, Kaiyu Guan, Bin Peng, Shiqi Wei, Lei Zhao

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X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 15%
Student > Master 6 15%
Unspecified 3 8%
Researcher 3 8%
Other 2 5%
Other 2 5%
Unknown 17 44%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 18%
Engineering 5 13%
Environmental Science 3 8%
Unspecified 3 8%
Physics and Astronomy 1 3%
Other 3 8%
Unknown 17 44%