Campus Units
Economics, Mechanical Engineering
Document Type
Article
Publication Version
Published Version
Publication Date
9-11-2020
Journal or Book Title
Scientific Reports
Volume
10
First Page or Article ID Number
14957
DOI
10.1038/s41598-020-71898-8
Abstract
Maize (corn) is the dominant grain grown in the world. Total maize production in 2018 equaled 1.12 billion tons. Maize is used primarily as an animal feed in the production of eggs, dairy, pork and chicken. The US produces 32% of the world’s maize followed by China at 22% and Brazil at 9% (https://apps.fas.usda.gov/psdonline/app/index.html#/app/home). Accurate national-scale corn yield prediction critically impacts mercantile markets through providing essential information about expected production prior to harvest. Publicly available high-quality corn yield prediction can help address emergent information asymmetry problems and in doing so improve price efficiency in futures markets. We build a deep learning model to predict corn yields, specifically focusing on county-level prediction across 10 states of the Corn-Belt in the United States, and pre-harvest prediction with monthly updates from August. The results show promising predictive power relative to existing survey-based methods and set the foundation for a publicly available county yield prediction effort that complements existing public forecasts.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright Owner
The Authors
Copyright Date
2020
Language
en
File Format
application/pdf
Recommended Citation
Jiang, Zehui; Liu, Chao; Ganapathysubramanian, Baskar; Hayes, Dermot J.; and Sarkar, Soumik, "Predicting county-scale maize yields with publicly available data" (2020). Economics Publications. 763.
https://lib.dr.iastate.edu/econ_las_pubs/763
Included in
Agricultural and Resource Economics Commons, Agriculture Commons, Computer-Aided Engineering and Design Commons, Statistical Models Commons
Comments
This article is published as Jiang, Zehui, Chao Liu, Baskar Ganapathysubramanian, Dermot J. Hayes, and Soumik Sarkar. "Predicting county-scale maize yields with publicly available data." Scientific Reports 10 (2020): 14957. doi: 10.1038/s41598-020-71898-8.