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Predicting county-scale maize yields with publicly available data.
Jiang, Zehui; Liu, Chao; Ganapathysubramanian, Baskar; Hayes, Dermot J; Sarkar, Soumik.
Afiliação
  • Jiang Z; Department of Economics, Iowa State University, Ames, IA, 50011, USA.
  • Liu C; Department of Energy and Power Engineering, Tsinghua University, Beijing, 100084, China.
  • Ganapathysubramanian B; Department of Mechanical Engineering, Iowa State University, Ames, IA, 50011, USA.
  • Hayes DJ; Department of Economics, Iowa State University, Ames, IA, 50011, USA.
  • Sarkar S; Department of Mechanical Engineering, Iowa State University, Ames, IA, 50011, USA. soumiks@iastate.edu.
Sci Rep ; 10(1): 14957, 2020 09 11.
Article em En | MEDLINE | ID: mdl-32917920
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.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article