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Predicting county-scale maize yields with publicly available data.

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.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Jiang Z,Liu C,Ganapathysubramanian B,Hayes DJ,Sarkar S

doi

10.1038/s41598-020-71898-8

subject

Has Abstract

pub_date

2020-09-11 00:00:00

pages

14957

issue

1

issn

2045-2322

pii

10.1038/s41598-020-71898-8

journal_volume

10

pub_type

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