Author Information

Fred B. Warren

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No

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Paper/Presentation

Abstract

Statistical models were developed to predict the State average grain weight per ear using daily temperature and precipitation data, recorded from May 1 through late July. The required daily weather data was successfully obtained in an operational test of these models for ten major corn producing States in 1988. Relative forecast errors of ear weight averaged almost one-third smaller than those from a regular survey. Additional refinements of the models to make them more responsive to abnormally early adverse weather, as in 1988, are underway.

Keywords

modeling, weather, corn ear weight

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Apr 30th, 3:30 PM

FORECASTING CORN EAR WEIGHTS FROM DAILY WEATHER DATA

Statistical models were developed to predict the State average grain weight per ear using daily temperature and precipitation data, recorded from May 1 through late July. The required daily weather data was successfully obtained in an operational test of these models for ten major corn producing States in 1988. Relative forecast errors of ear weight averaged almost one-third smaller than those from a regular survey. Additional refinements of the models to make them more responsive to abnormally early adverse weather, as in 1988, are underway.