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Forecasting Corn Ear Weights From Daily Weather Data, Fred B. Warren
Forecasting Corn Ear Weights From Daily Weather Data, Fred B. Warren
Conference on Applied Statistics in Agriculture
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.
Model Building To Measure Impact Of Weather On Crop Yields, Arlin M. Feyerherm, Gary M. Paulsen
Model Building To Measure Impact Of Weather On Crop Yields, Arlin M. Feyerherm, Gary M. Paulsen
Conference on Applied Statistics in Agriculture
The object of this research was to identify and evaluate alternatives when building mathematical models to measure the impact of weather on crop yields. Alternatives exist relative to selection of: (1) observational units with attention to size and coverage (areal and temporal), (2) observational periods for defining weather variables, and (3) mathematical forms and types of weather variables to measure impacts of moisture and temperature. The study involved an analysis of four weather-yield functions for winter wheat. The functions represented combinations of levels of two factors: (1) size and coverage of the observational units (plot yields from a multi-state area …