Modeling rice field moisture content during the harvest season. II. Model implementation and validation.
Lu R. | Siebenmorgen T.J.
An algorithm was developed to implement the model of Lu and Siebenmorgen (1993) for predicting rice moisture content (m.c.) throughout a harvest season. Equations are presented for generating diurnal patterns of air temperature, relative humidity, and solar radiation from daily maximum and minimum temperatures and relative humidities, and the daily total solar radiation. Rice m.c. was simulated using both hourly and daily field meteorological data for the harvest seasons of 1988 through 1990 at two locations in Arkansas. The m.c.s predicted from both hourly and daily input weather data were closely matched throughout the entire harvest seasons, with the differences being usually less than one percentage point (the average absolute relative differences for the three harvest seasons ranging from 3 to 5%). The model, using both hourly and daily field meteorological data, predicted the rice m.c.s with reasonable accuracy; the average absolute prediction error between measured and predicted m.c. varying between 1.2 and 2.2 percentage points for the three harvest seasons. Large prediction errors (up to six percentage points) were obtained for some of the early harvest dates or when rice was harvested shortly after rain. Dew was predicted to appear on the kernel surface when the air relative humidity was about 94% or higher and could cause up to a four percentage point increase in rice m.c. overnight.
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