Abstract
General models requiring simple, readily available input data are needed for large area yield forecasting. Daily dry matter accumulation of a grain sorghum (Sorghum bicolor (L.) Moench) crop was modeled with photosynthesis and respiration equations requiring only daily meteorological variables (solar radiation, maximum and minimum temperatures, and precipitation), leaf area index, and stage of development. The equations were based on carbon dioxide exchange rates of sorghum measured with field chambers and an infrared gas analysis system. Higher rates of photosynthesis after floral initiation were attributed to increased sink capacity. Reduction of rate of photosynthesis due to high temperature and water stresses was included in the model. Respiration was modeled as a photosynthesis-dependent component and temperature-biomass dependent component. Dry matter predicted by the model was within 10 to 15% of dry matter measured in Kansas, Texas, and Nebraska. Panicle weight was estimated as a function of dry matter accumulation at half bloom, net photosynthesis after half bloom, translocation of previously stored material, and water and temperature stresses during panicle initiation and bloom. Grain yield, assumed to be 80% of panicle weight, was highly related to measured grain yield (R2 of.58).
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