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USDA-ARS, 808 E. Blackland Rd., Temple, TX 76502
Soil and Crop Sciences Dep., Texas A&M University, College Station, TX
* Corresponding author (kiniry{at}brc.tamus.edu).
Crop models for decision making should accurately simulate grain yields across a wide range of soils and climate regimes. This study was designed to evaluate two models' ability to simulate plot grain yields under diverse weather conditions and soils in Texas. The objective was to compare measured grain yields of maize (Zea mays L.) and sorghum [Sorghum bicolor (L.) Moench] with grain yields simulated by the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) model and to compare measured maize yields with grain yields simulated by a new version of the CERES-Maize (Crop-Environment Resource Synthesis) model. Using yield performance trials, both models were tested for their ability to simulate the mean yield for five years at each location and their ability to describe year-to-year variability in measured yields. Both models were tested at nine locations for maize and ALMANAC was tested at eight locations for sorghum. Model inputs included parameters for the soil type, planting dates, planting rates, and locally measured weather data. Mean simulated grain yield for each site was within 10% of the mean measured grain yield for all cases, except for CERES at Thrall, where mean simulated yield was 13% lower than mean measured yield. When the models did not account for a significant amount of the year-to-year variability in measured grain yield at a site, it was usually due to the narrow range of measured grain yields. The soils, weather, and crop parameter data sets developed here can be useful starting points for deriving data at similar sites, giving model users examples of realistic input data.
Received for publication April 7, 1997.
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