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United States Department of Agriculture

Agricultural Research Service

Title: Maize and Sorghum Simulations with Ceres-Maize, Sorkam, and Almanac under Water-Limiting Conditions

Authors
item Xie, Yun - BEIJING NORMAL UNIV
item Kiniry, James
item Nedbalek, Vernon - GARST SEED CO
item Rosenthal, Wesley - TEXAS AGRIC EXP STATION

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 26, 2001
Publication Date: N/A

Interpretive Summary: Crop models can aid decision making if they accurately simulate grain yields in extreme climatic conditions. In this study, we evaluated the ability that ALMANAC and CERES-Maize models to simulate grain yields in an extremely dry growing season at several sites in Texas. The objective of our study was to evaluate the ability of ALMANAC and CERES-Maize to simulate maize (Zea mays L.) and sorghum [Sorghum bicolor (L.) Moench] (for ALMANAC only) grain yields under the dry conditions of 1998 at the several yield-trial sites in central and southern Texas. There were 11 sites for maize and eight sites for sorghum. We had soil data from the soil survey of each county and information from soil cores collected at the actual sites of the yield trials. ALMANAC reasonably simulated dryland sorghum yields in this dry year. The models showed similar accuracy in simulating irrigated maize sites. For dryland maize, ALMANAC more accurately simulated grain yields than CERES. In CERES, the leaf area index and kernel weight that were simulated appeared to be overly sensitive to drought stress. Further study on the response of leaf area index and kernel weight to severe drought in CERES would be valuable. The soil, weather, and crop parameter data sets developed for this study could be useful guidelines for model applications in similar climatic regions and on similar soils.

Technical Abstract: Crop models for aiding decision making must accurately simulate grain yields in extreme climatic conditions. In this study, we evaluated the ability of two models to simulate grain yields in an extremely dry growing season at several sites in Texas. The objective of this study was to evaluate the ability of ALMANAC and CERES-Maize to simulate maize (Zea mays L.) and sorghum [Sorghum bicolor (L.) Moench] (for ALMANAC only) grain yields under these dry conditions at the several yield-trial sites in central and southern Texas in 1998. The models' predictions were tested under the conditions of 1998. There were 11 sites for maize and eight sites for sorghum. Model data sets included soil data from the soil survey of each county and information from soil cores collected at the actual sites of the yield trials. ALMANAC reasonably simulated dryland sorghum yields in this dry year. The models showed similar accuracy in simulating irrigated maize sites. For dryland maize, ALMANAC more accurately simulated grain yields than CERES. In CERES, the leaf area index and kernel weight that were simulated appeared to be overly sensitive to drought stress. Further study on the response of leaf area index and kernel weight to severe drought in CERES would be valuable. The soil, weather, and crop parameter data sets developed for this study could be useful guidelines for model applications in similar climatic regions and on similar soils.

Last Modified: 11/23/2014
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