Author
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WANG, FENGXIAN - UNIV OF MO |
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FRAISSE, CLYDE - CARGILL |
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Kitchen, Newell |
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Sudduth, Kenneth - Ken |
Submitted to: Agricultural Systems
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 3/18/2002 Publication Date: 6/1/2003 Citation: WANG, F., FRAISSE, C., KITCHEN, N.R., SUDDUTH, K.A. SITE-SPECIFIC EVALUATION OF THE CROPGRO-SOYBEAN MODEL ON MISSOURI CLAYPAN SOILS. AGRICULTURAL SYSTEMS. 2003. V. 79. P. 985-1005. Interpretive Summary: Crop yield is affected by many factors including soil, weather, and agronomic management practices. Crop growth models can provide insight on how these factors interact to affect crop production. Crop models are computer programs that describe how a crop grows using mathematical func- tions. Farmers and their consultants then may be able to use this insight to optimize management strategies between and within fields. We applied th CROPGRO-soybean model on two claypan soil fields in central MO. We wanted to understand how well the model was able to simulate crop growth for different areas of a field to see if it would provide useful information for precision agriculture. Field data and model results were compared for dry and average-precipitation cropping seasons over 3 years. The model was generally accurate in predicting soil water throughout the growing season. Grain yield estimated by the model agreed well with measured values for average precipitation years but was low for an extremely dry year. Within- season rainfall and claypan soil topsoil depth, two factors that affect soil water available for plant growth, had the greatest influence on soybean yield. Measured data showed the claypan soil layer did not restrict root penetration as expected. In fact, the density of roots increased within the claypan horizon, perhaps because the soybean plant needed more roots to obtain water from the high-clay soil layers. These results are significant because they show it is possible to use a soybean crop growth model to obtain information for precision agriculture decision-making. Being able to test management strategies using proven models will benefit farmers and crop consultants by helping them understand yield variation and to develop more efficient site-specific management plans. Technical Abstract: Crop modeling can be used to help understand how multiple factors interact to impact yield. The CROPGRO crop model has been applied to numerous research problems and has proved to be very useful in simulating soybean growth and development. The objective of this study was to evaluate the performance of the CROPGRO-Soybean model for simulating site-specific crop growth, soil water content, and grain yield on claypan soils (Aeric Vertic Epiaqualfs). Data were obtained during dry and average-precipitation weather conditions from two fields over three years in central Missouri. Plant yield, leaf area, and root length density along with soil topsoil thickness, moisture, and texture measurements were collected for calibrating and validating the model. Results indicated that CROPGRO- simulated soil water contents in the 15-90 cm soil profile agreed well with measured values. Simulated leaf area index and grain yield also agreed well with measured values during average precipitation years but were under-estimated during extremely dry years. Within-season precipitation and claypan soil topsoil depth were shown to have the greatest influence on soybean yield. Although we hypothesized it to be otherwise, field measurements showed that the claypan did not negatively affect soybean root penetration. |