Evaluating CROPGRO-Soybean Performance for Use in Climate Impact Studies
Gregory J. Carbone*,a,
Linda O. Mearnsb,
Theodoros Mavromatisc,
E. John Sadlerd and
David Stooksburye
a Dep. of Geogr., Univ. of South Carolina, Columbia, SC 29208
b Natl. Cent. for Atmos. Res., P.O. Box 3000, Boulder, CO 80303
c Dep. of Agric. and Biol. Eng., Univ. of Florida, Gainesville, FL 32611
d USDA-ARS, Coastal Plains Soil, Water, and Plant Res. Cent., 2611 W. Lucas St., Florence, SC 29501
e Dep. of Biol. and Agric. Eng., Univ. of Georgia, Athens, GA 30602

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Fig. 1. Locations of eight agricultural experiment stations used in analysis.
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Fig. 2. Components of mean squared deviation for maturity group V and Forrest cultivar. LCS, lack of correlation weighted by the standard deviations; SDSD, squared difference between standard deviations; SB, squared bias.
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Fig. 3. Time series of simulated and observed yield for Forrest cultivar at (a) Crossville, AL, and (b) Marion Junction, AL.
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Fig. 4. Components of mean squared deviation for maturity group VI. LCS, lack of correlation weighted by the standard deviations; SDSD, squared difference between standard deviations; SB, squared bias.
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Fig. 5. Time series of simulated and observed yield for maturity group VI at Jeanerette, LA.
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Fig. 6. Components of mean squared deviation for maturity group VII and Ransom cultivar. LCS, lack of correlation weighted by the standard deviations; SDSD, squared difference between standard deviations; SB, squared bias.
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Fig. 7. Time series of simulated and observed yield for (a) maturity group VII at St. Joseph, LA, and (b) Ransom cultivar at Fairhope, AL.
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Copyright © 2003 by the American Society of Agronomy.