Monday, November 5, 2007
37-1

Recent Advances in the CSM-CERES Sorghum Model.

Jeffrey White1, Gerrit Hoogenboom2, Samsul Huda3, Bruce Kimball1, Michael Ottman4, P. V. V Prasad5, Wesley Rosenthal6, Moussa Sanon7, Scott Staggenborg8, Sibiry Traore9, Michel Vaksmann10, and Richard L. Vanderlip5. (1) USDA-ARS, US Arid Land Agricultural Research Center, 21881 N. Cardon Lane, Maricopa, AZ 85239, (2) 165 Gordon Futral Court, University of Georgia, University of Georgia, Dept. of Biological & Agricultural Engineering, Griffin, GA 30223-1797, (3) Locked Bag 1797, AUSTRALIA,Univ.of W. Sydney, University Of Western Sydney, Centre for Plant & Food Science, Kawkesbury Campus, Penrith South DC, NSW1797, AUSTRALIA, (4) 1140 E South Campus Dr., University of Arizona, University of Arizona, Dept. Plant Science, Tucson, AZ 85721, (5) Kansas State University, 2004, Throckmoton Plant Sciences Center, Manhattan, KS 66506, (6) Texas Agricultural Experiment Station-Blackland Research Center, 720 East Blackland Road, Temple, TX 76502, (7) Department of Natural Resources Management and Farming Systems, Environment and Agricultural Research Institute (INERA), 04 P.O. Box 8645, Ouagadougou, Burkina Faso, (8) Kansas State University - Plant Pathology, Kansas State Univ., 3709 Throckmorton Hall, Manhattan, KS 66506, (9) ICRISAT, Bamako, Mali, (10) CIRAD/IER, B.P. 1813, Quinzambougou, Bamako, 1813, Mali

Sorghum (Sorghum bicolor [L.] Moench) is grown in a wide range of environments, and cultivars can differ greatly in photoperiod response, degree of tillering, and other traits. The process-based model CSM-CERES Sorghum, distributed with the DSSAT4 modeling software, shows promise as a tool for research as well as for guiding management decisions in sorghum systems. Initial testing, however, suggested the model had difficulty simulating leaf area development and partitioning to stem mass. This paper describes recent modifications to the model, assesses their impact on simulation of phenology, growth, and grain yield, and suggests needs for further research and applications. Datasets considered include a wide range of temperate and tropical conditions.