Thursday, November 8, 2007 - 10:00 AM
333-4

Yield Loss Prediction Tool for Asian Soybean Rust: A Multi-Disciplinary Project.

Saratha Kumudini1, James E. Board2, Claudia V. Godoy3, Chad Lee1, Don Hershman1, Joe Omielan1, and Elena Prior1. (1) Plant & Soil Sciences, University of Kentucky, 1405 Veterans Drive Rm 425, Lexington, KY 40546-0312, (2) Louisiana State University Agricultural Center, Rm. 104 Sturgis Hall, Department of Agronomy & Environmental Mgmt, Baton Rouge, LA 70803, (3) Embrapa - Soja, Rodovia Carlos Joao Strass, Caixa Postal 231, Londrina - PR, Brazil

Asian soybean rust (SBR) is a serious disease of soybean that has the potential to reduce crop yields by as much as 80%.  The goal of this multi-disciplinary, multi-institutional study was to develop a yield loss prediction tool for SBR that would be relevant in the United States. The utility of such a model is that potential yield losses may be weighed against cost of control to make more informed management decisions.  Crop yield is a function of the radiation intercepted by the crop canopy throughout the crop life cycle.  Since SBR is known to cause rapid canopy defoliation and yield loss, it was assumed that SBR-induced yield loss was primarily due to canopy defoliation.  A field study was conducted in Brazil to verify this assumption.  Results showed that both canopy defoliation and SBR lesions on non-abscised leaves contributed to the yield loss observed.  Modeling work was begun in Lexington, KY and Baton Rouge, LA to model yield based on healthy leaf area duration.   Field and controlled environment studies in Quincy, FL, and Lexington, KY, were carried out to quantify the impact of SBR lesions on primary plant productivity.