Home

Organizing Committee

Presentations

Poster Presentations

Outcomes




Poster Presentations


21

Minnesota Soybean Rust Forecast Model (MinnSoyRustMod)

Presenter: James Kurle(1)

Other authors and affiliations: Crystal Floyd(1), Zhining Tao(2), Greg Spoden(3), Dean Malvick(1), Carl Bernacchi(2), Sagar Krupa(1). (1)University of Minnesota, Department of Plant Pathology, St. Paul, MN 55108, U.S.A.; (2)Illinois State Water Survey, Champaign, IL 61820, U.S.A.; (3)State of Minnesota, Office of the Climatologist, St. Paul, MN 55108, U.S.A.

The Minnesota Soybean Rust Forecast Model (MinnSoyRustMod) is a temporal (daily) and spatial (by county) prediction system of the occurrence of conditions favorable for development of soybean rust. It is designed to assist Minnesota soybean growers by forecasting the disease potential, but it does not provide the actual decision tool for possible fungicide application. MinnSoyRustMod is an integrated model that couples long-range spore transport (LRT) to its wet deposition and soybean leaf canopy wetness for ≥6 continuous hours required for spore germination. The LRT module utilizes both forward (168 h) and backward (48 h) air trajectories of the NOAA’S-HYSPLIT model at the lifting condensation layer (LCL) height above the surface. The leaf wetness module includes air and dew point temperatures, fractional cloud cover, and soybean growth as the input parameters. The overall forecast is based on daily relationships between USDA-identified disease or source regions and the actual potential receptor locations in Minnesota. The daily graphic forecasts include regions within Minnesota at “no, moderate, or high risk” for the rust during + or – 7 days from time zero. During the testing of MinnSoyRustMod in 2007, daily forecasts of the disease potential were derived and then a subset of coherent results were used for validation by comparing and analyzing: (i) HYSPLIT output to USDA-identified source regions, (ii) the modeled and measured leaf wetness data, and (iii) the presence of rust spores in bulk air samples collected in Minnesota using nested PCR and DNA sequencing.

                                        Back to Poster Presentations