MANHATTAN, Kan.--A website at Kansas State University may turn out to be a hot link for golf course managers.
KTURF is an advanced computer program designed to predict pesticide and nitrogen leaching in the upper 20 inches of turfgrass given the soil conditions and watering regime of a particular course.
KSU civil engineer Steven K. Starrett and electrical and computer engineer Shelli K. Starrett developed the program and placed it on the internet at http://www.eece.ksu.edu/~starret/KTURF/.
Steven Starrett will describe KTURF at the annual meeting of the American Chemical Society in Boston. He will speak at 1:30 p.m. Wednesday, Aug. 26, at the Marriott Copley Place. The paper, "KTURF: Pesticide and nitrogen leaching model," is part of a special symposium on the fate of turfgrass chemicals and pesticide management approaches, sponsored by the agrochemicals division.
On average, KTURF's predictions are within 4 percent of testing case values, Starrett said. That is, when presented with data about a setting it has never seen before, the model's estimates are close to the measured values, so it looks like a feasible modeling technique, he said. It would be useful as a screening tool for golf course turf managers.
"New golf courses are being built at the rate of 400 a year in the United States," he said.
Starrett created KTURF using research data from soil columns he collected as part of his doctoral program at Iowa State University. The Starretts used a commercially available artificial neural network toolbox to begin developing the KTURF predictive models. They entered data on soil characteristics, pesticide or nitrogen characteristics, and irrigation or precipitation conditions, and the percentages of compounds leached.
Artificial neural networks "learn"
relationships that exist between input and output data, Starrett explained. They
develop, without bias or guidance from the programmer,
Contact: Steve Starrett
Kansas State University