| Statistical Programs |
| College of Agriculture | University of Idaho |
| Seminar Announcement |
| "Applied Statistics in Agriculture" |
|
Estimating the Likelihood of
Yellow Starthistle Occurrence using an
Empirically Derived Nonlinear Regression
Model
Presented By |
| Dr. Bahman Shafii |
|
Statistical Programs College of Agriculture University of Idaho |
|
Tuesday, March 2 3:30 P. M. Ag. Science 62 |
| Yellow starthistle is a toxic weed common in the semiarid climate of Northern Idaho. Early detection of yellow starthistle and predicting its infestation potential have important scientific and managerial implications. Identification of weed infestations is often carried out via remote sensing or survey techniques. However, such methods may be ineffective in detecting sparse infestations. Population levels of yellow starthistle are affected by various exogenous variables such as elevation, slope and aspect. These demographic variables can be used to develop prediction models to estimate the potential of yellow starthistle infestation. A nonlinear prediction model has been developed based on a polar coordinate transformation to investigate the ability of demographic variables to predict the likelihood of yellow starthistle occurrence in North Central Idaho. The study region included parts of the Salmon and Clearwater basins encompassing various land use categories . The model provided accurate estimates of incidence of yellow starthistle within each specified land use category and performed well in subsequent statistical validations. |
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