1. Damon L. Smith and Andrea F. Payne Department of Entomology and Plant Pathology, Oklahoma State University Stillwater, OK

2. Dollar spot prediction on creeping bentgrass Grape black rot prediction Pecan scab prediction

3. Come visit the following posters: 389-P Using weather variables to predict the probability of dollar spot development. D.L. Smith and J.P. Kerns Oklahoma State University and UW-Madison. 391-P Effects of temperature on growth and aggressiveness of Sclerotinia homoeocarpa. C. Wilson and J.Kerns University of Wisconsin-Madison and D.L. Smith, Oklahoma State University.

4. Spotts, R.A. 1977. Effect of Leaf Wetness Duration and Temperature on the Infectivity of Guignardia bidwellii on Grape Leaves. Phytopathology Vol. 67: 1378-1381.

5. According to Sentelhas et al., 2008, Agri. & Forest Meteor.

6. http://agweather.mesonet.org/index.php/advisors/grape_black_rot/black_rot_advisor http://agweather.mesonet.org/research/

7. http://agweather.mesonet.org/index.php/advisors/grape_black_rot/black_rot_advisor http://agweather.mesonet.org/research/

8. 30% reduction in fungicide applications using the advisory Consistent among other locations

9. Scab hour (SH) – an hour in which the average T ≥ 21 °C and RH ≥ 90% Accumulation of SH begins after a 14-day fungicide protection period ends Fungicide application is advised after a set number of SH based on cultivar susceptibility Driever, 1996

10. Grower Inputs Location Variety Susceptibility Last Fungicide Application

11. The advisory calculates the number of accumulated scab hours after a 14-day protection period. Recommendations are clearly illustrated for the user A 3-day forecast gives growers another tool to aid their decision to spray or not to spray

12. * P <.10*No significant Difference between treatments 70F / 90%Control60F / 85%60F / 80%65F / 80% 5/19/09- 6/29/09-6/12/096/8/096/10/09 7/31/09-7/1/096/26/096/29/09 -7/31/097/23/09 -8/25/098/14/09

13. 108-O Probability modeling of pecan scab using weather variables as inputs. A.F. Payne and D.L. Smith, Oklahoma State University

14. http://pecan.ipmpipe.org/

15. Uses Weather Stations in NOAA’s Network Belt Wide Pecan Scab Management Using the OSU Model

16. How well do the NOAA measurements of weather correlate with the Oklahoma Mesonet?

17. OklahomanmbR2R2 MD (h)SEPr > |t| Durant1561.020.280.72-0.310.160.06 Idabel1560.830.040.770.360.150.02 * Difference amounts to 4.3 to 5.0 hours over 14-day period

18. OklahomanmbR2R2 MD (h)SEPr > |t| Stillwater1560.350.100.50 0.15< 0.01 * Difference amounts to 7 hours over 14-day period

19. Refining scales of weather data measurement to drive site-specific models – Improving site-specific weather measurement (issue in the Midwest) Improving weather forecasts = Improved disease forecasts