Weather-based prediction of diseases of horticulture commodities in Oklahoma

1. Weather-based prediction of diseases of horticulture commodities in Oklahoma Damon L. Smith and Andrea F. Payne Department of Entomology and Plant Pathology, Oklahoma State University Stillwater, OK James P. Kerns Department of Plant Pathology University of Wisconsin Madison, WI

2. Weather-based Advisories in Oklahoma • Dollar spot prediction on creeping bentgrass • Pecan scab prediction • Grape black rot prediction

3. Dollar Spot Advisory • Location: OSU Turfgrass Research Center, OK (Fall, Spring 2008; Spring 2009); OJ Noer Turfgrass Center, WI (3 locations – 2009 growing season) • Host: Creeping bentgrass • Treatments: Non-treated, Preventative, Curative (vinclozolin 14-day interval) • New dollar spot foci counted daily • Hourly weather data recorded

4. Methods • Many zeros in the dataset = Foci counts transformed to binomial output (Foci = 1; No Foci = 0) and averaged across replicates for each treatment • Weather data were transformed to 5-day moving averages • Used Kendall’s Correlation Procedure • (PROC CORR; Kendall) • -Identified correlated independent variables • -Identified independent variables correlated with foci events • Binomial disease data and weather variables used in logistic regression analysis to predict the probability of dollar spot symptom development • (PROC LOGISTIC; STEPWISE option)

5. Best Overall - 2008

6. Estimated Probability Fall, No Fungicide Fall, Fungicide Spring, No Fungicide Spring, Fungicide

7. Oklahoma- 2009 = Probability of dollar spot development ≥ 10% = Fungicide protection intervals *

8. Wisconsin- 2009 = Probability of dollar spot development ≥ 10% = Fungicide protection intervals

9. 2009 Iteration • n=423 (2,538 obs averaged across rep) • Oklahoma and Wisconsin data

10. Oklahoma- 2009 = Probability of dollar spot development ≥ 50% = Probability of dollar spot development ≥ 30% *

11. OSU Pecan Scab Advisory • Internet Accessed, site-specific, weather-based disease advisory • Uses the Oklahoma Mesonet = 115 fully outfitted weather stations • Calculates the number of scab hours (hours during which T ≥ 21 C and RH ≥ 90%) accumulated over the last 14 non-fungicide protected days (Research by Gottwald et al. implemented by Driever and Vonbroemson) • Sprays advised based on scab hour thresholds for specific cultivars

12. OSU Pecan Scab Advisory • Highly susceptible cultivars = 10 scab hours • Moderately susceptible cultivars = 20 scab hours • Resistant cultivars = 30 scab hours

13. OSU Pecan Scab Advisory

14. OSU Pecan Scab Advisory

15. OSU Pecan Scab Advisory

16. How is the Advisory Working? • Several reports of Pecan Scab in orchards with no urgent scab advisory • Advisories work well for some folks, and not so well for others • Complaints about Mesonet weather station placement

17. Possible Corrections • Weather station placement might be an issue, but can be corrected with some calibration? • T and RH thresholds set incorrectly? • Need a weighted T or RH factor, instead of “hard” cutoff ? • Could be different fungal ecotypes?

18. LW and RH Correlations According to Sentelhas et al., 2008, Agri. & Forest Meteor.

19. Field Studies Combinations of relative humidity and temperature thresholds as treatments 90 %/ 70 ̊F 85 %/ 60 ̊F 80 %/ 60 ̊F 80 %/ 65 ̊F No Spray* *Will use the no spray check in new regression analyses

20. Nut Ratings – Madill, OK * P < .10 *No significant Difference between treatments

21. Major Challenges • What to do about leaf wetness and its measurement or interpolation? • Refining scales of weather data measurement to drive site-specific models – Improving site-specific weather measurement • Improving weather forecasts

22. Onsite vs. Mesonet

23. Onsite vs. SkyBit

24. Questions