1. Predicting Tomato Spotted Wilt Virus on tobacco in North Carolina A.L. Mila Dept. of Plant Pathology

2. TSWV symptoms on tobacco

3. Thrips: the culprit Frankliniella fusca TSWV epidemiology on tobacco Wide range of hosts (>500 spp.,>50 families)

4. TSWV incidence in NC Question: What is next season’s expected TSWV risk

5. TSWV in NC (1993-2007) Severe TSWV epidemics (8 counties) TSWV epidemic in 2002 and then occasionally (12 counties) TSWV in “trace” (38 counties)

6. What can a grower do? Imidacloprin (such as, Admire Pro: 0.8 oz/1000 pl) AND Actigard (0.5 oz – 1 oz/50,000 pl drench OR 10 – 25 ppm float water) Chemical control in the greenhouse

7. Untreated control Actigard 25 ppm [float water] Actigard: 4 weeks after transplant Wake co. 2006

8. Actigard: 6-7 weeks after transplant Untreated control Actigard 25 ppm [pretra] Wake co. 2006

9. Question: Which fields will have > 25% TSWV? What can a grower do? Imidacloprin (such as, Admire Pro: 0.8 oz/1000 pl) AND (if TSW incidence > 25%) Actigard (0.5 oz – 1 oz/50,000 pl drench OR 10 – 25 ppm float water)

10. Two questions to answer: Question - pre-season risk What is next season’s expected TSWV risk? Question - in-season risk Which fields will have > 25% TSWV?

11. TSWV in NC (1993-2007) Severe TSWV epidemics (8 counties) TSWV epidemic in 2002 and then occasionally (12 counties) TSWV in “trace” (38 counties) A total of 489 cases 58 counties 14 years (1993 – 2007)

12. Objectives Determine if any weather factors are predictors of TSWV risk at the county level Time: September before transplant to August (harvest) Weather factors: Total precipitation, days with rain, degree days, and average air temperature

13. Pre-season risk - Results Precipitation and temperature of Dec – Feb most significant explanatory weather factors ParameterEstimate Total Precipitation (December) -0.007 Total Precipitation (January) -0.014 Total Precipitation (February) -0.008 Sum of monthly average temperature (December, January & February) 0.14 * Magnitude of effect different for counties

14. Pre-season risk – “county effect” ► Correction between counties? (Structured heterogeneity) ► Other missing factors? (Unstructured heterogeneity)

15. Investigate the “county” effect: Bayesian disease mapping y i ~ Bin (n i, p i ) (likelihood) p i = f (T, Pr) + U i + V i Structured (autocorrelation) “Auto-regression function” Unstructured N (0, σ 2 )

16. Structured heterogeneity? NO Unstructured heterogeneity? YES Pre-season risk – “county effect” Sampson co. TSWV incidence Probability of TSWV incidence

17. Validation (2008 – present)

18. Predicted Pre-season risk North Carolina - 2008 CountyStationPredicted CravenHavelock 14 – 22 DuplinMount Olive 4 – 9 SampsonClinton 13 – 26 LenoirKinston 4 – 11 PittAyden 1 – 4 JohnstonClayton 0.6 – 3.5 WilsonSims 0 – 1 Reported 14 8 2 10 2.3 4 1

19. Predicted Pre-season risk North Carolina - 2010 CountyStationPredicted CravenHavelock 1 – 14 DuplinMount Olive 1 – 5 SampsonClinton 0.5 – 10 LenoirKinston 1 – 12 PittAyden 0 – 3 JohnstonClayton 0 – 0.5 WilsonSims 0 – 1

20. Conclusions Winter weather good predictor of TSWV risk for upcoming season * Importance of spring weather was not discussed…

21. Pre-season risk on the web

22. Expand effort - 2009 Pre-season risk (Georgia, North Carolina, South Carolina and Virginia) In-season risk (Georgia, North Carolina, South Carolina)

23. K. Cherry J. Radcliff & M. Browne NC Tobacco Agents NC Tobacco Research Commission Tobacco Education & Research Council Acknowledgements