Daniel Cooley and Jon Clements University of Massachusetts Amherst dcooley@microbio.umass

1. String Theories, Fuzzy Logic and Forecasting: Inconsistencies Applying Empirical Plant Disease Models Daniel Cooley and Jon Clements University of Massachusetts Amherst dcooley@microbio.umass.edu

2. Case study: sooty blotch flyspeck complex of apple Scab fungicides: green tip to fruit set 3 to 6 applics. 1 to 4 applics. SBFS fungicides: fruit set to harvest Models target period following end of primary apple scab to ~ 1.5 in. apples Can eliminate several early summer fungicide ‘cover’ applications

3. Basic concept Most or all SBFS inoculum develops on reservoir hosts in borders and moves into orchards Development in borders and on fruit is driven by surface moisture or very high humidity FS is focus

4. Original model Brown & Sutton 1995 – empirical model based on first signs Biofix – 10 days after petal fall 273 accumulated leaf wetness hrs. for periods ≥ 4 hrs.

5. Original model – LW sensing • DeWit monitor – “string” based • Wet if ≥ 50% deflection • Placed inside dripline of tree • 1.5 meter above ground

6. Original model action threshold • First appearance of signs: 209 to 310 ALWH • Benzimidazole trt. at 200 to 225 ALWH • “… the threshold that we have established with the deWit sensor may have to be modified if other sensors are used.”

7. Hartman revision Electronic sensor rather than deWit Used a 175 hr. treatment threshold Counted all wet hrs. – no 4 hr. minimum Biofix of the first post-petal fall fungicide treatment

8. Illinois / Iowa / Wisconsin • Babadoost et al. 2004 used Hartman modification • Compared electronic on-site with mesoscale interpolated (Skybit) data • Skybit LW accumulated more rapidly than on-site • SBFS Incidence higher in model-directed plots in 12 of 28 site yrs.

9. LW vs. RH Duttweiler et al. 2008 Accumulated hrs. of RH ≥ 97% better predictor in IA, but ALWH better in NC Regional differences in climate expected with empirical model

10. What does a user ask? When should I spray? Commercial model software and monitoring software bundle – Spectrum Commercial remote monitoring and model delivery – SkyBit Public web-based weather and model delivery – NEWA and Orchard Radar On-site monitoring and published Extension recommendations

11. First SBFS recs., 5 models SkyBit model, 350 threshold Jun 16 Spectrum model, 300 threshold Jul 17 Orchard Radar using SkyBit LW, temp. adj. 270 threshold Jun 6 Ext. rec., on-site Hobo 270 threshold Jun 12 NEWA, on-site Hobo 170 threshold Jun 2 Accumulated Leaf Wetness or High RH Hours 5 wks. 2 – 3 fungicide applications PF Date

12. Key differences • Biofix • Petal fall (cultivar?) • 10 days after petal fall • Last fungicide targeting scab • Accumulated leaf wetness hrs action threshold • Count all hours or exclude short periods • Choose one: 170, 200, 259, 270, 300, 350 …

13. Key differences • Method of data collection • On-site • Remote site-specific • On-site • Placement of grid • 45º facing north 1.5 meters • Canopy or open? • Is anyone still using strings? • Grid sensitivity: 40% of range?

14. Key differences • Remote site-specific • Sources of data – leaf wetness not common • Algorithms for location • Algorithms to interpolate from common data such as RH and wind speed to LW • Should we just use RH?

15. Comparing four data sources Accumulated Leaf Wetness or High RH Hours Date

16. Issues to resolve • Biofix – last primary scab fungicide vs. phenology • If fungicide, depletion should be used • Differentiate action threshold from damage threshold, i.e. first SBFS fungicide trigger from first visible signs on non-sprayed fruit

17. Issues to resolve Standardize sensor placement for on-site equipment considering ease of use and maintenance (not in canopy) Standardize sensor wetness threshold Determine accurate LW estimators for off-site sensing