Sooty Blotch and Flyspeck for Apples and Pears
Overview | Logic | Management | Data access | References | More info | Figures
Primary contact for this NEWA model
Anna Wallis, PhD | Fruit IPM Coordinator Cornell Integrated Pest Management Email: aew232@cornell.edu
Contact Anna with questions about using this model in the field, interpreting its output, or requesting support.
Version 20260730 DLO
1. Overview
1.1 What this model does
Sooty blotch and flyspeck (SBFS) are surface fungi that blemish apple and pear fruit finish. They do not rot the fruit, but they downgrade its market value. This model estimates how much infection pressure has built up in your block since petal fall, and tells you whether a cover fungicide application is warranted.
The model tracks three things. (1) how long it has been since fruit became susceptible, (2) how many hours the fruit surface has been wet, and (3) how much rain has fallen since your last fungicide application if you tell it about your sprays.
The complete workflow is shown in Figure 1.
1.2 Inputs and outputs at a glance
| Item | Value |
|---|---|
| Weather inputs | Air temperature, leaf wetness, precipitation, rain probability forecast |
| Degree day base | 43 F |
| Degree day method | Baskerville-Emin |
| Petal fall threshold | 454 degree days (McIntosh, default estimate) |
| Optional user input | Petal fall date for the block |
| Optional user input | Most recent fungicide application date |
| Output | Risk level of No risk, Low, Moderate, or High |
1.3 Season
The model runs on weather from January 1 forward, but produces no risk level until petal fall has occurred. Before that point the page reports how many degree days remain until petal fall is expected.
2. Model logic
2.1 Weather data
The model pulls hourly and daily weather from your selected NEWA station, starting January 1 of the selected year and running through your date of interest, plus the available forecast days. Leaf wetness, precipitation, and air temperature all come from that station.
2.2 Determining petal fall
Petal fall is the point at which fruit becomes susceptible, and it is where all SBFS tracking begins.
2.2.1 Degree day estimate (default)
The model accumulates degree days from January 1 using base 43 F and the Baskerville-Emin method. 454 degree days is the default estimate for McIntosh petal fall. Until that threshold is reached, the page tells you how many degree days remain and reports no risk level.
2.2.2 User-entered date (recommended)
The degree day default is a regional estimate. If you know the actual petal fall date for a block, enter it. Your date replaces the degree-day estimate, and every downstream number is recalculated from it.
2.3 Accumulating leaf wetness hours
Starting on the petal fall date (counted as day 0), the model adds up leaf wetness hours. An hour counts if the station recorded at least one minute of leaf wetness during that hour. The total is cumulative and never resets, even after a fungicide application.
This accumulated total is the single most important driver of SBFS risk. The thresholds fall at roughly 100, 130, and 170 accumulated hours.
2.4 Accounting for fungicide applications (optional)
If you enter the date of your most recent fungicide application, two additional counters start on that date:
- Days since the application
- Inches of rain since the application (an estimate of fungicide wash-off and depletion)
Entering a fungicide date changes what the model evaluates. The "days" input to the risk lookup switches from days since petal fall to days since your application, which effectively restarts the protection clock. Rain since the application then becomes an active input.
Important. if you do not enter a fungicide date, rainfall does not influence the calculated risk level at all. Daily rain amounts and rain probability still appear in the results table so you can judge conditions yourself, but the risk level is driven only by days since petal fall and accumulated leaf wetness hours.
2.5 Assigning a risk level
2.5.1 Lookup inputs and bands
The model compares the current values against a lookup table with three dimensions:
| Input | Bands used |
|---|---|
| Days (since petal fall, or since fungicide if entered) | 0-9, 10-13, 14-20, 21+ |
| Rain since fungicide application (inches) | 0-1.49, 1.5-1.99, 2.0+ |
| Accumulated leaf wetness hours since petal fall | 0-99, 100-129, 130-169, 170+ |
Accumulated leaf wetness hours is the dominant input. The days counter modifies it, and rain only comes into play once leaf wetness has already passed 130 hours.
2.5.2 Decision path
Figure 2 shows the exact path the model takes through the lookup table. "Days" means days since petal fall, or days since your last fungicide application if you entered one. If you did not enter a fungicide date, rain is treated as zero, so every rain branch takes the lowest path.
The general pattern
- No risk occurs only early. Within 9 days of petal fall (or of a fungicide application) with fewer than 100 accumulated leaf wetness hours.
- Low covers most of the early season, and continues later when leaf wetness is still under 100 hours.
- Moderate appears once leaf wetness passes about 130 hours, or once you are more than 21 days out from your last application with more than 100 hours accumulated. Rain accelerates the move into Moderate.
- High requires roughly 170+ accumulated leaf wetness hours, and arrives fastest when 2 or more inches of rain have fallen since your last application.
Applying a fungicide and entering the date resets the days counter and the rain total, which typically drops the reported risk level. The accumulated leaf wetness hours keep climbing, so risk rebuilds more quickly with each successive interval as the season goes on.
2.5.3 Complete lookup matrix
Each table below covers one "days" band. Rows are accumulated leaf wetness hours since petal fall. Columns are inches of rain since the last fungicide application.
If no fungicide date is entered, only the first rain column applies.
Days 0-9 since petal fall or last fungicide application
| Leaf wetness hours | Rain 0-1.49 in | Rain 1.5-1.99 in | Rain 2.0+ in |
|---|---|---|---|
| 0-99 | No risk | No risk | No risk |
| 100-129 | Low | Low | Low |
| 130-169 | Low | Moderate | Moderate |
| 170+ | Low | Moderate | High |
Days 10-13
| Leaf wetness hours | Rain 0-1.49 in | Rain 1.5-1.99 in | Rain 2.0+ in |
|---|---|---|---|
| 0-99 | Low | Low | Low |
| 100-129 | Low | Low | Low |
| 130-169 | Low | Moderate | Moderate |
| 170+ | Low | Moderate | High |
Days 14-20
| Leaf wetness hours | Rain 0-1.49 in | Rain 1.5-1.99 in | Rain 2.0+ in |
|---|---|---|---|
| 0-99 | Low | Low | Low |
| 100-129 | Low | Low | Low |
| 130-169 | Moderate | Moderate | Moderate |
| 170+ | Moderate | Moderate | High |
Days 21 or more
| Leaf wetness hours | Rain 0-1.49 in | Rain 1.5-1.99 in | Rain 2.0+ in |
|---|---|---|---|
| 0-99 | Low | Low | Low |
| 100-129 | Moderate | Moderate | Moderate |
| 130-169 | Moderate | Moderate | Moderate |
| 170+ | High | High | High |
2.6 Reading the results table
The table shows the selected date (bold) with the two preceding days and the following forecast days, so you can see whether risk is about to rise.
| Column | What it means |
|---|---|
| Days since petal fall | Days elapsed since the biofix date; petal fall itself is day 0 |
| Accumulated leaf wetness hours | Running total of wet hours since petal fall |
| Days since last fungicide application | Shown only when you enter an application date |
| Rain since last fungicide application | Inches since that date; an estimate of fungicide depletion |
| Daily rain amount | Inches of precipitation for that day |
| Rain probability (night / day) | Forecast chance of rain, roughly 10 pm and 10 am |
Row color matches the risk level: white (No risk), then Low, Moderate, and High.
3. Management guidance
3.1 Action by risk level
| Risk level | Recommended action |
|---|---|
| No risk | No action needed. |
| Low | If a first cover application has not been made, make the first cover fungicide application for apple scab. Otherwise, no action needed. |
| Moderate | Check the 5-day forecast. Make a cover application if two or more days with precipitation are predicted. |
| High | Make a cover application for sooty blotch and flyspeck. |
3.2 Fungicide options
To limit fruit finish blemishes, consider a cover application of one of the following treatments.
- 4 oz/100 gal Topsin + 1 lb/100 gal Captan 50W (or Captan-80, 10 oz/100 gal)
- 0.67 oz/100 gal Flint 50WG
- 1.6 oz/100 gal Sovran WDG
- 6.1 oz/100 gal Pristine WG
- 1 lb/100 gal Captan 50W (or Captan-80, 10 oz/100 gal) + 21 fl oz/100 gal ProPhyt
Always follow the label and consult the current Cornell Pest Management Guidelines for your state.
3.3 Getting the most accurate results
- Enter your actual petal fall date. The degree-day default is a regional estimate for McIntosh and will not match every block or variety.
- Enter every fungicide application date. Without one, the model cannot account for protection or wash-off, and rainfall is ignored in the risk calculation (see section 2.4).
- Use a station that represents your block. Leaf wetness is highly local, and it is the model's dominant input.
- Track by block. Petal fall and spray dates are saved per station and per year in your NEWA account, so keep separate entries for blocks that differ.
4. Data access
4.1 Current access
Model output is available through the NEWA website. The risk summary table on the model page includes a Download CSV button that exports the full season of daily values, not only the rows shown on screen. The export includes the date, days since petal fall, accumulated leaf wetness hours, and daily rain amount, plus days since the last fungicide application and rain since that application when a fungicide date has been entered.
4.2 Web service endpoint (planned for 2027)
A token-based web service endpoint for this model is planned for release in 2027. It will allow model output to be retrieved programmatically, without going through the website, for users who want to pull results into their own systems, dashboards, or farm management software.
Access will require a token issued to the requester rather than being open and anonymous, so that use can be attributed and supported.
The endpoint address, the process for requesting a token, the request and response formats, and any usage limits will be published in this section when the service is released. Until then, no endpoint is available and no tokens are being issued.
If you would like to be notified when the service becomes available, or you want to describe an intended use so it can be considered during design, contact Anna Wallis (see section 5.1).
5. References and credits
5.1 Primary contact
Anna Wallis, PhD Fruit IPM Coordinator Cornell Integrated Pest Management Email: aew232@cornell.edu
Anna is the primary contact for this NEWA model. Direct questions here first, including field use, interpretation of results, training, and interest in the forthcoming web service.
5.2 Primary reference
Brown, E.M. and Sutton, T.B. 1995. An empirical model for predicting the first symptoms of sooty blotch and flyspeck of apples. Plant Disease 79:1165-1168.
5.3 Model author
This NEWA disease forecast tool was authored by Dr. Kerik Cox, Plant Pathology and Plant-Microbe Biology, Cornell University, with input from Dr. Dan Cooley, University of Massachusetts. Contact Dr. Cox (kdc33@cornell.edu) with questions about the scientific content and recommendations.
5.4 Document author and revision history
This documentation page was written by Dan Olmstead, Cornell Integrated Pest Management (dlo6@cornell.edu). Contact him with corrections to this page, as distinct from questions about the model science.
| Version | Author | Notes |
|---|---|---|
| 20260730 | Dan Olmstead | First entry. Baseline information |
Content was derived from the model source in src/pages/sooty-blotch-flyspeck/ and verified against it on 2026-07-30. If the model logic changes, this page should be re-verified and its version incremented.
6. More information
- Cornell Fruit Resources - Tree Fruit IPM
- Cornell Pest Management Guidelines
- Tree Fruit Field Guide to Insect, Mite, and Disease Pests
- Sooty Blotch and Flyspeck Fact Sheet (PDF)
7. Figures
Figure 1. Model workflow
Figure 1. End-to-end workflow, from station selection through petal fall determination and daily accumulation to the recommended management action. Described in sections 2.1 through 2.4.
Figure 2. Risk level decision path
Figure 2. How the three lookup inputs resolve to a risk level. Leaf wetness hours is evaluated first, then the days counter, then rain. Equivalent to the full matrix in section 2.5.3.