Dollar Spot Model

The Smith-Kerns Dollar Spot Prediction Model is a logistic-based model that uses a 5-day moving average of daily relative humidity and daily average air temperature to create a probability that dollar spot will occur on a given day.  The model was created by Dr. Damon Smith and Dr. Jim Kerns and has been validated through years of additional field research conducted primarily in Wisconsin but also in Oklahoma, Pennsylvania, Mississippi, Tennessee, Connecticut, and New Jersey.  The model can be used by golf course superintendents to more accurately time control measures to suppress dollar spot.

What is the Smith-Kerns Dollar Spot Model?

The peer-reviewed paper detailing the model development and validation has been published in PLOS One and can be accessed here:

In brief, the model uses logistic regression to determine the probability that a particular event will happen.  In our case, that event is the appearance of dollar spot.

The first step in this model is to use 5-day moving averages of average daily relative humidity and average daily air temperatures in Celsius to create a logit (µ) as follows:

Logit (μ) = -11.4041 + (0.0894 X MEANRH) + (0.1932 X MEANAT)

The logit (µ) is then inserted into the following equation to give the probability:

Probability of a dollar spot epidemic = elogit (μ)/(1 + elogit (μ)) X 100

Note that the ‘e’ in the above equation is referred to as ‘Euler’s Number’ and is approximately equal to 2.718.

Also note that since dollar spot is not active at temperatures below 10°C or above 35°C the model should be considered inactive when 5-day average temperatures are above or below those numbers.  In rare cases, the model may indicate dollar spot activity is likely below 10°C or above 35°C when relative humidity is very high, but this should be ignored.

How does the model work?

One unique feature of this model is that it does not tell users when to spray, it simply gives them a probability of dollar spot occurring.  So the first thing users will need to do is establish a spray threshold unique to their course.  Work done at Wisconsin on ‘Penncross’ creeping bentgrass determined that a probability of 20% provided effective disease suppression, so that is a reasonable starting point.  However, depending on the type of grass you have, the cultural practices you employ, and the environmental conditions at your facility you might have to use a higher or lower threshold.

Once the spray threshold has been determined, a fungicide reapplication interval needs to be assigned for each application.  During this reapplication interval you should theoretically be protected from dollar spot, no matter how high the probability is, and the model can mostly be ignored.  Once the reapplication interval is reached, the model threshold can again be used to determine the next application.

For example, in the figure below, note that the first time the model probability goes above our spray threshold is on May 21st, which is when we apply Emerald at 0.18 oz.  We expect to get 28 days of control out of this application, so we essentially ignore the model output for 28 days.  However, on day 29 the model probability is below the threshold, so we wait to spray again until the threshold is reached the following week on on June 27th.  This process is repeated throughout the growing season.

How can you use the model?

A self-calculating excel file can be used to calculate dollar spot probability by simply importing daily average relative humidity and daily average temperature for your location.  Two different excel files can be downloaded:

  • If you prefer to input high and low temperature in Fahrenheit then download  the following excel file: SmithKernsDollarSpotModelCalculator_Fahrenheit
  • If you prefer to input high and low temperature in Celsius then download  the following excel file: SmithKernsDollarSpotModelCalculator_Celsius
  • Manually downloading the weather data into the excel files above can be cumbersome.  Jason Haines, a golf course superintendent in British Columbia, has developed a series of files that will automatically download your local weather data into the above files and automatically calculate your dollar spot probability.  For more information on these files please visit his site:

In addition, you can access the Smith-Kerns Dollar Spot model through the following groups:

Funding Acknowledgement

We would also like to acknowledge the United States Golf Association, the Wisconsin Turfgrass Association, and the Oklahoma Turfgrass Research Foundation for providing funding for this project.

Questions?  Feedback?

For any questions or feedback about the Smith-Kerns Dollar Spot Prediction Model please contact:

Paul Koch, Ph.D.
Assistant Professor
Department of Plant Pathology
University of Wisconsin – Madison