Tarspotter, the Corn Tar Spot Disease Forecaster

For Apple: https://apps.apple.com/us/app/tarspotter/id1454584176

For Android: https://play.google.com/store/apps/details?id=ipcm.tarspotcalculator&hl=en_US&gl=US

The purpose of Tarspotter is to assist farmers in making management decisions for tar spot in corn. The best time to manage tar spot is during V8 to R4 growth stage. Tar spot fungal spores which infect corn, leading to the development of tar spot. University research has indicated that the appearance of Tar spot fungus can be predicted using several variables including weather. Based on this research, models have been developed to forecast the risk of Tar spot fungus being present in a corn field. Farmers can easily input site-specific information about their corn field into this app, which combines this information with the research-based models to predict the best timing for tar spot treatment.

Tarspotter uses GPS coordinates to determine if weather has been favorable for the development of Tar spot fungus during corn flowering in a specific field. Models in the app use temperature, dewpoint, humidity, and precipitation to predict favorable conditions for most corn growing regions. Based on these predictions and crop phenology, a site-specific risk prediction is generated.

To begin:

The first step to create a new tar spot risk forecast is to enter information about a field. This includes field name and GPS location. You may use the map or enter custom GPS coordinates using the text input. Entering notes is optional. Next tap ‘Done’ and the field information will be saved in your ‘Field List’.

Open the Field List and tap on a field name to view the forecast screen. The forecast screen is displayed next, where some basic field information is required to progress. You may change the Action Threshold by +-15% to account for your own preference of management. Each field can have it’s own Action Threshold level. The default level is 35%. In addition, the forecast models use fungicide applications that have occurred within the last 14 days. Generally, the optimum time to run the models is between V10 to R3 growth stages, however, Tar spot fungus can be present at anytime on some varieties in some environments.

Choose a date for the forecast. The calendar defaults to the present date. Choose any day previous to this date to run historical risk calculations. Also, the models only run when the app is able to connect to the internet and download a complete set of weather for the field’s GPS location.

If Tarspotter predicts High risk (a red indication is displayed) in your area for your planting scenario, field scouting or a fungicide application would be recommended. High risk scenarios can develop quickly. If Low risk (blue indication in the display) is predicted, then infection is not likely. However, Tarspotter should be consulted again in a week to monitor the situation. When Tarspotter indicates Active 0% or Inactive, infection is not likely at that time.

There are two buttons at the top of the forecast screen. The ‘History’ button will display a list of previous risk forecasts for a field. The ‘Email’ button will create an email containing the risk forecast(s) for a field that can be shared for further record keeping or management. A CSV (spreadsheet compatible) file is attached with all risk forecast results to allow desktop computer data management and further record keeping.

If a field receives a High Risk prediction using Tarspotter, we recommend consulting your local Extension personnel or resources for the best fungicide management options for your area.

To use Tarspotter in other locations, add new fields to your Field List. You can edit the Field List by swiping to delete fields. After you have used Tarspotter on several fields, you can create an email containing the forecast history of all the fields using the ‘Export’ button.

Version 1.25

Screen shots are from Version 1.23, and will be updated shortly.

This tool is for guidance only and should be used with other sources of information and professional advice when determining risk of tar spot development. The information in the app and this publication is only a guide, and the developers assume no liability for practices implemented based on this information.

The Tarspotter risk models were developed at the University of Wisconsin-Madison.

We would like to acknowledge the following groups and individuals for their work and support.

UW-Madison Integrated Pest Management Program

UW-Madison Nutrient and Pest Management Program