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Warning systems: using environmental knowledge against plant pathogens

Content Author:
Jose Gonzalez

By José González, Research Associate II, Iowa State University (


Farmers have factored weather conditions into disease management decisions since farming began. So “disease-warning systems” – using the weather to assess the risk of a disease outbreak - are really nothing new. But these systems have gained a foothold with specialty crop growers in recent years because they can weigh the risk more accurately and consistently than empirical experience alone.

One force driving the development of disease-warning systems is technology. It’s more convenient and less expensive to measure, store, and process weather data than ever before. Whether you make weather measurements on your own farm or use weather estimates from networks like NEWA (link here), this information is now more accessible than ever before.

The other technology that’s mushroomed in recent years is computing. Processing of weather data into spray advisories can be done by your personal phone, tablet, datalogger, or laptop.

Plant pathologists and farmers have provided the field-based science and experience that enable computers to translate weather data into spray timing advice.

There are many warning systems for timing sprays against apple diseases. They have gained favor with some growers because they can save money by reducing the number of sprays needed to control a disease.  This blog will focus on only two types of warning systems: for fire blight, and sooty blotch and flyspeck (SBFS).

Figure 1. Fire blight (left) and SBFS (right) symptoms on apple.
fire blight sooty blotch and flyspeck

Fire blight. Although outbreaks of fire blight (caused by Erwinia amylovora) can seem erratic in occurrence, a comprehensive model called MARYBLYT, developed by USDA and University of Maryland (MD) researchers can predict four of the five types of infection associated with fire blight: blossom, canker, shoot, and trauma blight. Fire blight bacteria survive the winter in cankers, and can infect new plant tissue after spread by insects, wind, or rain. Conditions such as proportion of opened flowers, accumulated hours of temperatures above 65⁰ F, wetting events (rainfall or dew), and daily average temperatures of 60⁰ F or more are among the model’s inputs. When the weather conditions combine to create a high risk of infection, the alarm goes on and a spray advisory (usually for a streptomycin bactericide) is issued. Newer versions of MARYBLYT also track residual efficacy of each spray to help growers decide when another spray is needed.


Sooty blotch and flyspeck (SBFS). The newest model for SBFS in the Midwest is simpler than for fire blight.  All that’s needed is to track hourly relative humidity (RH) starting right after first cover spray. The spray threshold is reached when the total number of hours above 90% RH since the first-cover-spray date reaches 385. Then it’s back to calendar-timed sprays for the rest of the growing season. Using this RH-based warning system in Iowa has saved an average of 2.6 sprays per season. This means less cost and less time spent on fungicide spraying.


Connection to the CPPM project. One of the main goals of our ongoing USDA-CPPM research project is to learn how these two warning systems behave when used in combination with the Intelligent Sprayer. The Intelligent Sprayer is a new type of airblast sprayer that uses much less volume per spray by directing sprays more efficiently. This combination can be economical in two ways: cutting down on the number of sprays (with the warning systems) and using less spray with each trip (with the Intelligent Sprayer). Piggybacking these IPM tools have the potential to make a significant dent in the cost and time required to control major apple diseases.

We’ll be sharing our 2020 season results very soon, and are anxious to have your feedback. We’ll have two more years of Iowa and Ohio field trials on the project, so please stay tuned!


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