Seedling emerging from ground Seedling emerging from ground Seedling emerging from ground

Wind, Rain and Winter: How Weather Spreads Crop Disease

June 2, 2023

Dr. Zach Hansen
Weather Science Team Manager at Climate

Are the weather and plant disease connected? Very much so. A portion of my team’s work has been dedicated to building predictive models that connect the complex relationship between plant pathogens and relative humidity, temperature, wind speed and more. Here are a few overlooked factors that could silently be impacting the presence of disease in your fields.

The Winter Pathogen Time Bombs

The threat of disease can extend beyond the growing and even harvest season. As new crops emerge in spring, certain pathogens will be waiting within this year’s crop residue. If the environmental conditions are favorable, the disease may spread and infect next year’s crop. Proper rotation and tillage can help reduce future disease risk by burying the pathogen into the soil and allow it to break down over time.

Illustrated animation of a crop growing and being harvested. Pathogens are shown in the soil over the winter, which come up on the crop the following season.
Some pathogens can survive the winter in the soil, waiting to infect seedlings in the spring.

Fungi’s Favourite Form of Travel

Fungi reproduce by releasing tiny spores. When a gust of wind moves through, these spores can catch a free ride to another plant. This process keeps repeating as long as the wind current is strong enough. Given wind has been forecasted for a long time, we can now predict how certain plant diseases will spread in the same way that we forecast pollen during allergy season. Southern Rust, for example, is driven by large-scale wind patterns, so if we can predict the wind, we can use machine learning to predict the likelihood that Southern Rust (in corn) will spread in your field.

Animated Illustration showing fungi spores travelling on a breeze and moving from one crop to another.
Carried only by a breeze, fungi can soar across a field and land on neighboring crops.

The Fungus Catapult

As rain falls from the sky, fungi land on crop leaves, which creates a splash effect or can even allow the leaf to bend and “fling” the fungi forward. Tiny fungal spores can then land on another leaf and infect more plants. And the process repeats itself.

This type of disease spread doesn’t occur in a meaningful way during every rainfall. It needs to pass a certain threshold. If you look at a soybean disease like frogeye leaf spot, this pathogen relies on ground disturbance, which can be from machinery moving through the field, or the rainfall. This makes tracking those weather events even more important.

Animated illustration of rain hitting a crop, moving a fungal spore from one plant to another.
The force of rain hitting a crop leaf can create enough momentum to send fungal spores flying through the air.

How Data Science Can Improve Disease Management

When you use scouting tools like those on FieldView™, every walk of the field can build a rich, searchable history of your field health. You don’t need to say, “I think we had this blight a few years back,” you can know exactly which fields were infected, what time of season it occurred and even look at yield data to compare the effectiveness of different treatments.

Image generated in iPad showing the Scouting map layer, with red, green and yellow areas to illustrate variability.
High-Tech Fungicide Timing

Many inputs have an optimal window of time to apply them. With fungicides in particular, the opportunity to add the right amount, at the right time, can be extremely difficult to calculate in your head. That’s why our team is focusing on how emerging technologies, like machine learning, that can comb through the endless list of factors; past rainfall, current temperature, relative humidity, the rainfall that may occur in the next 24 hours or next week, windspeed, thunderstorms, etc. Using this elite level of computation, we’re working to deliver advice on fungicide applications that is both easy to understand and backed by an immense database of information. Deciding when and how much to spray will never be easy. With advancements in neural networks and machine learning, we can make finding that answer considerably easier and more effective. The weather will always change, so we need as many tools as possible to think ahead of it. At least as much as we can.

About the Author

Dr. Zach Hansen is the Weather Science Team Manager at Climate. He has spent nearly three years at Climate, in a variety of roles all centered on weather. In his current role, he and his team work to ensure that weather data is used effectively in predictive models that help growers make a variety of decisions. Zach received his undergraduate degree in Atmospheric Science from the University of Utah and his PhD in Atmospheric Science from the University of Wisconsin-Madison. Prior to joining Climate, Zach worked as a research scientist at Nanjing University in China, where he examined the life cycles and characteristics of thunderstorms on a variety of scales