Wind, Rain and Winter: How Weather Spreads Crop Disease

Fungi’s Favorite 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. 


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. 


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

Data-Driven Scouting


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.

High-Tech Fungicide Timing

Many inputs have an optimal window of time to apply them. But 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 my team is focusing on how emerging technologies, like machine learning, that can comb through this endless list of factors. We look at 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. But with advancements in neural networks and machine learning, we can make finding that answer easier and more effective. Because the weather will always change, so we need as many tools as possible to think ahead of it.