Resources
|
Research Highlights

Research Highlights
Field-Specific White Mold Management

White mold in soybeans.

By Laura Temple

White mold thrives in soybeans during cool, wet conditions. The fungus that causes it, Sclerotinia sclerotiorum, can infect many other hosts and survive in the soil for five years or more, making it a long-term, annual challenge in many states, including Pennsylvania.

“White mold has caused soybean yield loss equal to an average of $62 per acre in Pennsylvania soybeans annually since 1996,” says Paul Esker, Extension plant pathologist and associate professor with Penn State University. 

Since 2019, the Pennsylvania Soybean Board has invested in research led by Esker to understand the pathogen and develop practical management strategies that are simple for soybean farmers to adopt. Based on the results, his team is developing a matrix of management options to help farmers easily evaluate how to best protect against white mold on their farms.

“Pennsylvania farms are diverse, often with complex crop rotations that can include cover crops and rely on no-till,” Esker explains. “Plus, the microclimates are fascinating, with marked differences from valley to valley that impact weather and more. All these factors create the need for field-specific management of white mold.”

Disease Distribution

His team surveyed fields across Pennsylvania for three seasons to understand regional distribution and genetic diversity of white mold. White mold can be found in every region of the state. Mold samples from diseased soybeans and soil samples yielded more than 150 isolates of the pathogen.

White mold and soil samples have been collected from 13 counties across Pennsylvania since 2019. The disease has been observed throughout the state.

“White mold is not highly diverse genetically across the state, based on samples from 13 counties across the state,” Esker says. “We are now conducting fungicide sensitivity tests to discover potential for resistance. We know fungicides have been applied to control white mold frequently in some areas, and not at all in others.”

To learn how the pathogen moves within fields, they sampled soil from 35 plots within eight chosen fields in 2020 and 2021. Esker reports that spatially, white mold appeared where it was expected – in hotspots along tree lines and in low spots with poor drainage.

“However, the appearance of the disease doesn’t overlap with the location of the pathogen in the soil,” he says. “We are learning how spores move in fields, which will inform management recommendations.”

Recommendations Matrix

Esker notes that while white mold can be found everywhere, it presents different challenges and risks regionally and at the field level. Its development, spread and severity are influenced by factors like planting date, weather conditions as soybeans flower, variety selection, row spacing, and other practices. 

“We want to encourage growers to do something to address white mold in soybeans,” he says. “We are creating a blueprint of options they can consider, with the clear understanding that not every farm can do the same thing.”

For example, Esker says that altering planting dates can reduce while mold pressure in some valleys, but that isn’t an option in other areas. 

To provide guidance for farmers, his team is designing a series of questions about white mold pressure in each field. The answers will lead to options for practices that can be modified or adopted to address it. The tool is designed to help soybean farmers pinpoint options that will work for a given field. 

Sporecaster App Validation

Esker’s research also investigated the value of the Sporecaster app to Northeastern soybean production. The app is a tool developed by the University of Wisconsin-Madison to predict the need for white mold management in the Upper Midwest. However, regional differences between production practices and climate influence its accuracy.

His team monitored white mold pressure in 23 fields across Pennsylvania in 2021 to validate the accuracy of the Sporecaster app.

“Overall, we found that the app was more sensitive to white mold pressure than our conditions warranted,” he reports. “However, based on what we observed in 2021, we are making adjustments for using the app to see if we can successfully adapt it for our area.”

In 2022, the team will again monitor white mold pressure to see if these changes improve the accuracy of the app for this region. If the fine-tuning is successful, it could become a helpful information source to incorporate into the recommendation matrix.

“Relying on Sporecaster alone will not be sufficient,” Esker adds. “We will be encouraging farmers to use the recommendations matrix to sit down and do a deep dive for each farm to protect soybean yield from white mold losses. And, because Sclerotinia sclerotiorum can infect other crops, this process will generate information to address white mold differently for an entire operation.”

This project was funded by the soybean checkoff. To find research related to this research highlight or to see other checkoff research projects, please visit the National Soybean Checkoff Research Database.