Research Highlights

Deep Sensing to Monitor Soybean Health

In this article, you’ll find details on:

• An array of sensors for soybean plants provides data that goes beyond symptoms to the root cause of issues.
• Innovative research has developed three unique sensors that detect viruses, pesticides and stress in soybeans.
• Making these sensors affordable and easy to use will allow farmers to use deep sensing and data collection to better manage their soybean fields. 

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By Laura Temple

What if soybeans could explain how they are doing?

Perhaps they can — with a little help.

Liang Dong, professor of electrical engineering and director of the Microelectronics Research Center at Iowa State University, is creating an array of sensors that collect data allowing soybeans to “tell” researchers and farmers about their condition. He and Steve Whitham, professor of plant pathology at Iowa State, are focusing on early detection of potential issues. 

Iowa Soybean Research Center funding initiated this effort to better monitor key plant health indicators in soybeans. The ISRC matches soy checkoff investments from the Iowa Soybean Association with other industry funds to support innovative soybean research, providing a strong foundation for further work. For example, Dong and his collaborators have leveraged the investment in this work into further funding from the USDA-National Institute of Food and Agriculture.

“These sensors go beyond the visible symptoms that point to issues,” Dong says. “They look deeper, down to the molecular level, to identify the root causes of problems early. Their deep sensing capabilities help us better understand plants and develop smarter, earlier, more effective solutions for farmers.”

Three different sensors targeting viruses, pesticides and molecules produced under stress demonstrate the potential to monitor key factors in soybean responses to the environment. While Dong expects crop researchers to find value in these sensors, the ultimate goal is to create affordable sensors for farmers and agronomists to use in soybean fields.

Early Disease Detection

One leaf sensor detects the presence of bean pod mottle virus, a disease spread by bean leaf beetles that reduces soybean quality and yield. Dong’s team invented a new sensitive material that identifies the virus and the amount present in a soybean plant.

“The sensitive material in the sensor identifies and interacts with the virus, even before symptoms begin to appear,” he explains. “It then sends out an electrical signal based on how much of the virus is present.”

This plant virus-sensing technology takes inspiration from methods in human medicine, but Dong believes it’s something new for agriculture. He sees potential for the same concept to be applied to other soybean diseases.

Pesticide Presence

Another sensor uses microneedles to detect pesticide residue. It can be used on soybean leaves, soil or water.

“This technology allows us to see how much pesticide sticks to the leaf surface or how much gets absorbed by the plant,” Dong says. “It also goes a step further, measuring leftover residue in the soil or water.”

In the development process, his team focused primarily on detecting dicamba residue. However, the technology isn’t limited to that herbicide. It can be used to spot residue from other pesticides. Using the sensor in plants and the soil provides a fuller picture of what’s happening inside and around the plant.

“This information helps us understand how pesticides work,” he adds. “We get a deeper look at what gets into plants and where the rest of the application goes, providing a full spectrum of information about pesticide movement.”

Sensing Soybean Stress

The third sensor detects the level of hydrogen peroxide in a soybean plant. Soybeans produce more hydrogen peroxide when under stress. The amount varies based on the degree of that stress, caused by factors like drought, heat, waterlogging, disease pressure and more.

“We have inoculated soybeans with pathogens to see how that affects hydrogen peroxide levels,” Dong explains. “In some cases, the change is very slight, but our sensor can detect that change within a minute.”

This sensor also uses microneedles, but the sensing material reacts to hydrogen peroxide. The ability to rapidly detect slight changes in these levels deepens understanding of soybean response to stress.

Affordable, Accessible Data Collection

Dong’s current focus is to enhance measurement reliability and reduce the size and cost of creating these sensors. His team is also working to create two methods to use them.

• Wearable sensors continuously collect and transmit data wirelessly, ideal for agronomic research.
• A hand-held version of the sensors would allow for spot collection of data over a broad area, which would be more practical for farmers and agronomists monitoring soybean fields. 

“Our goal is for the cost of each sensor to be less than $1,” he says. “This would allow more users to gather data, so they understand what is happening in their fields and effectively address issues at their root.”

He believes integrating data gathered inside and outside soybeans will allow the plants to “tell” farmers what they need to thrive each season.

Additional Resources

Iowa State Professor Creates Plant Sensors for the Early Detection of Soybean Diseases Through ISRC-funded Project – ISRC article

Detailed Data Supports Irrigation Management Decisions – SRIN article

Scientists Use Drone Cameras to Spot Herbicide-Resistant Plants – GROW article

Bean Pod Mottle of Soybean – Crop Protection Network article

Meet the Principal Investigator: Liang Dong

Published: May 19, 2025