NDSU assistant professor receives USDA-NIFA award to help manage CLS in sugarbeets

NDSU assistant professor of bioenvironmental and structural engineering Xiaoyu (Iris) Feng has received a $728,000 award from the United States Department of Agriculture’s National Institute of Food and Agriculture (USDA-NIFA) for her research project entitled, “Portable Dual-Function Biosensor for Early Detection and Management of Sugarbeet Foliar Diseases.”

Feng is developing a portable, dual-function biosensor for early detection of Cercospora leaf spot (CLS) disease in sugar beets. The biosensor will be developed to allow growers to detect infections quicker than traditional scouting methods to allow for better management of the disease. A 2024 survey from the Beet Sugar Development Foundation estimated that CLS could cause losses exceeding $900 million nationally in a single year if left unmanaged.

Current CLS management strategies include using resistant varieties and applying fungicides. Some have been effective in controlling CLS but they pose environmental and health risks or are not scalable. One of these, polymerase chain reaction (PCR), has been widely used for early CLS detection, but it is expensive and labor-intensive, limiting its application at large scale in field monitoring.

“Historically, severe CLS outbreaks have caused substantial economic losses in North Dakota and Minnesota due to reduced production and increased fungicide costs,” Feng said. “Because of these impacts, early detection and timely management are critical.”

This is Feng’s first major research project on sugar beets, but her past research has focused heavily on precision agriculture, sensing technologies and data-driven decision-support systems.

“USDA-NIFA's support allows us to bring together experts in engineering, plant pathology, biosensing, and agricultural economics to develop practical tools that can ultimately benefit growers and strengthen the sugar beet industry,” Feng added. NDSU assistant professor Extension specialist Eric Branch is Co-PI and brings extensive sugarbeet plant pathology experience to the project.

“As an agricultural engineer, I am interested in developing and deploying technologies that help producers make better management decisions,” Feng said. “While much of my previous work has focused on sensing technologies and environmental monitoring, I saw an opportunity to apply those engineering tools to one of the most important crops in North Dakota.”

According to a 2023 study by the NDSU Department of Agribusiness & Applied Economics, the Red River Valley sugarbeet industry contributes an estimated economic impact (direct and secondary) of $6.1 billion dollars in North Dakota, Minnesota, and Eastern Montana.

Feng describes her new biosensor as “an early warning system for sugar beet diseases,” designed to quickly and accurately identify genetic material from the pathogen. The portable unit will detect the fungus responsible for CLS, allowing growers to detect infections earlier than with usual scouting methods.

CLS begins as small spots on leaves, but as it progresses, the spots expand and merge, causing significant damage. “The plant attempts to grow new leaves to replace the damaged ones, but its ability to photosynthesize and produce sugars is reduced,” Feng said. “To exacerbate the issue, producing new foliage requires energy that would otherwise be stored as sugar in the root, so growers impacted by CLS often experience reductions in both root yield and sugar concentration which directly impacts profitability.”

The technology will be optimized in laboratory and greenhouse settings at NDSU before tested it in North Dakota and Minnesota sugar beet fields.

An exciting aspect of the research for Feng is the possibility that the technology may have an impact beyond sugarbeets. “Our goal is to move disease detection from the laboratory to the field, giving growers faster access to information with lower costs that can help protect yield and reduce unnecessary inputs,” she said. “Biosensor technology has the ability to detect many different plant pathogens and in the future, similar systems could be used to monitor additional diseases in other crops grown throughout the state and across the country.”

“We want to provide growers with a practical tool that helps them identify disease pressure earlier and more easily so they can make informed management decisions,” Feng added. “Earlier detection will improve fungicide timing, reduce unnecessary applications, lower production costs, and help preserve yield and sugar quality. We hope this technology will contribute to a more profitable and sustainable sugar beet industry in our region.”