Low-cost electrochemical sensors catch peanut fungus days before symptoms appear

Peanuts have been woven into the agricultural identity of Virginia for the better part of two centuries, a crop that shows up in everything from school lunches to ballpark snacks. But beneath the soil, an invisible enemy has been quietly undermining that heritage. Sclerotinia blight, a fungal disease caused by the pathogen Sclerotinia minor, has devastated peanut plant populations in recent years, and in severe outbreaks it can wipe out as much as half of a grower’s yield. For farmers who depend on the crop for their livelihoods, the difference between a healthy field and a ruined one often comes down to timing — how quickly an infection is spotted and how fast it can be contained.

Researchers at Virginia Tech believe they have found a way to shift that timing dramatically in farmers’ favor. A team at the university has developed a low-cost electrochemical sensor capable of detecting Sclerotinia blight in peanut plants as early as five days after infection. By contrast, the physical symptoms that farmers have traditionally relied upon — the telltale signs of fungal invasion visible on stems and foliage — sometimes do not appear for as long as two months. That gap between infection and visible disease is precisely where the pathogen gains its advantage, spreading silently through a field while a grower remains unaware that anything is wrong.

The research, led by Frank Erukainure, a Ph.D. candidate in the Department of Biological Systems Engineering and an Institute for Critical Technology and Applied Science Doctoral Scholar, was described in a paper published in ACS Agricultural Science & Technology. Erukainure’s work on the project earned him the 2026 Boyd-Scott Graduate Research Award, one of the American Society of Agricultural and Biological Engineers’ top honors for graduate scholarship. The recognition underscores how significant the problem is: Sclerotinia blight is not a marginal nuisance but a persistent threat to one of Virginia’s most valuable row crops.

The stakes are easy to quantify. In 2024, farmers in the southeastern region of Virginia harvested roughly 30,000 acres of peanuts, bringing in a cumulative 37.4 million dollars. Historically, growers have relied on time-consuming physical inspections to detect the fungus, walking their fields and examining plants for signs of disease. The trouble with that approach is that by the time the fungus produces its characteristic structures — irregular, rice grain-sized formations that Erukainure describes as the disease’s most visible calling card — the outbreak is often already beyond easy control. Once those structures appear, the disease spreads quickly across the farm, and the pathogen settles into the soil, where it can survive for years, making eradication extraordinarily difficult.

The technical insight behind the new sensor lies in plant biochemistry. When peanut plants are infected with Sclerotinia minor, they produce abundant quantities of oxalic acid, a chemical compound that accumulates in the plant’s sap. This elevated oxalic acid serves as an early biochemical fingerprint of infection, a molecular distress signal that appears long before any outward symptom. The Virginia Tech sensor is designed to read that signal directly. Peanut plant sap is extracted from the plant and placed on the sensor, which is built from 3D-printed resin substrates fitted with platinum electrodes. The electrochemical platform measures the concentration of oxalic acid in the sample, flagging infections that would otherwise remain hidden for weeks.

The choice of materials is not incidental. By relying on 3D-printed resin and a relatively simple electrode arrangement, the team has kept the sensor inexpensive to produce, a critical consideration for any technology that hopes to reach working farms. Cost, scalability, and the number of sensors a grower would need to monitor large acreages are all questions the researchers are actively evaluating as development continues. These practical factors will shape how the technology is ultimately deployed on plants in real farm environments, and the team is candid that additional field testing is needed before the sensors can move from validated greenhouse trials into routine agricultural use.

The early detection capability itself has already been validated in greenhouse trials, an important milestone that demonstrates the sensor works under controlled conditions. If the fungus is caught early enough, the infected plant can be treated with a fungicide to prevent the disease from spreading to healthy parts of the plant and to neighboring crops. That intervention window — the days between infection and visible symptom onset — is exactly what the sensor opens up. Instead of reacting to an established outbreak, growers could treat a nascent one, protecting both their yields and the soil beneath their fields from long-term contamination.

The peanut blight sensor is not the team’s first foray into plant-mounted diagnostics. In a previous study published in ACS Sensors, Erukainure and his advisor Abhilash Chandel, assistant professor of precision agriculture and data management, demonstrated a wearable microneedle sensor designed to monitor glucose and water stress in crop plants, providing real-time sensor readings directly from living plants. That device attaches to the stem of a plant and streams plant health data to a phone application, giving growers a continuous window into the physiological state of their crops. The team now hopes to develop a similar wearable sensor for detecting Sclerotinia blight in peanut plants, extending the same continuous-monitoring philosophy to fungal disease.

Chandel frames the broader shift in stark terms: technologies like these are transforming plant production. By monitoring plant health in real time, he argues, such sensors enable proactive intervention, improving crop resilience, productivity, and sustainability. The vision is one in which disease management moves from periodic, labor-intensive scouting to continuous, data-driven surveillance — a model familiar from precision medicine, applied instead to the physiology of crops. For a disease like Sclerotinia blight, whose survival structures can lurk in soil for years and sabotage subsequent growing seasons, the value of catching an infection at day five rather than day sixty is difficult to overstate.

The next step is already on the calendar. The researchers plan to connect with farmers in the Tidewater region of Virginia to pilot test the sensors in the coming year, a crucial transition from controlled greenhouse experiments to the messier realities of commercial production. That pilot phase will determine how the technology performs across variable field conditions, how growers integrate it into existing management routines, and whether the promise of early detection translates into measurably healthier harvests. If it does, a modest 3D-printed sensor with platinum electrodes could become an essential tool in protecting a crop that Virginia has grown for two hundred years — and in demonstrating that the future of plant disease management may be measured not in seasons, but in days.

Subject of Research: Electrochemical biosensor detection of Sclerotinia blight fungal infection in peanut crops

Article Title: Protecting the peanut: Sensors help fend off fungus

Article References: Protecting the peanut: Sensors help fend off fungus. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: peanuts, Sclerotinia blight, Sclerotinia minor, electrochemical sensor, oxalic acid, plant disease detection, precision agriculture, Virginia Tech, fungicide, wearable plant sensors, crop yield loss, 3D-printed sensors