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

Sap flow is one of the clearest indicators of how plants respond to their surroundings. As water evaporates from microscopic pores in leaves, known as stomata, it creates tension that pulls water upward through the plant’s xylem. This stream carries water and dissolved minerals from the roots toward the leaves, linking plant hydration to light, temperature, humidity and soil conditions. Conventional approaches for measuring sap movement can be bulky, rigid or difficult to attach to narrow stems, especially in grasses and other plants whose tissues are thin, flexible and easily damaged.

The newly described system is based on two design concepts that are increasingly important in soft wearable electronics. The first is magnetic sensing, which can detect changes in the position or separation of magnetic components without requiring a rigid electronic structure to press directly against the plant. The second is kirigami, an engineering strategy that uses carefully arranged cuts in a thin material to make it stretch, bend and expand. Unlike origami, which relies primarily on folds, kirigami introduces cuts that allow a structure to accommodate complex shapes and mechanical motion.

For a plant-mounted sensor, that flexibility is more than a visual feature. A stem can bend in the wind, change diameter as it grows and respond dynamically to water availability. A rigid device may restrict these movements or lose contact with the plant, producing unreliable readings. A kirigami-based structure can distribute strain across its patterned surface, reducing localized pressure while maintaining a functional connection between the sensing elements. The magnetic configuration then translates mechanical changes associated with sap flow into measurable signals.

The central innovation is the attempt to sense a physiological process indirectly, through the tiny mechanical effects generated as water travels within the plant. Sap flow is not simply a visible stream that can be tapped like fluid in a pipe. It is influenced by pressure gradients, tissue elasticity and the plant’s changing water status. By placing a compliant wearable structure around or alongside a fragile stem, the researchers seek to capture these changes without cutting the plant open or inserting probes into its vascular tissue. This non-invasive approach could make long-term observations more practical.

The choice of grass-like plants is particularly significant. Their slender stems and leaves are common in agriculture, ecology and environmental monitoring, yet their small dimensions make them difficult targets for standard instrumentation. A sensor that is too heavy can alter posture and wind response; one that is too stiff can interfere with growth; and one that requires invasive installation may damage the very transport pathway under investigation. A conformable magnetic kirigami device offers a route toward measurements that follow the plant’s movement rather than forcing the plant to adapt to the instrument.

Continuous sap-flow monitoring could provide information well beyond whether a plant is “hydrated” or “dry.” Changes in the signal may reveal how plants respond to drought, heat, shade, sudden changes in humidity or restricted water uptake. In controlled experiments, such data could help researchers compare plant varieties and study the timing of stress responses. In agricultural settings, distributed sensors might eventually support irrigation strategies that respond to plant demand rather than relying only on soil moisture or fixed schedules. Such applications remain dependent on calibration, durability and field validation, but the underlying concept moves plant monitoring toward a more intimate form of wearable technology.

The work also reflects a broader shift in electronics, from rigid devices built around conventional mechanical assumptions to soft systems designed for living surfaces. Human wearable sensors have already demonstrated the value of flexible materials that move with skin, muscles and organs. Plants present a different set of engineering problems: their surfaces can be waxy, their stems grow, their tissues transport fluid internally, and their movements are driven by wind, light and water balance rather than muscles. Magnetic kirigami sensing adapts ideas from flexible electronics to this biological environment, illustrating how device architecture can be shaped by the mechanics of the organism being measured.

The most compelling promise of the technology is its potential to make plant water transport continuously observable without turning the plant into a laboratory specimen. If refined for large-scale use, networks of miniature sensors could generate real-time maps of plant stress across greenhouses, fields or ecological sites. Those measurements could complement imaging, weather data and soil sensing, helping scientists connect invisible vascular activity with visible growth and survival. For now, the study presents a striking demonstration of how a patterned, flexible structure and a magnetic sensing principle can open a new window into fragile plants—one in which the instrument bends, stretches and listens while the plant continues to grow.

Subject of Research: Magnetic kirigami-based wearable sensing of sap flow in fragile grass-like plants

Article Title: Magnetic kirigami-based wearable plant sap flow sensor for fragile grass-like plants

Article References: Zou, Y., Chai, Y., Sa, H. et al. “Magnetic kirigami-based wearable plant sap flow sensor for fragile grass-like plants.” npj Flexible Electronics (2026). https://doi.org/10.1038/s41528-026-00630-9

Image Credits: AI Generated

DOI: 10.1038/s41528-026-00630-9

Keywords: plant sap flow, wearable sensor, magnetic sensing, kirigami, flexible electronics, grass-like plants, plant physiology, non-invasive monitoring, smart agriculture, plant water transport