This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Sweet, salty, crunchy or creamy—no matter how it's munched, the Virginia peanut has been a cash crop for the commonwealth for much of the past two centuries. But a fungal disease called Sclerotinia blight has decimated peanut plant populations in recent years, with severe outbreaks causing up to a 50% yield loss.
Virginia Tech researchers hope to help farmers detect and prevent its spread by building sensors that can detect infection early. "Early detection is critical because once the disease produces these irregular, rice grain-sized structures, it spreads quickly on the farm and will stick inside the soil for the next farming season," said Frank Erukainure, a doctoral candidate in the Department of Biological Systems Engineering. "It can survive for years and years, making it difficult to get rid of the disease." An Institute for Critical Technology and Applied Science doctoral scholar, Erukainure is the lead author of a paper published in ACS Agricultural Science & Technology describing the development and testing of these low-cost sensors.
His work on this 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. In 2024, farmers in southeastern Virginia harvested about 30,000 acres of peanuts (about 47 square miles) and brought in a cumulative $37.4 million. Historically, farmers have relied on time-consuming physical inspections to detect the fungus, often when it's already too late to stop its spread.
But if the fungus is detected early, the plant can be treated with a fungicide to help prevent spread to healthy parts of the plant. The sensor developed by Erukainure and his team at the Virginia Tech Digital Ag Technologies Lab, led by his adviser, Abhilash Chandel, assistant professor of precision agriculture and data management, detects the Sclerotinia minor pathogen as early as five days after infection. Physical symptoms, by contrast, sometimes do not appear for two months.
Peanut plant sap is extracted and placed on the sensor, which is composed of 3D-printed resin substrates and platinum electrodes. The sensors detect high concentrations of oxalic acid, a chemical that plants infected with the fungus Sclerotinia minor produce abundantly and that is present in their sap. Although the sensor's early detection capability has been validated in greenhouse trials, additional field testing is needed to determine how and when the technology will be deployed on plants in real farm environments.
As development continues, researchers will evaluate practical considerations such as cost, scalability and the number of sensors growers may need to effectively monitor large acreages—work that will shape how this emerging technology can ultimately help growers make faster, more informed decisions to enhance crop resilience and support more sustainable peanut production. The researchers plan to connect with farmers in the Tidewater region of Virginia to pilot-test these sensors in the next year, a key step in advancing the research from controlled trials to real-world production settings. In a previous study published in ACS Sensors, Erukainure and Chandel showed that a wearable microneedle sensor to monitor glucose and water stress in crop plants could provide real-time sensor readings.
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