The research will aim to develop a diagnostic device for economical, rapid testing of soybean pathogens in order to detect diseases at an early stage to reduce their spread and minimize damage. The technology will aid with rapid monitoring of soybean crops during the growing season to help with making management decisions to protect yield potential. Also, the technology will be used by researchers to better understand pathogenic stress in soybean at different stages and under diverse conditions.

The project is to develop sensors for low-cost monitoring of several key fungal, viral, and bacterial diseases. The goal is early detection of diseases at a stage when there are often no symptoms, to reduce the risk of disease spreading. The sensor will enable real-time disease monitoring during the growing season that can help farmers to make important management decisions for protecting yield potential.

We will deliver an array of non-invasive or minimally invasive electrochemical sensing elements specific to multiple critical biomarkers in the plant. The sensor will be designed, manufactured, and tested towards high detection specificity and sensitivity with low cost.

Updated February 27, 2023:
We have developed a low-cost sensor capable of detecting bean pod mottle virus (BPMV) in soybean plants. The sensor utilizes virus-specific nanocavities to recognize BPMV. The sensor uses a differential pulse voltammetry technique for accurate and rapid detection of BPMV in soybean leaves. The sensor has demonstrated a high sensitivity of 100 µA ng-1 mL cm-2 over a linear range of concentration from 0.01 to 100,000 ng mL-1 with a limit of detection of 10 pg mL-1. The intra-assay coefficient of variation is <10% for standard samples and <15% for real samples from leaves.

We have developed a low-cost sensor that can detect salicylic acid of soybean plants under various stresses. The sensor is formed with an array of microscale needles that can be attached to the leaf of soybean. The sensor uses gold nanoparticles as catalysts on the surface of the needles to support redox reactions with salicylic acid. The sensor has demonstrated its ability to detect the target molecules in the soybean leaf with a sub-ppm resolution.

We are currently writing papers to document this effort.

Updated October 14, 2024:
We developed a series of wearable plant sensors designed to monitor critical indicators of plant health directly in the field. These include a reactive oxygen species sensor that uses microneedles coated with a biohydrogel to measure hydrogen peroxide, a key marker of plant stress, in soybean plants. This sensor delivers rapid results within 1-3 minutes and provides an easy, low-cost way to track plant responses to stress. Additionally, we developed a virus detection sensor for the bean pod mottle virus (BPMV) in soybean plants, utilizing a specialized material that selectively binds to virus particles, delivering results in under 2 minutes. This sensor surpasses traditional lab tests in speed and convenience, enabling real-time virus monitoring in the field. Finally, we created a pesticide uptake sensor that measures how much dicamba herbicide is absorbed by soybean plants. Using microneedles designed to bind dicamba molecules, the sensor provides real-time insights into herbicide uptake, helping optimize pesticide use for more sustainable agricultural practices. Together, these sensors offer portable, fast, and efficient tools for tracking plant health, enabling better stress management and integrated pest control strategies for soybeans.

This research led to the development of novel wearable sensors that enable real-time, in-situ monitoring of reactive oxygen species, plant viruses, and pesticide uptake. The new knowledge gained from this work includes the discovery of how bioelectrodes, microneedles, and molecularly imprinted polymers can be combined to create highly sensitive and selective sensors capable of detecting chemical and biological changes within plants. This research also demonstrates the ability to monitor plant responses under biotic stress, virus infection, and herbicide absorption, providing insights into plant physiology beyond traditional measurements. The practical applications of this research include the ability for farmers and agricultural industries to use these wearable sensors for on-site, rapid, and cost-effective monitoring of plant health. The sensors can be applied directly in the field, reducing the need for complex, time-consuming, and expensive lab-based methods like liquid chromatography, polymerase chain reaction, or histological staining. By providing real-time data, the sensors empower more informed decision-making for pest management, stress monitoring, and herbicide application. This new knowledge and technology have the potential to significantly impact the agricultural industry and farmers by improving crop management, reducing chemical inputs, and promoting more sustainable farming practices.

This research will provide soybean farmers with a solution to early detection of soybean diseases in their fields. This project will build new measurement capacities needed to tackle challenges in state-wide and nation-wide crop disease prediction and prevention in the future.