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.

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.