Evaluation of Sensor Technology for Real-Time Detection of Cyst Nematode Infected Soybean Plants
Ralph A. Dean
Project runs from 12/01/2018 to 11/05/2019
Soybean cyst nematode (SCN, Heterodera glycines) is a major pest in all soybean-growing areas, particularly in sandy soils. Here, we propose a series of growth chamber experiments to demonstrate the potential of sensor technologies based on the capacitive micromachined ultrasonic transducer (CMUT) developed by our research team at NC State for detecting volatiles associated with SCN. In addition, we plan to identify and characterize discriminating VOCs from SCN infected soybeans and examine their detection by the sensor arrays.