TECHNICAL SESSION: Advanced detection and diagnosis of plant diseases
A Smartphone-Based Volatile Sensor Platform for Noninvasive Detection of Plant Pathogens
Qingshan Wei - North Carolina State University. Jean Ristaino- North Carolina State University, Taleb Ba Tis- North Carolina State University, Zheng Li- North Carolina State University, Amanda Saville- North Carolina State University, Jeana Hansel- North Carolina State University, Rajesh Paul- North Ca
Plant disease diagnosis conventionally relies on molecular assays that are complicated, time consuming, and constrained to centralized laboratories. Here, we developed a cost-effective, field-deployable, and smartphone-based volatile organic compound (VOC) sensor platform that allows noninvasive diagnosis of plant pathogen infections by monitoring characteristic leaf volatile emissions. This integrated system incorporates a paper-based chemical sensor array (test strip) to detect key plant volatiles at the ppm level within one minute of reaction. The colorimetric test strip was then digitally imaged and analyzed by a custom-developed smartphone reader device. Using this platform, we demonstrate the multiplexed detection and classification of 10 individual plant volatiles, including (E)-2-hexenal, one of the major VOC markers of late blight. In addition, diagnosis of tomato late blight (P. infestans) as early as 2 days after inoculation was demonstrated with this handheld device, which is much earlier than the manifestation of visible symptoms. Finally, we demonstrate a detection accuracy of 95% for P. infestans diagnosis in both lab-inoculated and field-collected infected tomato leaves in blind pilot tests.