New testing technology aims to identify plant pathogens faster

Image: zoyas2222/Shutterstock

25 March 2025 | Muriel Cozier

The need to manage the risks posed by pathogens and pests resulting from the global agricultural trade is leading the US Department of Homeland Security’s (DoH) Science and Technology Directorate to develop technologies that can analyse biogenic volatile organic compounds (BVOCs).

The US government calculates that plant diseases and pests introduced to the US by travellers and importers are impacting annual global yields of crops such as wheat, rice, corn potatoes and soy, by more than 20%. Lengthy border inspections can lead to financial losses and current methods, relying on manual inspection of samples from agricultural shipments, and are likely to be inadequate in detecting emerging diseases, as they only focus on the visible signs of problems.  

In the first phase of the plant disease detection initiative, the DoH's Science and Technology Directorate worked with the Department of Energy’s Oak Ridge National Laboratory (ORNL) on a technology assessment to find suitable systems for further development and future deployment. They assessed technologies including X-ray imaging and simple immunological tests for pathogens, emerging technologies like advanced imaging artificial intelligence (AI) and machine learning methods for sorting fruits and vegetables and recognizing anomalies at high speeds, as well as instruments detecting BVOCs. They have chosen to explore BVOC detecting technologies further because they are less invasive and quicker. 

BOVC instrumentation can detect fragrant molecules emitted by the plant or pest. “Pathogens release characteristics waste products or metabolites, but at the same time the infected plants’ chemistry may change and release different products. Together the pathogen and the plant are emitting different scents, and we may be able to detect them,” explained David Graham, biosecurity programmes lead at ORNL. 

After sampling the air via a small pump, compounds are analysed by mass spectrometry or by electronic sensors that bind compounds in their surface. AI and machine learning could go some way towards dimishing 'noise' in the data and allowing the BVOC technology to be highly precise.

Homeland Security’s Science and Technology Directorate says that their work is currently in the technology development phase with laboratory tests being carried out to see how several BVOC detectors perform under simulated conditions found in port environments. This testing will then move to the field. It is hoped that a fully operational product will be available within three years, and the  BVOC technology could in future be developed to detect a wider range of threats from fresh fruits and vegetables in passenger luggage, through to woodboring insects, drugs and explosives. 

Further reading

Why climate change is increasing our risk of exposure to mycotoxins
This Google X spinout wants to make plants programmable - with AI
A novel platform allows rapid detection of pathogens on food

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