- Every year, millions of pounds of fresh fruits, vegetables and animal products enter through US ports of entry. Perhaps harmless at first glance, these food products could harbor hidden threats that seriously endanger our agriculture and national economy.
WASHINGTON, USA – Plant diseases and pests brought into the country by travelers and importers reduce the annual global yield of major crops (wheat, rice, corn, potatoes, soy) by more than 20 percent. If border inspections take long, this could cause financial losses as agricultural products are perishable. That is why the Science and Technology Directorate’s (S&T) Food, Agriculture, and Veterinary Defense project is working to slow this trend and help officers perform inspections, intercept and identify thousands of plant pathogens as quickly as possible.
“Maintaining the integrity and continuity of food and agricultural supply is imperative,” said S&T program manager Dr Rory Carolan. “Any disruption to these critical structures could be catastrophic with huge economic impacts and health consequences, which would be devasting as this industry contributes more than $1.1 trillion to the US economy per year and is highly interconnected on a global scale.”
Traditionally, the Directorate’s primary focus has been on high-priority animal diseases via the Plum Island Animal Disease Center, where S&T and US Department of Agriculture researchers work side by side.
“Now, crop and plant security are a new frontier for S&T—from crop diseases and pests to aquaculture, forestry, and more,” said Dr Carolan, who leads the plant disease detection initiative. “We invest in detecting diseases with the highest risk to the US agriculture.”
Current methods, relying on manual inspection of samples from agricultural shipments, may be inadequate to detect emerging diseases because most detection methods focus on visible pests. However, diseases can hide inside plant products or shipping materials.
In the first phase of the plant disease detection initiative, S&T collaborated with the Department of Energy’s Oak Ridge National Laboratory (ORNL) on an extensive technology assessment to find suitable systems for further development and future deployment. S&T and ORNL released a technology assessment report with their findings last year.
The assessed technologies included X-ray imaging and simple immunological tests for pathogens, emerging technologies like advanced imaging artificial intelligence (AI) and machine learning (ML) methods for sorting fruits and vegetables and recognizing anomalies at high speeds, as well as instruments detecting biogenic volatile organic compounds (BVOCs). These technologies were compared to trained agriculture inspection dogs’ olfactory abilities that can successfully detect many concealed products and some plant pests and pathogens.
Ultimately, S&T chose to focus on developing cutting edge BVOC detecting technologies because they are less invasive and quicker. BVOCs are biologically emitted molecules that can be scents, like the smell of Christmas trees. The scents that BVOC instruments can detect are fragrant molecules emitted either by the plant or the pest.
“Pathogens release characteristic waste products or metabolites, but at the same time the infected plants’ chemistry may change and release different products,” explained Dr David Graham, biosecurity programs lead at ORNL. “Together, the pathogen and the plant are emitting different scents, and we may be able to detect them.”
The S&T-chosen BVOC technologies work by first sampling the air via a small pump and then detecting fragrant compounds via two different methods—by mass spectrometry, a very sensitive way of assessing compounds based on the volatile molecule’s mass, and by small electronic sensors that bind compounds on their surface. S&T plans to address any false positives that may happen due to the bustling, dusty, hot ports of entry where rail cars, tractor-trailers, cargo ships arrive from abroad. AI/ML could help diminish the noise and thus make the BVOC technology highly sensitive and precise in such field environments. Dr Carolan and his team plan to train the AI/ML software and build a library of possible characteristic fragrant molecules.
The technology development phase of the plant disease detection initiative is currently underway. S&T and ORNL are conducting laboratory tests to see how several BVOC detectors perform under simulated field-like conditions. “For example, we’d be blowing diesel exhaust at them,” Dr Carolan said.
After that, ideally, the technologies would be tested under field conditions, while cargo vehicles are offloading or driving by x-rays, or as cars line up to come through the border, or similar conditions.
“This could be a very efficient way to minimally interfere with trade and the flow of commodities or the movement of people,” said Dr Carolan, who hopes to have a prospective product within three years. “Tools provided by S&T allow decision makers and responders to be informed and utilize countermeasures to help prevent, protect, remediate, and increase DHS capabilities.”
In the future, S&T may further develop the BVOC technology to detect a wider range of threats from fresh fruits and vegetables in passengers’ baggage to woodboring pests, fentanyl and even explosives.
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