GAINESVILLE, Fla. — Fresh produce can look a lot different on your table than it did when first harvested from the field.
What was once fresh and vibrant looks wilted and moldy. Tie Liu feels your pain.
“Everybody has this problem: Which of these vegetables or fruits should I use first? Guess wrong, and you end up throwing out the food,” said Liu, a postharvest researcher and assistant professor in the UF/IFAS horticultural sciences department.
Consumers are not the only ones encountering this problem.
“If you are transporting food from the farm to retailer, knowing the freshness of the produce can help you better plan ahead and maximize the freshness of the product,” Liu said. “But right now, there is no quick, easy way to know how long, for example, a head of broccoli has until it’s no longer fresh.”
The process of senescence occurs when a series of chemical changes begin inside a vegetable or fruit after it’s been harvested.
That broccoli might look fine to the human eye, but the clock is ticking. This leads Liu to investigate whether it is possible to develop a hand-held or wearable device that can look beyond the visual spectrum to determine freshness.
“If successful, this device will tell you how fresh produce is and help food transporters and packing houses better time shipments, increasing efficiency and providing fresher food for the consumer. Think of it like facial recognition, but instead of identifying faces, the device would identify freshness level” Liu said.
Funded by a nearly half-million dollar, four-year grant from the USDA National Institute of Food and Agriculture’s (NIFA) Agriculture and Food Research Initiative (AFRI), the project, called FreshID, also tackles a global problem: food waste and loss.
“About 40% of food produced is wasted. A significant proportion of that waste and loss occurs between the time the produce is harvested and when it gets to the consumer. The FreshID project aims to help make sure that food gets to the consumer at the right time,” Liu said.
The project, led by Liu , includes researchers in the UF Herbert Wertheim College of Engineering. The team will combine their expertise in plant molecular biology, hyperspectral imaging, computed tomography (CT) imaging and artificial intelligence (AI).
“Ultimately, we want to understand how physiological, biochemical and molecular changes going on inside produce can be detected using X-ray CT imaging and a hyperspectral camera, which is a camera that can see the whole spectrum of light, not just the blue, green and red pixels of a normal camera. We would then use that data to train a computer, using machine learning, to recognize the visual signals that indicate freshness levels,” Liu said.