Bio-sensor machine that can detect rancid or fraudulent olive oil

Home > News & Articles > Olive Oil Business News > Bio-sensor machine that can detect rancid or fraudulent olive oil

Extra-virgin olive oil is flavorful and healthy, which could explain why sales of high-quality olive oil have tripled in America in the last two decades. But when you buy a bottle of extra-virgin olive oil, can you be sure the oil inside is, indeed, “extra virgin”?

No. In fact, as much as two-thirds of the extra-virgin olive oil sold in the United States is actually much lower-grade oil, lacking the antioxidants, omega-3 fatty acids, and flavor found in true extra-virgin olive oil. What’s a consumer to do?

Don’t despair. A team of UC Davis students has built a biosensor designed to quickly and easily evaluate the chemical profile of oil, providing producers, distributors, retailers and ultimately consumers with an effective, inexpensive way to ensure olive oil quality.

The biosensor is UC Davis’ entry into an international science competition called iGEM (International Genetically Engineered Machines), which invites top students from around the world to spend their summer engineering solutions to real-world concerns.

The UC Davis team of undergraduate students — Lucas Murray, Brian Tamsut, James Lucas, Sarah Ritz, Aaron Cohen and Simon Staley — will present their biosensor at the iGEM convention this weekend, today through Nov. 3, in Boston.

“It’s a lot of work, but it’s rewarding,” said Tamsut, a sophomore majoring in biotechnology, surrounded by his teammates in the UC Davis Genome Center where their palm-sized biosensor was taking shape. “It’s especially rewarding knowing our project is practical and will solve a real, tangible problem.”

Bio-sensor machine that can detect rancid or fraudulent olive oil, 3.4 out of 10 based on 21 ratings

Post Views

VN:F [1.9.22_1171]
Rating: 3.4/10 (21 votes cast)
VN:F [1.9.22_1171]
Rating: 0 (from 4 votes)

Leave a Reply

Your email address will not be published. Required fields are marked *