Electronic nose technology aims to transform food safety

The presence of a strong, unpleasant odor in food is an indication that bacteria has contaminated the food past the point of human consumption. However, oftentimes pathogens such as salmonella and E. coli are difficult to detect.

Taeyeong Choi, assistant professor of information technology in Kennesaw State University's College of Computing and Software Engineering, is working on developing an electronic nose (e-nose) to detect abnormalities from their version of the sniff test. 

His proposed method would not only eliminate the need to "waste" food to discern whether it is safe but also revolutionize food safety by relying on what the e-nose can detect rather than only the appearance of the food. 

Food safety is a really important issue for the public, and I realized that millions of people are affected by foodborne illness each year."

Taeyeong Choi, assistant professor of information technology, Kennesaw State University's College of Computing and Software Engineering

Foodborne illnesses are responsible for about 128,000 hospitalizations and 3,000 deaths each year in the United States, amounting to approximately one in six Americans dealing with food poisoning every year, according to the Centers for Disease Control and Prevention.

The traditional methods for detecting contamination are accurate, but they require time, resources, and are considered destructive. 

To analyze the safety of a food, a sample must be taken from it, leading to potential food waste. Current modernized strategies for food safety tests involve image analysis based on artificial intelligence, which offers a faster alternative, but it is only able to see what a human eye is able to see. 

Choi's NSF-funded project was born out of his desire to contribute to society. As an AI and robotics expert, Choi felt he was up to the challenge of innovating food safety. 

The e-nose works by analyzing volatile organic compounds (VOCs) or groups of chemicals that can evaporate with ease and release potentially harmful gases - an example of this is smog. 

Utilizing AI models trained from thousands of samples of VOCs, the e-nose will be able to not only detect contaminants but also differentiate between different foods around it. 

"Currently, we are mainly interested in pathogens like salmonella and E. coli, since they're the most common and impact a lot of people," Choi said. "Over time, and through continued discussions with my colleagues who have expertise in food safety, we will continue to increase the number of pathogens we are able to detect."

The e-nose will not only revolutionize food safety using olfactory sensors but also has a multitude of potential applications in healthcare, robotics, and security. 

In the future, the e-nose could be used to detect multiple diseases from a single breath sample from the patient.