Your smartphone can recognize faces, and your car can detect lane markers; now, researchers have taught machines to taste. A team at Penn State University has developed an “electronic tongue” that combines atom-thin sensors with artificial intelligence to detect food fraud, spoilage, and contamination within minutes.
This research, published in Nature, combines two cutting-edge technologies. The team used sensors made from graphene, which is an incredibly thin form of carbon that’s just one atom thick and conducts electricity exceptionally well. They paired these sensors with artificial intelligence that can learn patterns. Together, this creates a system that’s remarkably good at detecting tiny differences between similar liquids.
The system mimics how humans taste and process flavors. Just as our tongues have taste receptors that send signals to our brain’s gustatory cortex — the region responsible for interpreting tastes beyond the basic categories of sweet, sour, bitter, salty, and savory — this electronic tongue uses sensors that send electrical signals to an artificial neural network that analyzes the data.
Traditional food testing requires expensive laboratory equipment and time-consuming analysis. However, this new system can detect various substances and assess their quality, authenticity, and freshness in about a minute. The sensors work like electronic taste buds, producing electrical signals that change when exposed to different chemical solutions.
What makes this system particularly innovative is its ability to learn and improve on human expertise. When researchers allowed the artificial intelligence to define its own parameters for analysis rather than using human-selected metrics, accuracy improved from 80% to more than 95%. Using a technique called Shapley additive explanations, the team could even peek into the AI’s decision-making process, offering a rare glimpse into how artificial intelligence reaches its conclusions.
“We found that the network looked at more subtle characteristics in the data—things we, as humans, struggle to define properly,” says corresponding author Saptarshi Das, in a statement. “In terms of the milk, the neural network can determine the varying water content of the milk and, in that context, determine if any indicators of degradation are meaningful enough to be considered a food safety issue.”
The system proved remarkably effective at detecting watered-down milk at concentrations as low as 5%, distinguishing between different types of coffee blends, and tracking fruit juice freshness over several days. In one impressive demonstration, it differentiated between similar products like regular Coke, Diet Coke, Pepsi, caffeine-free Coke, and zero-sugar Coke with over 97% accuracy.
What’s amazing is this system doesn’t need perfectly identical sensors to work well. The AI is smart enough to adjust for small differences between sensors, much like our brains can adjust to slight variations in taste buds. This makes the technology much cheaper to produce in large quantities since manufacturers don’t need to worry about making every sensor exactly the same.
The system is incredibly sensitive at detecting harmful chemicals in food and water. To put this in perspective, it can find a potentially dangerous compound called perfluorohexanoic acid (a chemical used in manufacturing that can contaminate food and water) at levels equivalent to detecting a single drop in an Olympic-sized swimming pool—that’s 2.5 parts per billion. This ultra-sensitive detection ability could help catch contaminated food and water before it reaches consumers.
These results extend far beyond food testing, though. According to the researchers, its applications could potentially include medical diagnostics, with its capabilities limited only by the data used to train it.
This “electronic tongue” represents a significant step toward making sophisticated chemical testing more accessible and reliable. By embracing imperfection in the sensors while leveraging artificial intelligence, the researchers have created a system that could fundamentally change how we verify food safety and authenticity.
Source : https://studyfinds.org/electronic-tongue-taste-spoiled-milk/