An AI analysis and a chemical sensor determine drinks' dilution, freshness and type
The search for an automated way to "taste-test" products at mass-production speed and scale has stumped the food and beverage industry for decades. But in a new study, researchers used machine learning to overcome the limitations of a promising type of chemical sensor, meaning that a robotic tongue may soon assess your milk or merlot before you do. When ions in a liquid—say, a delicious drink—touch the conductive sheet of an ion-sensitive field-effect transistor (ISFET), the electric current that flows through changes based on the liquid's exact composition and the voltage applied. This lets scientists use ISFETs to convert chemical changes into electrical signals. The chemical makeup of any drink, and thus its taste, is influenced by contamination and freshness—which ISFETs can discern. "The food industry has a lot of problems in terms of figuring out whether food is adulterated or has something toxic in it," says Pennsylvania State University engineer Saptarshi Das. The first ISFETs were demonstrated more than 50 years ago, but the sensors aren't used much commercially. The…