Two researchers from the University of California have used machine learning to understand what a chemical smells like — a research breakthrough with potential applications in the food flavor and fragrance industries.
Anandasankar Ray, a professor from the molecular, cell and systems biology department at the University of California, said: "We now can use artificial intelligence to predict how any chemical is going to smell to humans."
"Chemicals that are toxic or harsh in, say, flavors, cosmetics, or household products can be replaced with natural, softer, and safer chemicals," the Science Daily website cited Ray as saying.
Humans sense odors when their odorant receptors (OR) activate in the nose. Each OR is activated by a unique set of chemicals.
"We tried to model human olfactory percepts using chemical informatics and machine learning. The power of machine learning is that it is able to evaluate a large number of chemical features and learn what makes a chemical smell like. The machine learning algorithm can eventually predict how a new chemical will smell and know if it smells like a lemon or a rose," Ray said.
Ray believes that this technique "allows to finding chemicals that have a novel combination of smells. The technology can help us discover new chemicals that could replace existing ones that are becoming rare, for example, or which are very expensive. It could also be used for other purposes such as making a mosquito repellent that works on mosquitoes but is pleasant smelling to humans."