Skoltech’s research will help restaurants control and automate the cooking processes in their kitchens. In the future, such technologies may become part of the home “smart” ovens. An article detailing this study’s results, supported by a grant from the Russian Science Foundation, has been published in the journal Food Chemistry.
How do you know if, for example, a chicken is ready to serve? At home, you can watch, smell the food to make sure it is perfectly cooked. However, if you are a chef in a restaurant or a huge industrial kitchen, relying on your eyes and nose to provide consistent, standardized results are difficult. This is why the restaurant industry is actively looking for cheap, reliable, and sensitive tools to replace subjective human judgment to make quality control automated.
Professor Albert Nasibulin from Skoltech and Aalto University, a senior researcher at Skoltech Fyodor Fedorov, and their colleagues contributed to solving the problem. They created an “electronic nose” – a set of sensors that detect specific scent components to “sniff” the chicken is cooked. The researchers also created a computer vision algorithm so that the system can visually examine the dish. Electronic noses are simpler and cheaper to operate than a gas chromatograph or mass spectrometer. They have even been shown to detect different types of cheeses or identify rotten apples or bananas from a batch of fruit. On the other hand, computer vision is capable of recognizing visual patterns.
Scientists have decided to combine the two methods for precise and non-contact control of the degree of food readiness. They chose chicken meat, popular worldwide, and grilled a lot of chicken breast to “train” the system to evaluate and predict how well it was cooked.
The researchers built their own “electronic nose” with eight sensors and placed it in a ventilation system. The scientists also photographed the grilled chicken and passed the information to the algorithm.
The system was able to identify undercooked, well-cooked, and overcooked chicken reasonably well, so it could potentially automate quality control in the kitchen. The study authors note that to use their technique on other parts of the chicken, say, on the legs or wings, or for another cooking method, the electronic “nose” and “eyes” will have to be retrained with new data.