AI taught to evaluate the freshness of beef

Although beef is one of the most popular foods in the world, it can be dangerous.

Improper storage and eatingStale tenderloin leads to serious health problems. Unfortunately, there are many drawbacks to the available methods for checking freshness of beef. For example, chemical analysis or assessment of the microbial population is too time-consuming and requires professional skills. On the other hand, non-beef-destructive methods based on near infrared spectroscopy require expensive and sophisticated equipment. Could artificial intelligence be the key to a more cost-effective way to measure the freshness of beef?

In South Korea, a group of scientists has developed a newa strategy that combines deep learning with diffuse reflectance spectroscopy (DRS), a relatively inexpensive optical technique. Unlike other types of spectroscopy, DRS does not require complex calibration. Instead, it can be used to quantify a fraction of the molecular composition of a sample using only an affordable and easily customizable spectrometer. Details of the new method are published Food Chemistry.

To determine the freshness of beef samples,the scientists used DRS measurements to estimate the proportion of different forms of myoglobin in meat. Myoglobin and its derivatives are proteins that are mainly responsible for the color of meat and its changes during decomposition. However, manually converting DRS measurements to myoglobin concentration for final determination of sample freshness is not a very accurate strategy, and this is where deep learning comes into play.

Convolutional Neural Networks (CNNs) are widelyAI algorithms used that learn from a pre-classified dataset - a training dataset and find hidden patterns in the data to classify new inputs. To educate CNN, the researchers collected data on 78 beef samples in the spoilage process by regularly measuring their pH (acidity) along with DRS profiles. They combined the findings with estimates of myoglobin. As a result, the deep learning algorithm correctly classifies the freshness of beef samples in seconds in about 92% of cases.

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Diffuse reflectance spectroscopy isa kind of absorption spectroscopy. This is sometimes called remission spectroscopy. Remission is the reflection or backscattering of light by a material, and transmission is the passage of light through a material.