In this proof-of-concept study (purchase required) the authors used direct-sampling ambient mass spectrometry (REIMS, sometimes called the “ion knife”) to build a classification model for different cuts of beef. They analysed untargeted lipid profile data from a reference set of 125 authenticated samples purchased directly from an abattoir (25 each of ribeye, sirloin, brisket, shank and foreshank) from 12-month old bulls of the Pirenaica breed. They used machine learning to select discriminatory features (11 fatty acids and 44 phospholipids). They report good discrimination between different cuts of meat using the model.
Photo by amirali mirhashemian on Unsplash
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