Mid-infrared spectroscopy: A technology to authenticate A2 milk
Analyse and differentiate between A2 and A1 milk more quickly, with fewer staff required
The digestion of milk is not the same for everyone and can cause discomfort. Milk A2 can be a solution, since it does not release during digestion the peptide causing these problems, as does A1. The Remugant Research Group (G2R) from the Animal Science Unit of the Universitat Autònoma de Barcelona (UAB) has examined ways to analyze and differentiate A2 and A1 more quickly and without needing so much staff.
In recent years, A2 milk has gained prominence among consumers and producers. Its uniqueness lies in a natural variant of β-casein, a key milk protein. Unlike A1 milk, A2 does not release the peptide β-casomorphin-7 (BCM-7) during digestion, which has been associated with gastrointestinal discomfort in some people after consuming conventional milk.
Given the growing interest, many farms are choosing to produce A2 milk. Traditional genetic methods, such as PCR or chromatography, are accurate for identifying A2 milk but require time, reagents, and specialized personnel, making them impractical for large-scale application in the dairy sector. This creates the need for a fast, cost-effective, and reliable way to authenticate A2 milk samples.
In this context, the researchers evaluated the potential of mid-infrared spectroscopy (MIR), a technology widely used in the dairy industry to analyze milk composition. MIR technology is considered a environmentally friendly analytical technique because it does not use reagents, offers speed, and can be applied for large-scale sample analysis. Its potential to identify A2 samples is appealing, as it can be easily integrated into existing control systems.
In the study, they analyzed more than 2,200 milk samples from Holstein cows across six dairy farms in Catalonia, all of which have routine milk control systems. For each sample, the researchers gathered genetic data, milk quality information, and MIR spectra.
As a first step, they performed an exploratory analysis (PCA), which did not clearly distinguish between A1 and A2, as the differences between β-casein variants are very subtle and do not significantly affect the overall milk composition. However, the supervised model (PLS-DA) achieved very solid results. When grouping samples into two categories—A1 milk (A1A1 and A1A2) and A2 milk (A2A2) — the researchers obtained an accuracy of 88% in the test set. This result indicates that MIR can capture signals associated with the β-casein genotype and that, with appropriate models, it can be used as a fast and reliable method to authenticate A2 milk in routine controls.
The findings suggest that MIR technology could become a valuable tool to ensure the authenticity of A2 milk and strengthen transparency for producers and consumers.
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