Milk authentication and discrimination via metal content clustering – A case of comparing milk from Malaysia and selected countries of the world

• Discrimination of geographical origin of factory milk samples by analyzing 24 elements.
• A new green method using small amounts of reagent and sample was utilized.
• Multi element and multivariate chemometric methods of HCA and PCA was used.
• Malaysian milk samples were separated from other countries by particular elements.
• Our study points to the possibility of ascertaining authenticity and adulteration of milk.

Authenticity is an important issue nowadays as humans are concerned about the safety and quality of food they consume. In this regard, determining the geographical origin of milks using their elemental composition is of high importance. Therefore, we have studied the elemental composition of milk from various sources within a tropical region where there is no dramatic change in season. 24 essential and trace elements in 231 raw and factory cow milk samples were studied. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) reveal that Malaysian milks are well separated from milk samples collected from selected countries based on their elemental compositions. However, it is noted that only 11 elements (Mg, Na, Ca, Ba, Cu, Fe, Zn, K, Se, Mo and Mn) are detected out of the 24 analyzed. Based on the observations from PCA. Between the detected elements, Ca, Na, Fe, Zn, Mn, K, Ba and Mg are observed to be the discriminating factors for the overall separation of Malaysian milk samples from milks of selected regions of the world. Toxic elements are not detected in any of the milk samples studied. NIST/Milk SRM 1849a-Infant/Adult nutritional formula, USDA was used to verify the accuracy of the methodology. Our study shows clear geographical origin clustering which map to the authenticity of milk and serve as a parameter for quality control of milk.