Fatty acid fingerprint enables linking forage and milk composition in assessing the geographical origin of Chinese Holstein cow milk.

This study aimed to assess the effectiveness of fatty acid (FA) fingerprinting in distinguishing the geographical origin of milk and linking milk FA profiles with those of forage. A total of 66 bulk-tank milk samples and 66 corresponding forage samples were collected over 3 consecutive days from 22 dairy farms across western, eastern, and southern China. The FA compositions of the samples were analyzed using GC-MS, identifying 81 individual FA. Using orthogonal partial least squares discriminant analysis and significance analysis, we identified significant regional differences in the 35 milk FA. Recursive feature elimination was used to identify 10 potential FA biomarkers for the geographical origin of milk, including C18:2 cis-9,trans-12, C18:1 trans-6, PUFA, C18:1 cis-12, C20:3 cis-8,cis-11,cis-14, C14:0, MUFA, C13:0 iso, C16:1 cis-9, and C13:0. A support vector machine model based on these 10 biomarkers classified the milk samples by region with an accuracy >95%. Canonical and Spearman's correlation analyses indicated relationships between milk and forage FA profiles. Specifically, milk FA such as C13:0 iso, C13:0, C14:0, and C16:1 cis-9 showed significant positive correlations with most short-chain FA, odd-chain SFA, and branched-chain SFA in the forage and negative correlations with long-chain FA and FA greater than C16. Conversely, milk FA C18:2 cis-9,trans-12, C18:1 trans-6, and C18:1 cis-12 exhibited the opposite trend. The correlation between UFA in milk and forage was more complex, showing both positive and negative relationships. These findings demonstrate that FA fingerprinting is a reliable method for determining the geographical origin of milk. The observed variations in milk FA are primarily influenced by forage FA, providing valuable insights for improving milk quality through better forage management.