 This paper proposes a novel approach for accurately identifying the geographic origin and production method of salmon based on data collected by dual platform mass spectrometry. This approach combines mid-level data fusion techniques with multivariate analysis to achieve a high level of accuracy in classifying salmon samples. The results show that the proposed method outperforms existing single platform approaches, providing reliable identification of salmon origin and production method. Furthermore, 18 robust lipid markers and 9 elemental markers were identified, providing strong evidence of the provenance of the salmon. This study demonstrates the potential of this approach for use in food authenticity applications. This article was authored by Ying He Hong, Nicholas Burse, Brian Quinn and others.