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Data fusion and multivariate analysis for food authenticity analysis

Author

Listed:
  • Yunhe Hong

    (Queen’s University Belfast)

  • Nicholas Birse

    (Queen’s University Belfast)

  • Brian Quinn

    (Queen’s University Belfast)

  • Yicong Li

    (Queen’s University Belfast)

  • Wenyang Jia

    (Queen’s University Belfast)

  • Philip McCarron

    (Queen’s University Belfast)

  • Di Wu

    (Queen’s University Belfast)

  • Gonçalo Rosas Silva

    (Queen’s University Belfast)

  • Lynn Vanhaecke

    (Queen’s University Belfast
    Ghent University)

  • Saskia Ruth

    (Wageningen University and Research
    University College Dublin)

  • Christopher T. Elliott

    (Queen’s University Belfast
    Thammasat University, 99 Mhu 18)

Abstract

A mid-level data fusion coupled with multivariate analysis approach is applied to dual-platform mass spectrometry data sets using Rapid Evaporative Ionization Mass Spectrometry and Inductively Coupled Plasma Mass Spectrometry to determine the correct classification of salmon origin and production methods. Salmon (n = 522) from five different regions and two production methods are used in the study. The method achieves a cross-validation classification accuracy of 100% and all test samples (n = 17) have their origins correctly determined, which is not possible with single-platform methods. Eighteen robust lipid markers and nine elemental markers are found, which provide robust evidence of the provenance of the salmon. Thus, we demonstrate that our mid-level data fusion - multivariate analysis strategy greatly improves the ability to correctly identify the geographical origin and production method of salmon, and this innovative approach can be applied to many other food authenticity applications.

Suggested Citation

  • Yunhe Hong & Nicholas Birse & Brian Quinn & Yicong Li & Wenyang Jia & Philip McCarron & Di Wu & Gonçalo Rosas Silva & Lynn Vanhaecke & Saskia Ruth & Christopher T. Elliott, 2023. "Data fusion and multivariate analysis for food authenticity analysis," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38382-z
    DOI: 10.1038/s41467-023-38382-z
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    References listed on IDEAS

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