Bayesian fusion model enhanced codfish classification using near infrared and Raman spectrum

Yi Xu, Anastasios Koidis, Xingguo Tian, Sai Xu, Xiaoyan Xu, Xiaoqun Wei, Aimin Jiang*, Hongtao Lei

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
53 Downloads (Pure)


In this study, a Bayesian-based decision fusion technique was developed for the first time to quickly and non-destructively identify codfish using near infrared (NIRS) and Raman spectroscopy (RS). NIRS and RS spectra from 320 codfish samples were collected, and separate partial least squares discriminant analysis (PLS-DA) models were developed to establish the relationship between the raw data and cod identity for each spectral technique. Three decision fusion methods: decision fusion, data layer or feature layer, were tested and compared. The decision fusion model based on the Bayesian algorithm (NIRS-RS-B) was developed on the optimal discrimination features of NIRS and RS data (NIRS-RS) extracted by the PLS-DA method whereas the other fusion models followed conventional, non-Bayesian approaches. The Bayesian model showed enhanced classification metrics (92% sensitivity, 98% specificity, 98% accuracy) that were significantly superior to those demonstrated by any of other two spectroscopic methods (NIRS, RS) and the two data fusion methods (data layer fused, NIRS-RS-D, or feature layer fused, NIRS-RS-F). This novel proposed approach can provide an alternative classification for codfish and potentially other food speciation cases.

Original languageEnglish
Article number4100
Issue number24
Publication statusPublished - 19 Dec 2022

Bibliographical note

Funding Information:
This research was funded by [the National Scientific Foundation of China] grant number [31871883], [HeYuan Planned Program in Science and Technology] grant number [2019041], [Generic Technique Innovation Team Construction of Modern Agriculture of Guangdong Province] grant number [2022KJ130, 2023KJ130], [National Key Research and Development Program of Thirteenth Five-Year Plan] grant number [2017YFC1601700].

Publisher Copyright:
© 2022 by the authors.


  • authenticity
  • Bayes information fusion
  • codfish
  • near infrared spectrum
  • Raman spectrum

ASJC Scopus subject areas

  • Food Science
  • Microbiology
  • Health(social science)
  • Health Professions (miscellaneous)
  • Plant Science


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