4.6 Article

Evaluation of multivariate data analysis for marine mussels Mytilus edulis authentication in China: Based on stable isotope ratio and compositions of C, N, O and H

期刊

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jfca.2022.104627

关键词

Mussel; Stable isotope ratio; Elemental composition; Multivariate analysis; Geographical origin

资金

  1. Key Projects of Intergovernmental International Cooperation in Science and Technology Innovation [2019YFE0103800]
  2. National Key Research and Develop-ment Program of China [2017YFC1600702]
  3. Central Public-interest Scientific Institution Basal Research Fund, YSFRI
  4. CAFS [20603022022017]
  5. Central Public-interest Scientific Institution Basal Research Fund, CAFS [2020TD71]
  6. Key Laboratory of Testing and Evaluation for Aquatic Product Safety and Quality, Ministry of Agriculture and Rural Affairs [ [SCKF-2020004]
  7. China Agriculture Research System of MOF and MARA

向作者/读者索取更多资源

Geographical traceability of marine bivalves is crucial for ensuring food quality and protecting the interests of consumers and importers. This study investigated the use of stable isotope ratio and element analysis combined with multivariate data analysis for tracing the origin of mussels. The results showed that these techniques can provide valuable information for identifying the geographical origin of mussels.
Geographical traceability of marine bivalves was crucial to avoid food fraud, to guarantee food quality and to protect the interests of both consumers and importers. In order to evaluate the availability of using stable isotope ratio and content of carbon (C), nitrogen (N), oxygen (O), and hydrogen (H) combined with multivariate analysis for the origin traceability of mussels, 120 samples collected from four major production provinces in China were analyzed. Principal component analysis (PCA) was used for data exploratory analysis, and linear discriminant analysis (LDA) was used to evaluate their performance in terms of classification or predictive ability. Results showed that there was a significant difference (p < 0.05) in the eight variables in mussels from different origins, which proved that these signals were useful for identifying the origins of mussels. Based on the PCA, there was no clear distinction among the mussels from different regions. The LDA gave an overall accuracy rate of 92.8%, cross-validated accuracy rate of 86.7% and predictive accuracy rate of 92.3%. Present findings suggested that the stable isotope ratio and compositions analysis of C, N, O, and H could be potentially applied to the geographical origin traceability of China mussels assisted by multivariate data analysis.

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