Geographical traceability of sea cucumbers in China via chemometric analysis of stable isotopes and multi-elements

Abstract

Geographical traceability is critical in protection the local characteristic product such as sea cucumbers, which is one of the highly valued seafood in China. Thus, it is urgent to develop some advanced techniques to clearly identify the geographical origins of sea cucumbers. In this work, the potential of data fusion techniques used for the traceability of sea cucumbers in China was evaluated by linear discriminant analysis (LDA). To further improve the classification accuracy for sea cucumbers origins, the partial least discriminant analysis (PLS-DA) and soft independent modeling of class analogies (SIMCA) were also explored. Results showed that the stable isotope ratios and composition of C, N, O and H and mineral elements were significantly different (p < 0.05) among sea cucumbers from five regions, which indicated the regional orientation abilities of these variables. The principal component analysis (PCA) did not present a good separation of the sea cucumbers from five regions. High recognition (98.7 %) and satisfactory predictive ability (96.1 %) were achieved with the LDA using data fusion techniques. For the PLS-DA, the overall accuracies (97.1 %) were achieved. The SIMCA model provides 100 % accuracy in identification of sea cucumber samples. Therefore, data fusion techniques assisted by chemometrics may provide more useful strategies for geographical origins identification of sea cucumbers in China.