Stable isotope ratio analysis for the authentication of sea urchin (Mesocentrotus nudus) from different culture areas in the North Yellow Sea, China

Reliable methods of tracing the geographical origin of sea urchin are urgently needed for food safety and con-sumer health. To the best of our knowledge, the present study was the first attempt to trace the geographic origins of sea urchin by using stable isotope techniques. The 613C, 615N and 618O values from the gonad and spine of sea urchins collected from five locations were analyzed. From the gonad samples, the 613C values ranged from-22.07%o to-18.37%o, the 615N values ranged from 6.59%o to 9.99%o, and the 618O values ranged from 17.64%o to 27.19%o. From the spine samples, the 613C values ranged from-5.43%o to-3.57%o, the 615N values ranged from 7.95%o to 13.66%o, and the 618O values ranged from 33.99%o to 40.15%o. The 613C and 615N values from the gonads differed significantly among samples from different geographic origins, but the 618O values did not differ. The 615N and 618O values from the spines differed significantly among samples from different geographic origins, but the 613C values did not differ. Both quadratic discriminant analysis (QDA) and the k-nearest neighbor (KNN) methods yielded low recognition of the 613C, 615N, and 618O values from the gonad samples. However, higher accuracy was obtained using the stable isotope values from the spine samples combined with QDA or KNN methods. Moreover, the KNN methods gave more satisfactory accuracy, the initial, cross-validated, and pre-dictive classification rates were 97.1%, 97.1%, and 93.3%, respectively. The C, N, and O stable isotope analysis of spine samples may be used to verify the geographic origin of sea urchins.

Automated summary

Stable isotope techniques are reliable methods for tracing the geographical origin of sea urchins. Analysis of stable isotope values in the gonad and spine of sea urchins can distinguish samples from different geographic origins. Combining stable isotope values from spine samples with QDA or KNN methods yields higher accuracy.