The classification of sea cucumber (Apostichopus japonicus) according to region of origin using multi-element analysis and pattern recognition techniques

Element composition fingerprints were investigated for their potential to classify sea cucumber (Apostichopus japonicus) samples according to their geographical origin. Fifteen elements in 39 sea cucumber samples from three water environments (Bohai Sea, Yellow Sea, East China Sea) of China were quantitatively analyzed by inductively coupled plasma-mass spectrometry (ICP-MS). Pattern recognition techniques including principal component analysis (PCA), cluster analysis (CA, squared Euclidean distance between objects and between-groups linkage method as a clustering procedure) and linear discriminate analysis (LDA) were used for this purpose. Fifteen elements (Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Hg and Pb) in the sea cucumber samples of different regions showed significant differences (P < 0.05). Furthermore, sea cucumber samples from three water environments were accurately differentiated by PCA and CA. LDA gave an overall correct classification rate of 100.0% and cross-validation rate of 100.0%. These results demonstrate the usefulness of the multi-element analysis combined with pattern recognition techniques for authenticating of the geographical origin of sea cucumber in China.