Evaluation of elemental analysis assisted by chemometrics for authenticating production methods and geographical origins of salmonids

Abstract Advanced techniques were required to determine geographical origins and production methods of aquatic food due to frequent fraudulent misdescription of food content on product labels in the market. In this study, the elemental profile of 96 salmonids samples were detected by inductively coupled plasma atomic emission spectrometry (ICP-AES) and used to identify production methods and geographical origins of salmonids. Moreover, effects of fish size and harvest time on the elemental compositions in salmonids were investigated. A total of 14 elements (Al, Ca, Co, Cr, Cu, Fe, Ga, K, Mg, Mn, Na, Ni, Sr, and Zn) were determined in salmonids. Of these, elements Fe, K, Na, Mn, and Zn, were varied in fish collected in different harvest times, and elements Al, Fe, Ga, Mn, and Zn were related to fish sizes, six elements (Ga, K, Mg, Na, Ni, and Sr) were significantly different between freshwater-cultured and seawater-cultured salmonids, 13 elements (Al, Ca, Co, Cr, Fe, Ga, K, Mg, Mn, Na, Ni, Sr, and Zn) were significantly different among different areas. Three elements (K, Mg, and Na) and 12 elements (Ca, Co, Cr, Fe, Ga, K, Mg, Mn, Na, Ni, Sr, and Zn) were selected by SDA for identifying production methods and geographical origins of salmonids, respectively. Canonical discriminant analysis (CDA) visualized the difference in salmonids cultured by different production methods or from different areas. Multivariate statistics, linear discrimination analysis (LDA), k-nearest neighbor (KNN), and random forest (RF) demonstrated the validity of the elemental profile in distinguishing production methods and geographical origins of salmonids. The results showed that production methods of salmonids were distinguished by LDA, KNN, and RF with an overall accuracy of >94.74%. Among these, the highest accuracy was achieved by KNN with an accuracy of 100%. For authenticating geographical origins of salmonids, the accuracy of KNN (> 94.74%) was highest. The element profile was effective to distinguish production methods and geographical origins of salmonids, which were less affected by harvest time and fish size.