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      Current progress in the authentication of fishery and aquatic products using multi‐element and stable isotope analyses combined with chemometrics

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          Abstract

          Fraud occurs frequently in the fishery and aquatic product markets. Therefore, the authentication of fishery and aquatic products has become a crucial issue. Recently, elemental and stable isotope analyses have become popular for aquatic food authentication. In this review, relevant literature was collected to highlight the current progress in the authentication of fishery and aquatic products using multi‐element and stable isotope analyses combined with chemometrics. Both technologies provide valuable insight regarding geographic origin, culture method, and species identification of fishery and aquatic products. Their classification rate varied from 60% to 100% in most studies. The formation of both elemental and stable isotope profiles of fishery and aquatic products is complex and affected by many factors, including diet, biological differences, and culture environment. The classification rate of these methods may be increased by combining multiple technologies, selecting the correct elements and stable isotopes for specific purposes, selecting and verifying proper discrimination methods, and increasing sample sizes. This review provides valuable information to build reliable and stable tracing methods for fishery and aquatic products.

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          Most cited references134

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          OXYGEN AND HYDROGEN ISOTOPES IN THE HYDROLOGIC CYCLE

          J R Gat (1996)
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            Mechanism of carbon isotope fractionation associated with lipid synthesis.

            The low carbon-13/carbon-12 ratio of lipids is shown to result from isotopic fractionation during the oxidation of pyruvate to acetyl coenzyme A. In vitro analysis of the kinetic isotope effects of this reaction indicates that there will be a large, temperature-dependent difference in the carbon-13/carbon-12 ratio between the methyl and carbonyl carbon atoms of acetyl coenzyme A and between those carbon atoms of lipid components which derive from them.
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              Getting to the fat of the matter: models, methods and assumptions for dealing with lipids in stable isotope analyses.

              Within an organism, lipids are depleted in (13)C relative to proteins and carbohydrates (more negative delta(13)C), and variation in lipid content among organisms or among tissue types has the potential to introduce considerable bias into stable isotope analyses that use delta(13)C. Despite the potential for introduced error, there is no consensus on the need to account for lipids in stable isotope analyses. Here we address two questions: (1) If and when is it important to account for the effects of variation in lipid content on delta(13)C? (2) If it is important, which method(s) are reliable and robust for dealing with lipid variation? We evaluated the reliability of direct chemical extraction, which physically removes lipids from samples, and mathematical normalization, which uses the carbon-to-nitrogen (C:N) ratio of a sample to normalize delta(13)C after analysis by measuring the lipid content, the C:N ratio, and the effect of lipid content on delta(13)C (Deltadelta(13)C) of plants and animals with a wide range of lipid contents. For animals, we found strong relationships between C:N and lipid content, between lipid content and Deltadelta(13)C, and between C:N and Deltadelta(13)C. For plants, C:N was not a good predictor of lipid content or Deltadelta(13)C, but we found a strong relationship between carbon content and lipid content, lipid content and Deltadelta(13)C, and between and carbon content and Deltadelta(13)C. Our results indicate that lipid extraction or normalization is most important when lipid content is variable among consumers of interest or between consumers and end members, and when differences in delta(13)C between end members is <10-12 per thousand. The vast majority of studies using natural variation in delta(13)C fall within these criteria. Both direct lipid extraction and mathematical normalization reduce biases in delta(13)C, but mathematical normalization simplifies sample preparation and better preserves the integrity of samples for delta(15)N analysis.
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                Author and article information

                Contributors
                Journal
                Reviews in Aquaculture
                Reviews in Aquaculture
                Wiley
                1753-5123
                1753-5131
                September 2022
                April 25 2022
                September 2022
                : 14
                : 4
                : 2023-2037
                Affiliations
                [1 ] Key Laboratory of Mariculture, Ministry of Education Ocean University of China Qingdao China
                [2 ] School of Marine Science and Engineering Nanjing Normal University Nanjing China
                [3 ] Function Laboratory for Marine Fisheries Science and Food Production Processes Qingdao National Laboratory for Marine Science and Technology Qingdao Shandong Province China
                [4 ] College of Food Science and Engineering Ocean University of China Qingdao China
                Article
                10.1111/raq.12686
                733ccedc-d877-47b6-92e8-474cad3cccfc
                © 2022

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