Institute of Marine Research, P.O. Box 1870 Nordnes, 5817 Bergen, Norway.
Leiden University Medical Center, 2300 RC Leiden, the Netherlands.
Food Res Int. 2024 Sep;192:114785. doi: 10.1016/j.foodres.2024.114785. Epub 2024 Jul 16.
Seafood fraud has become a global issue, threatening food security and safety. Adulteration, substitution, dilution, and incorrect labeling of seafood products are fraudulent practices that violate consumer safety. In this context, developing sensitive, robust, and high-throughput molecular tools for food and feed authentication is becoming crucial for regulatory purposes. Analytical approaches such as proteomics mass spectrometry have shown promise in detecting incorrectly labeled products. For the application of these tools, genome information is crucial, but currently, for many marine species of commercial importance, such information is unavailable. However, when combining proteomic analysis with spectral library matching, commercially important fish species were successfully identified, differentiated, and quantified in pure muscle samples and mixtures, even when genome information was scarce. This study further tested the previously developed spectral library matching approach to differentiate between 29 fish species from the North Sea and examined samples including individual fish, laboratory-prepared mixtures and commercial products. For authenticating libraries generated from 29 fish species, fresh muscle samples from the fish samples were matched against the reference spectral libraries. Species of the fresh fish samples were correctly authenticated using the spectral library approach. The same result was obtained when evaluating the laboratory-prepared mixtures. Furthermore, processed commercial products containing mixtures of two or three fish species were matched against these reference spectral libraries to test the accuracy and robustness of this method for authentication of fish species. The results indicated that the method is suitable for the authentication of fish species from highly processed samples such as fish cakes and burgers. The study shows that current and future challenges in food and feed authentication can efficiently be tackled by reference spectral libraries method when prospecting new resources in the Arctic.
海鲜欺诈已成为全球性问题,威胁着食品安全和安全。海鲜产品的掺假、替代、稀释和标签错误是违反消费者安全的欺诈行为。在这种情况下,开发用于食品和饲料鉴定的敏感、稳健和高通量分子工具对于监管目的变得至关重要。分析方法,如蛋白质组学质谱,已显示出在检测标签错误的产品方面的潜力。对于这些工具的应用,基因组信息是至关重要的,但目前,对于许多具有商业重要性的海洋物种,这种信息是不可用的。然而,当将蛋白质组分析与光谱库匹配结合使用时,成功地鉴定、区分和量化了纯肌肉样本和混合物中的商业重要鱼类物种,即使基因组信息很少。本研究进一步测试了先前开发的光谱库匹配方法,以区分来自北海的 29 种鱼类,并检查了包括单个鱼类、实验室制备的混合物和商业产品在内的样本。为了验证从 29 种鱼类生成的库,将鱼样的新鲜肌肉样本与参考光谱库进行匹配。使用光谱库方法正确鉴定了新鲜鱼样的物种。当评估实验室制备的混合物时,也得到了相同的结果。此外,含有两种或三种鱼类混合物的加工商业产品与这些参考光谱库进行匹配,以测试该方法用于鱼类物种鉴定的准确性和稳健性。结果表明,该方法适用于鉴定鱼饼和汉堡等高度加工样本中的鱼类物种。该研究表明,在北极地区勘探新资源时,参考光谱库方法可以有效地解决食品和饲料鉴定的当前和未来挑战。