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一个协同解决方案,用于打击鱼的欺诈行为,使用光稳定同位素比率和胺痕迹剂

Maria Olga Varrà¹, Lenka Husáková², Paola Iacumin³

¹Department of Food and Drug, University of Parma, 43126 Parma, Italy.

|July 11, 2024

概括

这项研究开发了一种使用稳定同位素和微量元素准确识别鱼物种和起源的新方法,防止海鲜欺诈. 优化的战略确保了更好的可追溯性和消费者对海鲜行业的信任.

科学领域:

海洋生物学海洋生物学
食品科学食品科学食品科学
分析化学分析化学

背景情况:

海鲜欺诈,包括错误标记物种和原产地,是一个重大问题.
现有的方法难以可靠地区分相似的鱼物种及其起源.
确保海鲜产品的完整性对于消费者信任和行业可持续性至关重要.

研究的目的:

制定一个优化的战略,防止鱼物种和来源的欺诈性替代.
建立可靠的分析标准,以区分欧洲和飞与地中海和大西洋.
提高海鲜供应链中的可追溯性和安全性.

主要方法:

在鱼样本中分析稳定同位素 (δ13C, δ15N) 和微量元素 (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Yb, Lu).
使用同位素比质谱法 (IRMS) 和感应合等离子体质谱法 (ICP-MS).
员工分类和回归树 (CART) 分析,以制定决策规则和值.

主要成果:

δ13C和δ15N的变异主要取决于物种,但仅仅对于可靠的样本区分是不够的.
对于 δ13C (-19.91‰), δ15N (14.87‰) 和 Pr (0.49 μg kg-1) 的确定的值实现了高精度 (>90%).
开发的方法表现出优异的区分能力,精度和特异性超过80% (>93%).

结论:

稳定同位素和特定微量元素的联合使用,通过CART进行分析,为鱼身份认证提供了一个强大的策略.
这种新的方法显著提高了区分欧洲和来自不同海洋起源的飞之间的能力.
这些发现为提高海鲜可追溯性,确保产品完整性和增强消费者信心提供了有希望的解决方案.

关键词:

光稳定同位素,原产国标签.机器学习机器学习稀土元素稀土元素稀土元素可追溯性可追溯性

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