在商业鱼类产品中使用质谱和光谱图书馆匹配方法进行鱼类物种认证
Madhushri S Varunjikar1, Javier Pineda-Pampliega1, Ikram Belghit1
1Institute of Marine Research, P.O. Box 1870 Nordnes, 5817 Bergen, Norway.
Food research international (Ottawa, Ont.)
|August 15, 2024
概括
海鲜欺诈是一个全球性问题. 一种光谱图书馆匹配方法可以准确地识别各种产品中的鱼类,即使是加工的产品,有助于食品认证.
科学领域:
- 食品科学 食品科学 食品科学
- 分子生物学分子生物学
- 分析化学 分析化学
背景情况:
- 海鲜欺诈,包括错误标签和改,对全球的粮食安全和消费者安全构成重大风险.
- 准确的食品和料认证工具对于监管合规和消费者保护至关重要.
- 对于许多商业上重要的海洋物种,有限的基因组数据阻碍了传统的认证方法.
研究的目的:
- 评估用于验证鱼类物种的光谱图书馆匹配方法.
- 在各种样本类型上测试该方法的有效性,包括新鲜鱼,混合物和加工商业产品.
- 评估复杂食品矩阵中识别物种的方法的稳定性.
主要方法:
- 开发和应用29种鱼类的参考光谱库.
- 蛋白质组分析与光谱图书馆匹配相结合.
- 在单个鱼,实验室制备的混合物和商业海鲜产品 (鱼蛋糕,汉堡) 上测试该方法.
主要成果:
- 频谱图书馆匹配方法正确地认证了新鲜鱼样与参考图书馆的真实性.
- 对于实验室制备的鱼类混合物,可以实现精确的物种识别.
- 该方法在高度加工的商业产品中证明了鱼类物种的真实性和稳定性.
结论:
- 参考光谱库与蛋白质组分析相结合,为海产品认证提供了强大的解决方案,即使基因组信息有限.
- 这种方法有效地识别了各种样本复杂性的鱼类,从新鲜的肌肉到加工食品.
- 该方法为应对食品和料认证当前和未来的挑战提供了可行的策略,在北极等新兴市场有潜在的应用.
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