研究报告

基于脂肪酸特征的鱼油和藻油保健品真实性鉴别研究

  • 郑丽婷 ,
  • 胡飞 ,
  • 冯迪 ,
  • 安普畅 ,
  • 安红梅 ,
  • 武竹英 ,
  • 王道兵 ,
  • 钟其顶
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  • 1(华南理工大学 食品科学与工程学院,广东 广州,510640)
    2(国家市场监督管理总局技术创新中心(轻工消费品质量安全),北京,100015)
    3(北京工业大学 环境与生命学部,北京,100124)
    4(中轻技术创新中心有限公司,北京,100015)
第一作者:硕士研究生(钟其顶正高级工程师为通信作者,E-mail:zhongqiding@163.com)

收稿日期: 2024-10-25

  修回日期: 2024-12-10

  网络出版日期: 2025-08-29

基金资助

国家重点研发计划项目(2023YFF1104700);中轻集团科技项目(ZQ2021C03)

Authenticity identification of fish oil and algae oil functional food based on fatty acid characteristics

  • ZHENG Liting ,
  • HU Fei ,
  • FENG Di ,
  • AN Puchang ,
  • AN Hongmei ,
  • WU Zhuying ,
  • WANG Daobing ,
  • ZHONG Qiding
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  • 1(School of Food Science and Engineering, South China University of Technology, Guangzhou, 510640, China)
    2(Technology Innovation Center of Light Industrial Consumption Goods Quality and Safety, State Administration for Market Regulation, Beijing 100015, China)
    3(Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China)
    4(Sinolight Technology Innovation Centre Co.Ltd., Beijing 100015, China)

Received date: 2024-10-25

  Revised date: 2024-12-10

  Online published: 2025-08-29

摘要

该研究建立了基于脂肪酸组成鉴别鱼油和藻油真实性的方法。采用正交偏最小二乘判别分析(orthogonal partial least squares discriminant analysis, OPLS-DA)评价基于11种主要脂肪酸鉴别鱼油和藻油保健品原料真实性的可行性,主成分分析(principal component analysis,PCA)可实现鱼油、藻油和其他3种植物油的区分,OPLS-DA模型可实现未知样品中掺杂植物油的分类预测。鱼油和藻油原料可以通过OPLS-DA有效鉴别,模型的R2X=0.870,R2Y=0.931,Q2=0.833,经过200次循环迭代置换检验证明模型不存在过度拟合,经特征差异代谢物筛选(VIP>1,P<0.05),获得鱼油和藻油鉴别的关键脂肪酸为二十二碳六烯酸(docosahexaenoic acid,DHA)和二十碳五烯酸(eicosapentaenoic acid,EPA)。采用气相色谱内标法对市售不同类型鱼油和藻油保健品中DHA和EPA的含量进行测定,方法重复性为1.40%和1.49%,稳定性为1.58%和1.51%,加标回收率为98.79%和99.91%。结果发现市售10款产品中有1款以大豆油冒充鱼油以假乱真。研究表明,脂肪酸组成结合化学计量学可为鱼油和藻油保健品真实性判别提供技术支撑。

本文引用格式

郑丽婷 , 胡飞 , 冯迪 , 安普畅 , 安红梅 , 武竹英 , 王道兵 , 钟其顶 . 基于脂肪酸特征的鱼油和藻油保健品真实性鉴别研究[J]. 食品与发酵工业, 2025 , 51(16) : 72 -80 . DOI: 10.13995/j.cnki.11-1802/ts.041289

Abstract

This study established a method for authenticating fish oil and algal oil based on fatty acid composition.Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to evaluate the feasibility of identifying the authenticity of fish oil and algal oil using 11 major fatty acids.Principal component analysis (PCA) effectively distinguished fish oil, algal oil, and three other kinds of vegetable oils.Furthermore, the OPLS-DA model accurately predicted the classification of unknown samples containing adulterated vegetable oils.OPLS-DA demonstrated high efficacy in distinguishing fish oil and algal oil raw materials, with model parameters of R2X=0.870, R2Y=0.931, and Q2=0.833.After 200 iterative permutation tests, the model was confirmed to be free of overfitting.The key fatty acids for the identification of fish oil and algae oil were docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) after the characteristic differential metabolite screening (VIP>1, P<0.05).Using the gas chromatography internal standard method, the DHA and EPA content in various commercially available fish oil and algal oil health products was measured.The method demonstrated repeatability of 1.40% and 1.49%, stability of 1.58% and 1.51%, and recovery rates of 98.79% and 99.91%.It was found that among the 10 commercially available products, one product fraudulently substituted soybean oil for fish oil.These findings indicated that combining fatty acid composition analysis with chemometric techniques provides robust technical support for authenticating fish oil and algal oil health products.

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