食品科学

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基于特征脂肪酸及脂肪酸比值的食用植物油掺假判别

吴卫国,刘真知,彭思敏,唐 芳,刘军鸽,田 梅   

  1. 1.湖南农业大学食品科技学院,食品科学与生物技术湖南省重点实验室,湖南 长沙 410128;
    2.湖南省桃江县质量监督检验及计量检定所,湖南 桃江 413400;
    3.湖南农业大学科技创新平台管理中心,湖南 长沙 410128
  • 出版日期:2013-08-25 发布日期:2013-09-03

Adulteration Identification of Edible Vegetable Oils Based on Fatty Acid Profile

WU Wei-guo,LIU Zhen-zhi,PENG Si-min,TANG Fang,LIU Jun-ge,TIAN Mei   

  1. 1. Hunan Province Key Laboratory of Food Science and Biotechnology, College of Food Science and Technology,Hunan Agricultural University, Changsha 410128, China;
    2. Quality Supervision and Determination Agency of Taojiang County, Hunan Province, Taojiang 413400, China;
    3. Management Center of Scientific and Technological Innovation Platform, Hunan Agricultural University, Changsha 410128, China
  • Online:2013-08-25 Published:2013-09-03

摘要:

采用气质联用技术获取茶籽油(n=12)、菜籽油(n=10)、花生油(n=8)、大豆油(n=7)、棉籽油(n=7)、棕榈油(n=2)、葵花籽油(n=2)共48个植物油纯油样品的脂肪酸组成,并结合每类纯油脂国家标准所标注的脂肪酸含量,分析每类纯油的特征脂肪酸组成;同时以茶油掺假为列,设计茶油中掺入花生油、大豆油、棉籽油、葵花籽油的掺假模型,绘制茶油掺假油脂样品中的油酸/亚油酸和棕榈酸/硬脂酸的二维图,建立基于特征脂肪酸及脂肪酸比值的食用植物油掺假判别的方法。

关键词: 植物油脂, 掺假, 气相色谱-质谱联用, 特征脂肪酸

Abstract:

Fatty acid composition of tea seed oil (n = 12), rape seed oil (n = 10), peanut oil (n = 8), soybean oil (n = 7),
cotton seed oil (n = 7), palm oil (n = 2) and sunflower seed oil (n = 2) was determined using gas chromatography-mass
spectrometry (GC-MS). Based on the results obtained and the national standards for fatty acid composition of pure edible
vegetable oils, some characteristic fatty acids in the seven types of vegetable oils were defined. A two-dimensional diagram
was drawn for cis-oleic acid methyl ester/cis-linoleic acid methyl ester and palmitic acid methyl ester/stearic acid methyl
ester ratios in tea seed oil adulterated with peanut oil, soybean oil, cotton seed oil, sunflower oil, respectively. Finally we
developed a method for identifying adulterated edible vegetable oils based on fatty acid profile.

Key words: vegetable oils, adulteration, gas chromatography-mass spectrometry (GC-MS), characteristic fatty acids