食品科学 ›› 2018, Vol. 39 ›› Issue (22): 207-212.doi: 10.7506/spkx1002-6630-201822032

• 成分分析 • 上一篇    下一篇

基于酚类化合物组成差异的7 类植物油脂识别

白云慧1,温海超1,张磊2,倪元颖1,李景明1,*   

  1. (1.中国农业大学食品科学与营养工程学院,北京 100083;2.新疆农业大学科研管理处,新疆?乌鲁木齐 830052)
  • 出版日期:2018-11-25 发布日期:2018-11-21
  • 基金资助:
    公益性行业(农业)科研专项(201303072)

Phenolic Compositions and Discrimination of Seven Vegetable Oils

BAI Yunhui1, WEN Haichao1, ZHANG Lei2, NI Yuanying1, LI Jingming1,*   

  1. (1. College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China;2. Scientific Research Administration Department, Xinjiang Agricultural University, ürümqi 830052, China)
  • Online:2018-11-25 Published:2018-11-21

摘要: 采用超高效液相色谱-串联质谱联用技术,对葵花籽油、菜籽油、花生油、胡麻油、橄榄油、玉米油和芝麻油中的酚类化合物进行检测,采用主成分分析、线性判别分析和层次聚类分析3?种方法识别植物油。结果表明:植物油中酚类化合物组成和含量存在明显差异;主成分分析中,提取4?个主成分可以反映原变量89.42%的信息,花生油、橄榄油、葵花籽油和芝麻油分布在不同象限,区分良好;线性判别分析结果显示,在84.4%程度上可以对7?种植物油实现良好区分;层次聚类分析中,菜籽油、橄榄油、芝麻油可以同其他植物油明显区分。

关键词: 植物油, 酚类化合物, 主成分分析, 线性判别分析, 层次聚类分析

Abstract: The phenolic compositions of sunflower oil, rapeseed oil, peanut oil, flaxseed oil, olive oil, corn oil and sesame oil were determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Principal component analysis, linear discriminant analysis and cluster analysis were applied to discriminate these vegetable oils. Results showed that phenolic composition and contents greatly varied among these vegetable oils. In PCA analysis, four principal components were extracted, which accounted for 89.42% of the total variance explained. The PCA score plots showed a noticeable difference among the seven oils. The vegetable oils were apparently distinguished by linear discriminant analysis with an accuracy rate of 84.4%. Good discrimination of rapeseed oil, olive oil and rapeseed oil from other oils was achieved by hierarchical cluster analysis.

Key words: vegetable oil, phenolic compound, principal component analysis, linear discriminant analysis, hierarchical cluster analysis

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