通过质谱联用统计分析对植物油进行鉴别

Differentiation of vegetable oils by mass spectrometry combined with statistical analysis.

作者信息

Jakab A, Nagy K, Héberger K, Vékey K, Forgács E

机构信息

Institute of Chemistry, Chemical Research Center, Hungarian Academy of Sciences, P.O. Box 17, H-1525, Hungary.

出版信息

Rapid Commun Mass Spectrom. 2002;16(24):2291-7. doi: 10.1002/rcm.862.

DOI:10.1002/rcm.862

PMID:12478574

Abstract

The main triacylglycerol (TAG) composition of different plant oils (almond, avocado, corn germ, grape seed, linseed, mustard seed, olive, peanut, pumpkin seed, sesame seed, soybean, sunflower, walnut and wheat germ) were analyzed using two different mass spectrometric techniques: HPLC/APCI-MS (high-performance liquid chromatography/atmospheric pressure chemical ionization mass spectrometry) and MALDI-TOFMS (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry).Linear discriminant analysis (LDA) as a multivariate mathematical statistical method was successfully used to distinguish different plant oils based on their relative TAG composition. With LDA analysis of either APCI-MS or MALDI-MS data, the classification among the almond, avocado, grape seed, linseed, mustard seed, olive, sesame seed and soybean oil samples was 100% correct. In both cases only 6 different oil samples from a total of 73 were not classified correctly.

摘要

使用两种不同的质谱技术分析了不同植物油（杏仁油、鳄梨油、玉米胚芽油、葡萄籽油、亚麻籽油、芥花籽油、橄榄油、花生油、南瓜籽油、芝麻油、大豆油、葵花籽油、核桃油和小麦胚芽油）的主要三酰甘油（TAG）组成：HPLC/APCI-MS（高效液相色谱/大气压化学电离质谱）和MALDI-TOFMS（基质辅助激光解吸/电离飞行时间质谱）。线性判别分析（LDA）作为一种多元数学统计方法，成功地用于根据其相对TAG组成区分不同的植物油。通过对APCI-MS或MALDI-MS数据的LDA分析，杏仁油、鳄梨油、葡萄籽油、亚麻籽油、芥花籽油、橄榄油、芝麻油和大豆油样品之间的分类正确率为100%。在这两种情况下，总共73个油样中只有6个未被正确分类。