1. 广东工业大学轻工化工学院
2. 惠州出入境检验检疫局
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王同珍, 余林, 邱思聪, 等. 气相色谱-质谱技术结合化学计量学对6种植物油进行判别分析[J]. 分析测试学报, 2015,34(1):50-55.
Discriminant Analysis for Six Kinds of Vegetable Oils by Gas Chromatography-Mass Spectrometry Combined with Chemometrics[J]. 2015,34(1):50-55.
测定了6种不同种类植物油(茶籽油、大豆油、花生油、葵花籽油、玉米油和芝麻油)的脂肪酸组成及含量,旨在探讨利用植物油脂肪酸的指标对不同种类的植物油进行分类和判别的可能性。采用气相色谱-质谱联用技术,对6种不同植物油中脂肪酸的组成和含量进行测定,用SPSS19.0统计软件进行主成分分析、聚类分析和判别分析。对6种不同植物油脂肪酸进行分析、对比,得出植物油脂的主要成分为C16∶0,C18∶0,C18∶1 cis-9,C18∶2 cis-9,12和C18∶3 cis-9,12,15。这5种主要脂肪酸的总含量在茶籽油、大豆油、花生油、葵花籽油、玉米油和芝麻油中分别为98.455%,97.586%,89.019%,97.378%,98.294%和98.021%。6种植物油的不饱和度(U/S)均大于2.000,其中最小为花生油2.055,最大为茶籽油3.976。进行主成分分析降维得到前3个主成分,因为前3个主成分的特征//值均大于1且累计贡献率达到80.060%,第1主成分的贡献率为35.853%,第2主成分的贡献率为23.847%,第3主成分的贡献率为20.360%。 建立了3个典则判别函数,典则判别函数的相关系数均大于0.990,且对于茶籽油、大豆油、花生油、葵花籽油、玉米油和芝麻油的初始分类正确率为100.0%,交叉验证正确率为100.0% 。
Determination of compositions and contents of fatty acids in vegetable oils,including tea seed oil,soybean oil,peanut oil,sunflower seed oil,corn oil and sesame oil,was performed by gas chromatography-mass spectrometry(GC-MS),to investigate the use of vegetable oil fatty acids indicators to distinguish different types of vegetable oils and classification possibilities.SPSS.19.0 statistical software was used to principal component analysis,cluster analysis and discriminant analysis.The fatty acids in six vegetable oils were investigated.The results indicated that the main compositions of vegetable oils were C16∶0,C18∶0,C18∶1 cis-9,C18∶2 cis-9,12 and C18∶3 cis-9,12,15,respectively.Total contents of five major fatty acids were 98.455%,97.586%,89.019%,97.378%,98.294% and 98.021% corresponding to the tea seed oil,soybean oil,peanut oil,sunflower oil,corn oil and sesame oil,respectively.The ratios of unsaturated and saturated fatty acids(U/S) were greater than 2.000 in six kinds of vegetable oils,in which the minimum value was 2.055 for peanut oil and the maximum value was 3.976 for tea seed oil.When this data set was used,in order to obtain the reduced number of principal components,the first three principal compounds were chosen(80.060% of the total variance) because the eigenvalues were higher than 1,and which explained the reason of higher percentage of variance than each original data.The first principal component explained the higher percentage of variance 35.853%,the second principal component explained the explained 23.847% and the third principal component explained 20.360%.The study established three discriminant functions and the discriminant function correlation coefficients were greater than 0.990.The initial classification accuracy and cross-validation accuracy of tea seed oil,soybean oil,peanut oil,sunflower oil,corn oil and sesame oil all reached to 100.0%.
植物油气相色谱-质谱联用仪主成分分析聚类分析判别分析
vegetable oilgas chromatograph-mass spectrometer(GC-MS)principal component analysis(PCA)cluster analysis(CA)discriminant analysis(DA)
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