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气相色谱-质谱联用法(GC-MS)因其分离效率高、分析速度快、灵敏度高、检测线低等特点,被广泛应用于油脂分析鉴别领域。但与矿物油的鉴别相比,动物油类之间的主成分种类相近且含量集中,单纯通过GC-MS进行鉴别分析具有局限性,因此,区分常见动物油一直是司法鉴定领域中的难题。本文尝试运用GC/MS分析人油和5种常见动物油,通过对峰面积归一化法得出每个样品脂肪酸相对百分含量,结合KNN算法(K Nearest Neighbors,KNN)对人油与常见动物油进行建模区分。本实验以每个动物油脂样本中的6个主要脂肪酸相对含量(C14:0、C16:0、C16:1、C18:0、C18:1、C18:2)作为变量值,运用训练样本即为测试样本的方法进行交互验证,发现当k值等于3或4时,测试样本出错率最低,区分效果良好,人油测试样本分类准确率达到100%,并考察了6种脂肪酸相对含量作为变量的区分贡献值,结果C14:0区分贡献值最大。此方法相对于传统分析手段而言简单易行,提高了鉴别分析的效率和精度,尽管实验样本种类有限,但实验方法具有普遍意义。本文为动物油区分的进一步深入研究提供了一种新的思路和参考。
Gas chromatography-mass spectrometry (GC-MS) is widely used in the field of oil analysis due to its high separation efficiency, high analysis speed, high sensitivity and low detection line. However, compared with the identification of mineral oil, the main components of animal oils are similar in type and concentration, and the identification by GC-MS is limited. Therefore, it is always a difficult problem in forensic identification to distinguish common animal oils. This article attempts to use GC / MS analysis of human oil and five common animal oils, by the peak area normalization method to obtain the relative percentage of fatty acids in each sample, combined KNN algorithm (K Nearest Neighbors, KNN) of human oil and common animal oil Distinguish modeling. In this experiment, the relative contents of 6 major fatty acids (C14: 0, C16: 0, C16: 1, C18: 0, C18: 1, C18: 2) in each animal fat sample were used as the variable values. The results show that when the k value is equal to 3 or 4, the error rate of the test sample is the lowest, and the discrimination effect is good. The classification accuracy of the human oil test sample reaches 100%, and the relative content of the six fatty acids as the variable Distinguish contribution value, the result C14: 0 Distinguish contribution maximum. Compared with the traditional analysis methods, this method is simple and easy, which improves the efficiency and accuracy of the discriminant analysis. Although the experimental sample types are limited, the experimental method has universal significance. This article provides a new way of thinking and reference for the further research on animal oil differentiation.