化学计量学结合气质联用法对4种食用动物油判别模型的构建
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摘要
通过测定4种不同类型动物油(鸡油、牛油、羊油和猪油)的挥发性成分,从动物油挥发性风味物质的角度,探讨了对不同类型动物油进行判别和分类的可能性。采用热脱附/气相色谱-质谱联用法(TD/GCMS)对4种动物油的挥发性成分进行准确定性以及相对含量测定,利用SPSS 22.0统计软件对4种动物油的挥发性化合物进行主成分分析、聚类分析以及判别分析。依据挥发性化合物的风味阈值、特性以及相对含量水平,进行变量与指标损益之后应用主成分分析,在4种动物油的53种挥发性成分中筛选出19种主要风味物质,并将其相对含量进行降维得到3个主成分,应用主成分分析结果依次进行聚类分析和判别分析,建立了动物油的3个典则判别函数模型。对鸡油、牛油、羊油和猪油的挥发性成分在训练模型内进行判别,模型验证结果的正确率为100%。
The volatile components of four different types of animal oils,e.g.chicken oil,tallow,goat oil and lard oil,were determined.In perspective of the volatile flavor substances of animal oils,the possibilities of distinguishing and classifying different types of animal oils were explored.A gas chromatography-mass spectrometry with thermal desorption( TD/GC-MS) was performed for the determination of the quasi-determinacy and relative contents of volatile components in four animal oils,while principal component analysis,cluster analysis and discriminant analysis were applied in the analysis of the principal components of volatiles in the oils based on SPSS 22.0 statistical software.According to the flavor threshold value and characteristics of volatile compounds and their relative contents,the principal component analysis( PCA) was used after the variables and index gains and losses.A total of 19 main flavor substances were screened out from the 53 volatile components in the four animal oils,and their relative contents were reduced to obtain three principal components.Based on this,three canonical discriminant function models for animal oils were established by using the results of principal component analysis in turn for cluster analysis and discriminant analysis.The accuracies for discriminating the volatile components of chicken oil,tallow,goat oil and lard oil by the training models reached to 100%.
The volatile components of four different types of animal oils,e.g.chicken oil,tallow,goat oil and lard oil,were determined.In perspective of the volatile flavor substances of animal oils,the possibilities of distinguishing and classifying different types of animal oils were explored.A gas chromatography-mass spectrometry with thermal desorption( TD/GC-MS) was performed for the determination of the quasi-determinacy and relative contents of volatile components in four animal oils,while principal component analysis,cluster analysis and discriminant analysis were applied in the analysis of the principal components of volatiles in the oils based on SPSS 22.0 statistical software.According to the flavor threshold value and characteristics of volatile compounds and their relative contents,the principal component analysis( PCA) was used after the variables and index gains and losses.A total of 19 main flavor substances were screened out from the 53 volatile components in the four animal oils,and their relative contents were reduced to obtain three principal components.Based on this,three canonical discriminant function models for animal oils were established by using the results of principal component analysis in turn for cluster analysis and discriminant analysis.The accuracies for discriminating the volatile components of chicken oil,tallow,goat oil and lard oil by the training models reached to 100%.
引文
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