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电子鼻快速检测煎炸油品质

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原文链接
  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
  • 维普
利用PEN3型电子鼻系统分析了高温煎炸过程中大豆色拉油挥发性成分的动态变化规律.大豆色拉油于180℃油浴锅控温无料煎炸,每隔6h取样电子鼻检测分析.结果发现,随着煎炸时间的延长,油中芳香苯类、氨氧化物、氨类、烷烃、硫化氢、乙醇等挥发性成分均有一定升高,尤其是氨氧化物、氨类、烷烃、硫化氢、醇类是煎炸油气味变化及品质恶化的主要来源.利用主成分分析方法(PCA)及线性判别分析方法(LDA)对不同煎炸时间的大豆色拉油进行归类区分,发现LDA分析效果优于PCA.采用负荷加载(Loadings)分析可判别不同传感器对于第一、第二主成分的贡献率及相关性,S1、S2、S3、S5、S6、S7、S8、S9等可作为优选传感器应用于分析煎炸油品质变化.因此利用电子鼻系统快速分析辨别煎炸油新鲜程度及品质是可行的.
Fast Detection of Fried Oil Quality by Electronic Nose
An electronic nose (PEN3) was used to characterize the dynamic change of volatile components during the frying process of soybean salad oil without objects in oil bath at 180 ℃.Volatile components produced by soybean oil were monitored dynamically and analyzed every 6 h.Results showed that volatile components such as aromatic benzenes, nitrogen oxides, amines, alkanes, H2S and ethanol revealed an obvious increase with the prolonged frying time.In addition, nitrogen oxides, amines, alkanes, H2S and ethanol were the major factors for the deterioration of oil.Data analysis was conducted by using principal component analysis (PCA) and linear discrimination analysis (LDA).LDA was more effective than PCA to distinguish the oil with various frying time.Loading analysis was used to analyze the contribution and correlation of different sensors to the first and second principal components.The sensors S1, S2, S3, S5, S6, S7, S8 and S9 could be used to analyze the quality of frying oil.These results will be helpful for the application of electronic nose to detect the quality of frying oil.

electronic nosequality of frying oilprincipal component analysislinear discrimination analysisloading analysis

李靖、王成涛、刘国荣、赵磊、杨培强

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北京工商大学食品添加剂与配料北京高校工程研究中心,北京 100048

北京工商大学北京市食品风味化学重点实验室,北京 100048

上海纽迈电子科技有限公司,上海 200333

电子鼻系统 煎炸油品质 主成分分析 线性判别分析 载荷分析

教育部科学技术研究重点项目北京市教委科研面上项目北京市高校人才强教计划项目北京市教委学科与研究生教育食品学科特色教学科研创新平台建设项目

211101KM201110011001PHR201008237PXM2012-014213-000063

2013

食品科学
北京食品科学研究院

食品科学

CSTPCDCSCD北大核心
影响因子：1.327
ISSN：1002-6630
年,卷(期)：2013.34(8)
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