摘要
采用电子鼻对芝麻油中掺入芝麻油香精进行识别。通过对所获得的数据进行主成分分析(Prin-cipal Component Analysis,PCA)、判别因子分析(Discriminant Factor Analysis,DFA)、偏最小二乘回归分析(Par-tial Least-squares Analysis,PLS)和统计质量控制分析(Statistical Quality Control,SQC)。结果表明:不同样品在电子鼻传感器上有不同的特征性响应图谱,电子鼻能够有效识别不同掺入比例的芝麻油样品;DFA方法的区分效果比PCA方法更好;SQC模型对于掺入芝麻油香精超过50%的芝麻油能明显区分;采用PLS对数据进行处理,电子鼻响应信号和芝麻油香精掺入比例之间有很好的相关性(相关系数为0.992 1),PLS方法能有效识别掺入比例为0%～100%的试验样品。试验证明电子鼻可用于芝麻油掺假的识别。
In this study, the recognition of sesame oil essence adulteration in sesame oil was performed using an electronic nose system. The principal component analysis （PCA）, discriminant factor analysis （DFA） and partial least- squares analysis （PLS） and statistical quality control analysis （SQC） were conducted on the obtained data. The results indicated that different samples had different characteristic response signals in electronic nose sensor, the adulteration of sesame oil sample with different proportions could be recognized effectively and DFA was more compe- tent than PCA in distinguishing effect. Sesame oils adulterated with sesame oil essence at levels of adulteration excee- ding 50% were distinguished easily by SQC. There was high correlation between electronic nose sensors＇ response signals and the adulteration ratio of sesame oil essence （correlation coefficient = 0. 992 1 ） in processing data by the PLS model. PLS could effectively identify the experimental samples of sesame oils adulterated with 0%- 100% sesa- me oil essence. It proved in the test that electronic nose could be applied in adulteration recognition of sesame oil.
出处
《中国粮油学报》
EI
CAS
CSCD
北大核心
2013年第8期83-86,共4页
Journal of the Chinese Cereals and Oils Association
基金
四川省教育厅科研项目(11ZA177)
关键词
电子鼻
掺假
芝麻油
芝麻油香精
electronic nose, adulteration, sesame oil, sesame oil essence
