食品科学

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基于电子鼻和多种模式识别算法的不同种食用香辛料的鉴别

丁玉勇   

  1. 江苏食品药品职业技术学院,江苏 淮安 223003
  • 出版日期:2013-08-25 发布日期:2013-09-03

Identification of Different Food Grade Spices by Use of Electronic Nose and a Variety of Pattern Recognition Algorithms

DING Yu-yong   

  1. Jiangsu Food and Pharmaceutical College, Huai’an 223003, China
  • Online:2013-08-25 Published:2013-09-03

摘要:

电子鼻检测8种食用香辛料煮制液,运用多种模式识别算法分析。结果表明:主成分分析(PCA)可以完全区分8种不同香辛料;线性判别式分析(LDA)有3个品种有重叠,无法区分,但类内距离变小;用判别因子分析(DFA)建立的香料品种模型识别8种香辛料,识别率100%;用偏最小二乘分析(PLS)建立回归模型,预测未知含量4种香料煮制液,预测误差在4.0%~8.7%之间,因此电子鼻结合适当的识别算法可以用于香辛料品种的区分、识别和含量的预测。

关键词: 电子鼻, 模式识别, 香辛料

Abstract:

Eight kinds of food grade spices were detected by electronic nose and analyzed by a variety of pattern recognition
algorithms. The results showed that principal component analysis could entirely distinguish among 8 different kinds of spices.
Linear discriminant analysis could not successfully distinguish these spices with 3 of them overlapping though shortened
intra-class distances were reported. A 100% recognition rate was acquired, when the spices were detected by the model based
on discriminant factor analysis. The regression model built by partial least squares analysis was used to estimate unknown
concentration of infusions of 4 spices showing errors between 4.0% and 8.7%. Therefore, electronic nose combined with proper
recognition algorithms is able to differentiate among and identify spices and estimate their concentration.

Key words: electronic nose, pattern recognition, spices