FOOD SCIENCE ›› 2017, Vol. 38 ›› Issue (8): 313-317.doi: 10.7506/spkx1002-6630-201708049

• Safety Detection • Previous Articles    

Discrimination of Sesame Paste Quality by Electronic Nose

ZHANG Miao, JIA Hongfeng, LIU Guoqun, HUANG Xiaoqin   

  1. College of Food Science and Technology, Sichuan Tourism University, Chengdu 610100, China
  • Received:2017-04-26 Revised:2017-04-26 Online:2017-04-25 Published:2017-04-24

Abstract: Different commercial brands of sesame paste and sesame paste produced from different cultivars as well as sesame paste adulterated with various amounts of peanut paste were tested by electronic nose. The response signals were analyzed by principal component analysis (PCA), discriminant fact analysis (DFA), partial least-squares analysis regression (PLSR) and statistical quality control (SQC). The results showed that different brands of black sesame paste and white sesame paste and mixed sesame pastes could be effectively identified by electronic nose. The response to the addition of adulterant (0%, 5%, 10%, 20%, 40%, 60%, 80% and 100%) was linear with a high correlation coefficient (R2) of 0.99. The established partial least squares regression (PLSR) model gave a prediction error ranging from 0.7% to 2.7%. It was proved that electronic nose could be applied in sesame paste discrimination.

Key words: electronic nose, sesame paste, adulteration, distinguishing, sensor

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