Application of screen-printed electrode biosensor combined with COI gene in meat identification technology

  • JIANG Juanjuan ,
  • DING Xinyi ,
  • NI Jun ,
  • DONG Yiyan ,
  • CHEN Huan ,
  • WEN Hong ,
  • LIU Jiahui
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  • 1 (Beijing University of Chemical Technology, College of Life Science and Technology, Beijing 100029, China)
    2 (Beijing Guangqumen Middle School, Beijing 100062, China)
    3 (Peking University, College of Chemistry and Molecular Engineering, Beijing 100000, China)

Received date: 2019-06-09

  Online published: 2020-02-11

Abstract

In order to identify mixed meat quickly and conveniently, this research attempted to build a sensor platform to identify binary blends of pork and beef, and to evaluate its specificity, sensitivity and commercial applications by using animal mitochondrial COI gene as recognition elements and disposable screen-printed electrode biosensors as devices. The research demonstrated that raw beef and raw pork with the target sequence in the range of 10-13-10-5 mol/L showed a good linear relationship with reduction peak current; the linear correlation of beef and pork were 0.961 36 and 0.987 4 respectively, while the detection limits were 5.048×10-14 mol/L and 3.491×10-14 mol/L respectively. The experiment was performed to simulate the adulteration of pork/beef mixture. When the amount of raw meat mixture was 50 ng, the electric signal value of the reactive dye methylene blue was more stable. On the other hand, when the adulteration ratio was less than 25% or greater than 25%, the binary mixture could be identified. The research reveals that the electrochemical sensor is a sensitively wide detecting, amplification-free, lower cost, and more convenient operation technology. Therefore, it is more in line with the requirements of low-proportion adulteration and rapid on-site detection.

Cite this article

JIANG Juanjuan , DING Xinyi , NI Jun , DONG Yiyan , CHEN Huan , WEN Hong , LIU Jiahui . Application of screen-printed electrode biosensor combined with COI gene in meat identification technology[J]. Food and Fermentation Industries, 2019 , 45(23) : 270 -275 . DOI: 10.13995/j.cnki.11-1802/ts.021296

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