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Journal of Sensors and Sensor Systems An open-access peer-reviewed journal
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Volume 7, issue 1
J. Sens. Sens. Syst., 7, 319-329, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
J. Sens. Sens. Syst., 7, 319-329, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Regular research article 26 Apr 2018

Regular research article | 26 Apr 2018

Voltammetric sensor for electrochemical determination of the floral origin of honey based on a zinc oxide nanoparticle modified carbon paste electrode

Kamalika Tiwari1, Bipan Tudu1, Rajib Bandyopadhyay1,2, Anutosh Chatterjee1, and Panchanan Pramanik3 Kamalika Tiwari et al.
  • 1Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata, India
  • 2Laboratory of Artificial Sensory Systems, ITMO University, Saint Petersburg, Russia
  • 3Institutes of Applied Science and Humanities, GLA University, Mathura, India

Abstract. A new methodology based on cyclic voltammetry using a chemically modified electrode has been developed for the discrimination of the floral origin of honey. This method involves an electronic tongue with an electrochemical sensor made from a carbon paste (CPs) electrode where zinc oxide (ZnO) nanoparticles are used as an electroactive binder material. The bare CPs electrode is evaluated for comparison. The electrochemical response of the modified electrode in 50 samples of five different floral types of honey has been analysed by the cyclic voltammetric technique. The voltammograms of each floral variety of honey reflect the redox properties of the ZnO nanoparticles present inside the carbon paste matrix and are strongly influenced by the nectar source of honey. Thus, each type of honey provides a characteristic signal which is evaluated by using principal component analysis (PCA) and an artificial neural network (ANN). The result of a PCA score plot of the transient responses obtained from the modified carbon paste electrode clearly shows discrimination among the different floral types of honey. The ANN model for floral classification of honey shows more than 90% accuracy. These results indicate that the ZnO nanoparticles modified carbon paste (ZnO Nps modified CPs) electrode can be a useful electrode for discrimination of honey samples from different floral origins.

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