Food Analytical Methods

, Volume 8, Issue 5, pp 1088–1092 | Cite as

A Tool for General Quality Assessment of Black Tea—Retail Price Prediction by an Electronic Tongue

  • Maria Khaydukova
  • Xavier Cetó
  • Dmitry Kirsanov
  • Manel del Valle
  • Andrey Legin


Retail price of food products is a complex interplay between multiple factors. Overall product quality has got one of the most serious impacts on the price in many situations. In the present study, an artificial sensory system (potentiometric electronic tongue) was employed for the analysis of black tea samples purchased in the retail stores in Spain and Russia. It was possible to relate the response of a potentiometric sensor system with retail prices of various black tea samples by means of partial least squares (PLS) regression. PLS regression models are allowed for the prediction of retail price with mean relative errors of about 15 and 25 % for Spain’s tea bags and for loose-packed tea from Russia, respectively. The suggested approach shows a promise for the development of an instrumental analytical technique for regulatory authorities to fight with counterfeits and for commercial purposes to evaluate market space.


Black tea Multisensor system Electronic tongue Retail price assessment 



Maria Khaydukova acknowledges the St. Petersburg State University for a research Grant and partial financial support from the Government of the Russian Federation, Grant 074-U01. Dmitry Kirsanov and Andrey Legin have received partial financial support from the Government of the Russian Federation, Grant 074-U01. Manel del Valle thanks the support from the programme ICREA Academia.

Conflict of Interest

Maria Khaydukova declares that she has no conflict of interest. Xavier Cetó declares that he has no conflict of interest. Dmitry Kirsanov declares that he has no conflict of interest. Manel del Valle declares that he has no conflict of interest. Andrey Legin declares that he has no conflict of interest. This article does not describe any studies with human or animal subjects.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Maria Khaydukova
    • 1
    • 2
  • Xavier Cetó
    • 3
  • Dmitry Kirsanov
    • 1
    • 2
  • Manel del Valle
    • 3
  • Andrey Legin
    • 1
    • 2
  1. 1.Laboratory of Chemical Sensors, Institute of ChemistrySt. Petersburg State UniversitySt. PetersburgRussia
  2. 2.Laboratory of Artificial Sensory SystemsITMO UniversitySt. PetersburgRussia
  3. 3.Sensors & Biosensors Group, Department of ChemistryUniversitat Autònoma de BarcelonaBellaterraSpain

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