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Portable Olfactometric Platform for Scent Tea Classification

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Hybrid Intelligent Systems (HIS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1375))

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Abstract

Electronic Noses (ENs) are analytical systems whose operation is based on emulating the sense of smell of mammals and insects. ENs have demonstrated their effectiveness during the last two decades when used in the food and environmental industries. They have been used in tasks such as quality control, determination of contaminants, classification of products, to name a few. On the other hand, olfactometric systems can be used to evaluate the smell’s reaction to controlled stimulus. However, conventional olfactometric devices are meant to be used with biological systems. This work shows the results of the analysis of tea samples (dry commercial tea bags) carried out using a custom portable olfactometric platform to stimulate a custom EN system based on Metal Oxide Gas Sensors (MOGS) and an Artificial Neural Network (ANN). The obtained results show a classification accuracy greater than 80%, which denotes that the developed devices and experimental protocol are suitable for evaluating tea samples.

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Author information

Authors and Affiliations

  1. Bioelectronics Section, Department of Electrical Engineering, CINVESTAV-IPN, Mexico City, 07360, Mexico

    Jeniffer Molina, Luis Fernando Valdez & Juan Manuel Gutiérrez

Authors
  1. Jeniffer Molina
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  2. Luis Fernando Valdez
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  3. Juan Manuel Gutiérrez
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Corresponding author

Correspondence to Juan Manuel Gutiérrez .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland, Olten, Solothurn, Switzerland

    Thomas Hanne

  3. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, AL, USA

    Niketa Gandhi

  5. Universidade Federal da Bahia, Salvador, Bahia, Brazil

    Tatiane Nogueira Rios

  6. Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

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Molina, J., Valdez, L.F., Gutiérrez, J.M. (2021). Portable Olfactometric Platform for Scent Tea Classification. In: Abraham, A., Hanne, T., Castillo, O., Gandhi, N., Nogueira Rios, T., Hong, TP. (eds) Hybrid Intelligent Systems. HIS 2020. Advances in Intelligent Systems and Computing, vol 1375. Springer, Cham. https://doi.org/10.1007/978-3-030-73050-5_66

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