Skip to main content
Log in

Electronic Olfactory Systems Based on Metal Oxide Semiconductor Sensor Arrays

  • Published:
MRS Bulletin Aims and scope Submit manuscript

Abstract

In this article, we present the Pico electronic nose, an artificial olfactory system based on thin-film semiconductor sensors, and two applications: food-quality control (coffee analysis) and environmental monitoring (odors at a landfill site). For both applications, the electronic nose data correlated with that of panels of trained judges. For the coffee, a global index (called the hedonic index) characterizing the sensorial appeal could be predicted with the electronic nose, and for the landfill site, the intensity of odors could be quantified. In this article, we stress the importance of stable and sensitive sensors, such as metal oxide thin films produced by sputtering, and of multivariate data analysis for extracting knowledge (e.g., gaining selectivity) from the data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. J. Gardner and P. Bartlett, Electronic Noses (Oxford University Press, 1999).

    Google Scholar 

  2. H. Ulmer, J. Mitrovics, G. Noetzel, U. Weimar, and W. Gopel, Sens. Actuators, B 43 (1997) p. 24.

    Google Scholar 

  3. P.N. Bartlett, T.M. Elliot, and J.W. Barcher, Food Technol. 51 (1997) p. 44.

    Google Scholar 

  4. F. Mellon, in Spectroscopic Techniques for Food Analysis, edited by R. Wilson (Wiley-VCH, Weinheim, Germany, 1994).

  5. D. Pal, S. Sachdeva, and S. Singh, J. FoodSci. Technol. 32 (1995) p. 357.

    Google Scholar 

  6. M. Pardo, G. Sberveglieri, IEEE Trans. Instrum. Meas. 51 (6) (December 2002) p. 1334.

    Google Scholar 

  7. M. Falasconi, M. Pardo, G. Sberveglieri, I. Riccò, and A. Bresciani, “The Novel EOS835 Electronic Nose and Data Analysis for Evaluating Coffee Ripening,” IEEE Sens. J. (2004) in press.

    Google Scholar 

  8. S. Singh, E. Hines, and J. Gardner, Sens. Actuators, B 30 (1996) p. 185.

    Google Scholar 

  9. M. Pardo, G. Niederjaufner, G. Benussi, E. Comini, G. Faglia, G. Sberveglieri, M. Holmberg, and I. Lundstrom, Sens. Actuators, B 69 (2000).

  10. R.M. Stuetz, R.A. Fenner, S.J. Hall, I. Stratful, and D. Loke, Water Sci. Technol. 41 (6) (2000) p. 41.

    CAS  Google Scholar 

  11. J. Nicolas, A.-C. Romain, D. Monticelli, J. Maternova, and Ph. Andŕ, in Proc. 7th Int. Symp. on Olfaction and Electronic Noses, edited by J. Gardner and K. Persaud (Institute of Physics Publishing, Bristol, UK, 2000) p. 141.

  12. G. Sberveglieri, S. Groppelli, P. Nelli, and C. Perego, Sens. Actuators, B 15-16 (1993) p. 86.

    Google Scholar 

  13. E. Zampiceni, E. Bontempi, G. Sberveglieri, and L. Depero, Thin Solid Films 418 (1) (2002) p. 16

    CAS  Google Scholar 

  14. R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification, 2nd ed. (John Wiley & Sons, New York, 2001).

    Google Scholar 

  15. Andrew Webb, Statistical Pattern Recognition, 2nd ed. (John Wiley & Sons, Chichester, UK, 2002).

    Google Scholar 

  16. A.K. Jain, R.P.W. Duin, and J. Mao, IEEE Trans. Pattern Analysis and Machine Intelligence 22 (1) (2000) p. 4.

    Google Scholar 

  17. M. Pardo, “Multivariate Data Analysis for Gas Sensor Arrays,” PhD thesis, Università di Brescia (March 2000).

    Google Scholar 

  18. R. Gutierrez-Osuna and H.T. Nagle, IEEE Trans. Systems, Man, and Cybernetics B 29 (5) (1999) p. 626.

    Google Scholar 

  19. M. Pardo and G. Sberveglieri, IEEE Sens. J. 2 (3) (2002) p. 203.

    Google Scholar 

  20. C.M. Bishop, Neural Networks for Pattern Recognition (Oxford University Press, Oxford, 1995).

    Google Scholar 

  21. G. Sberveglieri, G. Faglia, S. Groppelli, P. Nelli, and A. Camanzi, Semicond. Sci. Technol. 5 (41) (1990) p. 1231.

    CAS  Google Scholar 

  22. E. Comini, V. Guidi, C. Frigeri, I. Ricco, and G. Sberveglieri, Sens. Actuators, B 84 (2002) p. 26.

    Google Scholar 

  23. C. Garzella, E. Bontempi, L.E. Depero, A. Vomiero, G. Della Mea, and G. Sberveglieri, Sens. Actuators, B 93 (2003) p. 495.

    Google Scholar 

  24. K. Galatsis, Y.X. Li, W. Wlodarski, E. Comini, G. Sberveglieri, C. Cantalini, S. Santucci, and M. Passacantando, Sens. Actuators, B 83 (2002) p. 276.

    Google Scholar 

  25. H. Demuth and M. Beale, Manual of the Neural Network Toolbox, Version 3 (MathWorks, Novi, MI, 1998).

    Google Scholar 

  26. M. Pardo and G. Sberveglieri, IEEE Sens. J. 4 (3) (June 2004) p. 355.

    CAS  Google Scholar 

  27. M. Pardo, G. Sberveglieri, S. Gardini, and E. Dalcanale, Sens. Actuators, B 69 (2000) p. 359.

    Google Scholar 

  28. M. Pardo, G. Sberveglieri, F. Masulli, and G. Valentini, Anal. Chim. Acta 446 (2001) p. 223.

    CAS  Google Scholar 

  29. L. Odello and C. Odello, Espresso Italiano Tasting (Centro Studi e Formazione Assaggiatori, Brescia, Italy) 1998.

    Google Scholar 

  30. M. Pardo and G. Sberveglieri. in Proc. 8th Int. Symp. on Olfaction and Electronic Noses, edited by J. Stetter and R. Penrose (The Electrochemical Society, Pennington, NJ, 2001) p. 15.

  31. M. Pardo, G. Niederjaufner, E. Comini, G. Faglia, and G. Sberveglieri, in Proc. 4th Italian Conf. on Sensors and Microsystems (World Scientific, Rome, 1999) p. 99.

    Google Scholar 

  32. M. Falasconi, E. Gobbi, M. Pardo, M. della Torre, A. Bresciani, and G. Sberveglieri, Sens. Actuators, B (2004) in press.

    Google Scholar 

Download references

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pardo, M., Sberveglieri, G. Electronic Olfactory Systems Based on Metal Oxide Semiconductor Sensor Arrays. MRS Bulletin 29, 703–708 (2004). https://doi.org/10.1557/mrs2004.206

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1557/mrs2004.206

Keywords

Navigation