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Design, development and evaluation of a single-task electronic nose rig for assessing adulterated hydrosols

  • Seyed Ali Fatemi Heydarabad
  • Mohammad Hossein RaoufatEmail author
  • Saadat Kamgar
  • Akbar Karami
Original Paper
  • 73 Downloads

Abstract

The application of electronic noses (e-nose) in assessing food quality and authenticity is becoming more popular due to their excellent performance. Commercial e-noses are emerging in the market, however, they are diverse in function and still expensive, which economically limit their potential single-task food applications. This study concentrates on the design, development and evaluation of an e-nose rig capable of detecting adulterated hydrosols with the case study of rose water. The developed rig consists of eight gas sensors, an 18F4550 PIC microcontroller programmed in PICBasic Pro, and a mass flow controller. In addition, a computer based graphical user interface (GUI) programmed in MATLAB was developed. The ability of the developed e-nose to discriminate varying levels of adulterated rose water was evaluated. To this, eight different levels of adulterated rose water were prepared using rose geranium hydrosol and pure rose water. Radar-like graphs were established to visualize any differences in the response patterns. Principal component analysis (PCA) was performed to confirm the existing classes and also to reduce data dimensionality. This resulted in a data-point to variable ratio of 92:6 which is acceptable for the sake of this study to avoid overfitting problems. The PCA was followed by linear discriminant analysis (LDA) to evaluate the ability of the e-nose to indiscriminate adulterated rose water samples. This analysis revealed that the developed e-nose can perfectly discriminate various levels of adulteration found in our samples. LDA results were also compared to those of artificial neural networks (ANN), k-nearest neighbors and classification and regression trees among which the ANN showed the best performance. Hence, the rig successfully served as a cost-effective nondestructive tool in assessing adulterated rose water.

Keywords

Electronic nose Adulterated rose water Microcontroller-based PCA LDA 

Notes

Acknowledgements

The authors would like to gratefully acknowledge Research Council, Shiraz University for providing necessary support and funds and Dr. Goodner for his great feedbacks on some questions authors asked about his paper [26].

References

  1. 1.
    J.W. Gardner, P.N. Bartlett, A brief history of electronic noses. Sens. Actuators B 18(1–3), 210–211 (1994)Google Scholar
  2. 2.
    A.D. Wilson, Diverse applications of electronic-nose technologies in agriculture and forestry. Sensors 13(2), 2295–2348 (2013)Google Scholar
  3. 3.
    S. Chen, Y. Wang, S. Choi, Applications and technology of electronic nose for clinical diagnosis. Open J. Appl. Biosens. 2(02), 39–50 (2013)Google Scholar
  4. 4.
    H.K. Patel, The Electronic Nose: Artificial Olfaction Technology (Springer, New Delhi, 2014)Google Scholar
  5. 5.
    T.C. Pearce, S.S. Schiffman, H.T. Nagle, J.W. Gardner, Handbook of Machine Olfaction Electronic Nose Technology (Wiley-VCH, Weinheim, 2003)Google Scholar
  6. 6.
    G. Pioggia, F.D. Francesco, A. Marchetti, M. Ferro, R. Leardi, A. Ahluwalia, A composite sensor array impedentiometric electronic tongue Part II. Discrimination of basic tastes. Biosens. Bioelectron. 22(11), 2624–2628 (2007)Google Scholar
  7. 7.
    M. Peris, L. Escuder-Gilabert, A 21st century technique for food control: electronic noses. Anal. Chim. Acta 638(1), 1–15 (2009)Google Scholar
  8. 8.
    F. Shen, Q. Wu, A. Su, P. Tang, X. Shao, B. Liu, Detection of adulteration in freshly squeezed orange juice by electronic nose and infrared spectroscopy. Czech J. Food Sci. 34(3), 224–232 (2016)Google Scholar
  9. 9.
    M. Peris, L. Escuder-Gilabert, Electronic noses and tongues to assess food authenticity and adulteration. Trends Food Sci. Technol. 58, 40–54 (2016)Google Scholar
  10. 10.
    M.M. Macías, J.E. Agudo, A.G. Manso, C.J.G. Orellana, H.M.G. Velasco, R.G. Caballero, A compact and low cost electronic nose for aroma detection. Sensors 13(5), 5528–5541 (2013)Google Scholar
  11. 11.
    F. Sefidkon, Z. AKBARI, ASAREH, M. and BAKHSHI, K.G.R, Comparison of quantity and quality of aromatic compounds from Rosa damascena Mill by different extraction methods. Iran. J. Med. Aromat. Plants 22, 351–365 (2007)Google Scholar
  12. 12.
    M. Mahboubifar, S. Shahabipour, K. Javidnia, Evaluation of the valuable oxygenated components in Iranian rose water. Int. J. Chem. Tech. Res. 6, 4782–4788 (2014)Google Scholar
  13. 13.
    M. Moein, M.M. Zarshenas, S. Delnavaz, Chemical composition analysis of rose water samples from Iran. Pharm. Biol. 52(10), 1358–1361 (2014)Google Scholar
  14. 14.
    IRIC, Import and export of Iranian business products [online]. Statistics of the Islamic Republic of Iran Customs Administration, (2016), Available at: http://www.irica.gov.ir/
  15. 15.
    H.M.A. Cavanagh, J.M. Wilkinson, Bioactivity of Lavandula Essential Oils, Hydrosols and Plant Extracts (RIRDC, Kingston, 2006), pp. 1–30Google Scholar
  16. 16.
    B.R. Rao, Hydrosols and water-soluble essential oils of aromatic plants: future economic products. Indian Perfum. 56, 29–33 (2012)Google Scholar
  17. 17.
    H.C. Andola, V.K. Purohit, R.S. Chauhan, K. Arunachalam, Standardize quality standards for aromatic hydrosols. Med. Plants-Int. J. Phytomed. Relat. Ind. 6(3), 161–162 (2014)Google Scholar
  18. 18.
    A. Gliszczyńska-Świgło, J. Chmielewski, Electronic nose as a tool for monitoring the authenticity of food. A review. Food Anal. Methods 10(6), 1800–1816 (2017)Google Scholar
  19. 19.
    B. Hemmateenejad, J. Tashkhourian, M.M. Bordbar, N. Mobaraki, Development of colorimetric sensor array for discrimination of herbal medicine. J. Iran. Chem. Soc. 14(3), 595–604 (2017)Google Scholar
  20. 20.
    J.W. Gardner, Detection of vapours and odours from a multisensor array using pattern recognition Part 1. Principal component and cluster analysis. Sens. Actuators B 4(1–2), 109–115 (1991)Google Scholar
  21. 21.
    G. Jasinski, A. Strzelczyk, P. Koscinski, in Gas sampling system for matrix of semiconductor gas sensors. In IOP Conference Series: Materials Science and Engineering, Vol. 104, No. 1. (IOP Publishing, Bristol, 2006), p. 012033Google Scholar
  22. 22.
    A. Che Soh, K.K. Chow, M. Yusuf, U.K. Ishak, A.J. Hassan, M.K. and S. Khamis, Development of neural network-based electronic nose for herbs recognition. Int. J. Smart Sens. Intell. Syst. 7(2), 584–609 (2014)Google Scholar
  23. 23.
    K. Arshak, E. Moore, G.M. Lyons, J. Harris, S. Clifford, A review of gas sensors employed in electronic nose applications. Sens. Rev. 24(2), 181–198 (2004)Google Scholar
  24. 24.
    J. Yan, X. Guo, S. Duan, P. Jia, L. Wang, C. Peng, S. Zhang, Electronic nose feature extraction methods: a review. Sensors 15(11), 27804–27831 (2015)Google Scholar
  25. 25.
    F. Benrekia, M. Attari, M. Bouhedda, Gas sensors characterization and multilayer perceptron (MLP) hardware implementation for gas identification using a field programmable gate array (FPGA). Sensors 13(3), 2967–2985 (2013)Google Scholar
  26. 26.
    K.L. Goodner, J. Dreher, R.L. Rouseff, The dangers of creating false classifications due to noise in electronic nose and similar multivariate analyses. Sens. Actuators B 80(3), 261–266 (2001)Google Scholar
  27. 27.
    Q. Chen, J. Zhao, Z. Chen, H. Lin, D.-A. Zhao, Discrimination of green tea quality using the electronic nose technique and the human panel test, comparison of linear and nonlinear classification tools. Sens. Actuators B 159(1), 294–300 (2011)Google Scholar
  28. 28.
    N. Mobaraki, B. Hemmateenejad, Structural characterization of carbonyl compounds by IR spectroscopy and chemometrics data analysis. Chemometr. Intell. Lab. Syst. 109(2), 171–177 (2011)Google Scholar
  29. 29.
    S. Scott, D. James, Z. Ali, Data analysis for electronic nose systems. Microchim. Acta 156(3–4), 183–207 (2006)Google Scholar
  30. 30.
    Z. Haddi, S. Mabrouk, M. Bougrini, K. Tahri, K. Sghaier, H. Barhoumi, N.E. Bari, A. Maaref, N. Jaffrezic-Renault, B. Bouchikhi, E-Nose and e-Tongue combination for improved recognition of fruit juice samples. Food Chem. 150, 246–253 (2014)Google Scholar
  31. 31.
    M. Bougrini, K. Tahri, Z. Haddi, T. Saidi, N.E. Bari, B. Bouchikhi, Detection of adulteration in argan oil by using an electronic nose and a voltammetric electronic tongue. J. Sens. (2014).  https://doi.org/10.1155/2014/245831 Google Scholar
  32. 32.
    S. Buratti, S. Benedetti, M. Scampicchio, E.C. Pangerod, Characterization and classification of Italian Barbera wines by using an electronic nose and an amperometric electronic tongue. Anal. Chim. Acta 525(1), 133–139 (2004)Google Scholar
  33. 33.
    E. Borràs, J. Ferré, R. Boqué, M. Mestres, L. Aceña, O. Busto, Data fusion methodologies for food and beverage authentication and quality assessment—a review. Anal. Chim. Acta 891, 1–14 (2015)Google Scholar
  34. 34.
    A. Gorji-Chakespari, A.M. Nikbakht, F. Sefidkon, M. Ghasemi-Varnamkhasti, E.L. Valero, Classification of essential oil composition in Rosa damascena Mill. genotypes using an electronic nose. J. Appl. Res. Med. Aromat. Plants 4, 27–34 (2017)Google Scholar
  35. 35.
    A. Gorji-Chakespari, A.M. Nikbakht, F. Sefidkon, M. Ghasemi-Varnamkhasti, J. Brezmes, E. Llobet, Performance comparison of Fuzzy ARTMAP and LDA in qualitative classification of Iranian Rosa damascena essential oils by an electronic nose. Sensors 16(5), 636 (2016)Google Scholar
  36. 36.
    J. Jin, S. Deng, X. Ying, X. Ye, T. Lu, G. Hui, Study of herbal tea beverage discrimination method using electronic nose. J. Food Meas. Charact. 9(1), 52–60 (2015)Google Scholar
  37. 37.
    J. Jiaojiao, T. Xuxiang, C. Yanping, H. Yuanyuan, W. Minmin, Z. Haixia, H. Guohua, Optimization of eigenvalue selection in Chinese liquors discrimination based on electronic nose. J. Food Meas. Charact. 8(4), 270–276 (2014)Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Biosystems EngineeringShiraz UniversityShirazIran
  2. 2.Department of HorticultureShiraz UniversityShirazIran

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