EL USO DE NARIZ ELECTRÓNICA (e-nose) COMO HERRAMIENTA DE ANÁLISIS RÁPIDO DE ALIMENTOS
DOI:
https://doi.org/10.35172/rvz.2020.v27.524Palabras clave:
análisis de alimentos, método alternativo, nariz electrónica, sensoresResumen
La nariz electrónica es un equipo de análisis de olores que se utiliza en varias áreas, como el análisis de alimentos y el control ambiental. Su función es imitar la nariz humana a través de sensores que reaccionan con componentes volátiles y gases liberados de una muestra, dando como resultado la modificación de un circuito eléctrico que es interpretado por software. Su uso en el análisis de alimentos es prometedor debido a su facilidad de manejo, bajo costo y rapidez, lo que indica beneficios para la rutina industrial y de laboratorio. Su aplicabilidad abarca la detección de fraudes, deterioro, contaminación y sabores/olores, permitiendo la evaluación de la calidad de diversos productos, además de discriminar patógenos y deteriorantes alimentarios. Aunque prometedor, esta tecnología se consideró nueva y requirió estudios más profundos para que sea ampliamente utilizada en la rutina del análisis de alimentos. Por lo tanto, el objetivo de este estudio es proporcionar una revisión de la literatura relacionada con la aplicabilidad de la e-nose en el análisis de alimentos.
Citas
1. de Melo Lisboa H, Page T, Guy C. Gestão de odores: Fundamentos do nariz eletrônico. Eng Sanit e Ambient. 2009;14(1):9–18.
2. Loutfi A, Coradeschi S, Mani GK, Shankar P, Rayappan JBB. Electronic noses for food quality: A review. J Food Eng. 2015;144:103–11.
3. Ghasemi-Varnamkhasti M, Mohtasebi SS, Siadat M, Balasubramanian S. Meat quality assessment by electronic nose (Machine Olfaction Technology). Sensors. 2009;9(8):6058–83.
4. Wang Q, Li L, Ding W, Zhang D, Wang J, Reed K, et al. Adulterant identification in mutton by electronic nose and gas chromatography-mass spectrometer. Food Control. 2019;98(November 2018):431–8.
5. Firestein S. How the olfactory system makes sense of scents. Nature [Internet]. 2001;413(6852):211–8.
6. Netto MMO, Gonçalves WB, Li RWC, Gruber J. Biopolymer based ionogels as active layers in low-cost gas sensors for electronic noses. Sensors Actuators, B Chem. 2020;315(November 2019):128025.
7. NASA. Electronic Nose: NASA researchers are developing an exquisitely sensitive artificial nose for space exploration. [Internet]. [cited 2020 Jun 6]. Available from: https://science.nasa.gov/science-news/science-at-nasa/2004/06oct_enose
8. NASA. An Introduction to JPL’s ENose [Internet]. [cited 2020 Jun 6]. Available from: https://enose.jpl.nasa.gov/
9. Schaller E, Bosset JO, Escher F. “Electronic noses” and their application to food. LWT - Food Sci Technol. 1998;31(4):305–16.
10. Di Francesco F, Lazzerini B, Marcelloni F, Pioggia G. An electronic nose for odour annoyance assessment. Atmos Environ. 2001;35(7):1225–34.
11. Gostelow P, Parsons SA, Stuetz RM. Odour measurements for sewage treatment works. Water Res. 2001;35(3):579–97.
12. Sohn JH, Smith RJ, Yoong E. Process studies of odour emissions from effluent ponds using machine-based odour measurement. Atmos Environ. 2006;40(7):1230–41.
13. Wilson AD. Review of Electronic-nose Technologies and Algorithms to Detect Hazardous Chemicals in the Environment. Procedia Technol. 2012;1:453–63.
14. Arroyo T, Lozano J, Cabellos JM, Gil-Diaz M, Santos JP, Horrillo C. Evaluation of wine aromatic compounds by a sensory human panel and an electronic nose. J Agric Food Chem. 2009;57(24):11543–9.
15. Prieto N, Rodriguez-Méndez ML, Leardi R, Oliveri P, Hernando-Esquisabel D, Iñiguez-Crespo M, et al. Application of multi-way analysis to UV-visible spectroscopy, gas chromatography and electronic nose data for wine ageing evaluation. Anal Chim Acta. 2012;719:43–51.
16. Berna AZ, Trowell S, Clifford D, Cynkar W, Cozzolino D. Geographical origin of Sauvignon Blanc wines predicted by mass spectrometry and metal oxide based electronic nose. Anal Chim Acta. 2009;648(2):146–52.
17. Dutta R, Hines EL, Gardner JW, Kashwan KR, Bhuyan M. Tea quality prediction using a tin oxide-based electronic nose: An artificial intelligence approach. Sensors Actuators, B Chem. 2003;94(2):228–37.
18. Bhattacharyya N, Bandyopadhyay R, Bhuyan M, Tudu B, Ghosh D, Jana A. Electronic nose for black tea classification and correlation of measurements with “Tea taster” marks. IEEE Trans Instrum Meas. 2008;57(7):1313–21.
19. Nurjuliana M, Che Man YB, Mat Hashim D, Mohamed AKS. Rapid identification of pork for halal authentication using the electronic nose and gas chromatography mass spectrometer with headspace analyzer. Meat Sci. 2011;88(4):638–44.
20. El Barbri N, Llobet E, El Bari N, Correig X, Bouchikhi B. Electronic nose based on metal oxide semiconductor sensors as an alternative technique for the spoilage classification of red meat. Sensors. 2008;8(1):142–56.
21. Winquist F, Hornsten EG, Sundgren H, Lundstrom I. Performance of an electronic nose for quality estimation of ground meat. Meas Sci Technol. 1993;4(12):1493–500.
22. Yano Y, Yokoyama K, Tamiya E, Karube I. Direct evaluation of meat spoilage and the progress of aging using biosensors. Anal Chim Acta. 1996;320(2–3):269–76.
23. Olsen E, Vogt G, Ekeberg D, Sandbakk M, Pettersen J, Nilsson A. Analysis of the early stages of lipid oxidation in freeze-stored pork back fat and mechanically recovered poultry meat. J Agric Food Chem. 2005;53(2):338–48.
24. Miao H, Liu Q, Bao H, Wang X, Miao S. Effects of different freshness on the quality of cooked tuna steak. Innov Food Sci Emerg Technol [Internet]. 2017;44:67–73.
25. GholamHosseini H, Luo D, Liu H, Xu G. Intelligent processing of e-nose information for fish freshness assessment. Proc 2007 Int Conf Intell Sensors, Sens Networks Inf Process ISSNIP. 2007;173–7.
26. Gholam Hosseini H, Luo D, Xu G, Liu H, Benjamin D. Intelligent Fish Freshness Assessment. J Sensors. 2008;2008:1–8.
27. Eriksson Å, Waller KP, Svennersten-Sjaunja K, Haugen JE, Lundby F, Lind O. Detection of mastitic milk using a gas-sensor array system (electronic nose). Int Dairy J. 2005;15(12):1193–201.
28. Balasubramanian S, Panigrahi S, Logue CM, Marchello M, Sherwood JS. Identification of Salmonella-inoculated beef using a portable electronic nose system. J Rapid Methods Autom Microbiol. 2005;13(2):71–95.
29. Younts S, Alocilja EC, Osburn WN, Marquie S, Grooms DL. Differentiation of Escherichia coli 0157:H7 from non–0157:H7 E. coli serotypes using a gas sensor–based, computer–controlled detection system. Trans ASAE. 2002;45(5):1681–5.
30. Pereira JG, Gonçalves WB, Teixeira WSR, Sampaio ANCE, Mioni M R, Martins AO, Megid J, Gruber J. Fast detection of foodborne pathogens: an interdisciplinary approach. In: 30o Congresso Brasileiro de Microbiologia; 2019, Maceió; 2019.
31. Pereira JG, Gonçalves WB, Teixeira WSR, Sampaio ANCE, Mioni M R, Martins AO, Megid J, Gruber J. Electronic nose based on ionogel doped with Fe3O4 particles applied for discrimination of spoilage and pathogenic microorganisms in raw meats. In: 30o Congresso Brasileiro de Microbiologia; 2019, Maceió; 2019.
32. Keshri G, Magan N, Voysey P. Use of an electronic nose for the early detection and differentiation between spoilage fungi. Lett Appl Microbiol. 1998;27(5):261–4.
33. Gardner JW, Craven M, Dow C, Hines EL. The prediction of bacteria type and culture growth phase by an electronic nose with a multi-layer perceptron network. Meas Sci Technol. 1998;9(1):120–7.
34. Elliott-Martin RJ, Mottram TT, Gardner JW, Hobbs PJ, Bartlett PN. Preliminary investigation of breath sampling as a monitor of health in dairy cattle. J Agric Eng Res. 1997;67(4):267–75.
35. Medelius PJ. Nano sensors for gas detection in space and ground support applications. Proc MNT Aerosp Appl CANEUS2006. 2006;2006:1–5.
2. Loutfi A, Coradeschi S, Mani GK, Shankar P, Rayappan JBB. Electronic noses for food quality: A review. J Food Eng. 2015;144:103–11.
3. Ghasemi-Varnamkhasti M, Mohtasebi SS, Siadat M, Balasubramanian S. Meat quality assessment by electronic nose (Machine Olfaction Technology). Sensors. 2009;9(8):6058–83.
4. Wang Q, Li L, Ding W, Zhang D, Wang J, Reed K, et al. Adulterant identification in mutton by electronic nose and gas chromatography-mass spectrometer. Food Control. 2019;98(November 2018):431–8.
5. Firestein S. How the olfactory system makes sense of scents. Nature [Internet]. 2001;413(6852):211–8.
6. Netto MMO, Gonçalves WB, Li RWC, Gruber J. Biopolymer based ionogels as active layers in low-cost gas sensors for electronic noses. Sensors Actuators, B Chem. 2020;315(November 2019):128025.
7. NASA. Electronic Nose: NASA researchers are developing an exquisitely sensitive artificial nose for space exploration. [Internet]. [cited 2020 Jun 6]. Available from: https://science.nasa.gov/science-news/science-at-nasa/2004/06oct_enose
8. NASA. An Introduction to JPL’s ENose [Internet]. [cited 2020 Jun 6]. Available from: https://enose.jpl.nasa.gov/
9. Schaller E, Bosset JO, Escher F. “Electronic noses” and their application to food. LWT - Food Sci Technol. 1998;31(4):305–16.
10. Di Francesco F, Lazzerini B, Marcelloni F, Pioggia G. An electronic nose for odour annoyance assessment. Atmos Environ. 2001;35(7):1225–34.
11. Gostelow P, Parsons SA, Stuetz RM. Odour measurements for sewage treatment works. Water Res. 2001;35(3):579–97.
12. Sohn JH, Smith RJ, Yoong E. Process studies of odour emissions from effluent ponds using machine-based odour measurement. Atmos Environ. 2006;40(7):1230–41.
13. Wilson AD. Review of Electronic-nose Technologies and Algorithms to Detect Hazardous Chemicals in the Environment. Procedia Technol. 2012;1:453–63.
14. Arroyo T, Lozano J, Cabellos JM, Gil-Diaz M, Santos JP, Horrillo C. Evaluation of wine aromatic compounds by a sensory human panel and an electronic nose. J Agric Food Chem. 2009;57(24):11543–9.
15. Prieto N, Rodriguez-Méndez ML, Leardi R, Oliveri P, Hernando-Esquisabel D, Iñiguez-Crespo M, et al. Application of multi-way analysis to UV-visible spectroscopy, gas chromatography and electronic nose data for wine ageing evaluation. Anal Chim Acta. 2012;719:43–51.
16. Berna AZ, Trowell S, Clifford D, Cynkar W, Cozzolino D. Geographical origin of Sauvignon Blanc wines predicted by mass spectrometry and metal oxide based electronic nose. Anal Chim Acta. 2009;648(2):146–52.
17. Dutta R, Hines EL, Gardner JW, Kashwan KR, Bhuyan M. Tea quality prediction using a tin oxide-based electronic nose: An artificial intelligence approach. Sensors Actuators, B Chem. 2003;94(2):228–37.
18. Bhattacharyya N, Bandyopadhyay R, Bhuyan M, Tudu B, Ghosh D, Jana A. Electronic nose for black tea classification and correlation of measurements with “Tea taster” marks. IEEE Trans Instrum Meas. 2008;57(7):1313–21.
19. Nurjuliana M, Che Man YB, Mat Hashim D, Mohamed AKS. Rapid identification of pork for halal authentication using the electronic nose and gas chromatography mass spectrometer with headspace analyzer. Meat Sci. 2011;88(4):638–44.
20. El Barbri N, Llobet E, El Bari N, Correig X, Bouchikhi B. Electronic nose based on metal oxide semiconductor sensors as an alternative technique for the spoilage classification of red meat. Sensors. 2008;8(1):142–56.
21. Winquist F, Hornsten EG, Sundgren H, Lundstrom I. Performance of an electronic nose for quality estimation of ground meat. Meas Sci Technol. 1993;4(12):1493–500.
22. Yano Y, Yokoyama K, Tamiya E, Karube I. Direct evaluation of meat spoilage and the progress of aging using biosensors. Anal Chim Acta. 1996;320(2–3):269–76.
23. Olsen E, Vogt G, Ekeberg D, Sandbakk M, Pettersen J, Nilsson A. Analysis of the early stages of lipid oxidation in freeze-stored pork back fat and mechanically recovered poultry meat. J Agric Food Chem. 2005;53(2):338–48.
24. Miao H, Liu Q, Bao H, Wang X, Miao S. Effects of different freshness on the quality of cooked tuna steak. Innov Food Sci Emerg Technol [Internet]. 2017;44:67–73.
25. GholamHosseini H, Luo D, Liu H, Xu G. Intelligent processing of e-nose information for fish freshness assessment. Proc 2007 Int Conf Intell Sensors, Sens Networks Inf Process ISSNIP. 2007;173–7.
26. Gholam Hosseini H, Luo D, Xu G, Liu H, Benjamin D. Intelligent Fish Freshness Assessment. J Sensors. 2008;2008:1–8.
27. Eriksson Å, Waller KP, Svennersten-Sjaunja K, Haugen JE, Lundby F, Lind O. Detection of mastitic milk using a gas-sensor array system (electronic nose). Int Dairy J. 2005;15(12):1193–201.
28. Balasubramanian S, Panigrahi S, Logue CM, Marchello M, Sherwood JS. Identification of Salmonella-inoculated beef using a portable electronic nose system. J Rapid Methods Autom Microbiol. 2005;13(2):71–95.
29. Younts S, Alocilja EC, Osburn WN, Marquie S, Grooms DL. Differentiation of Escherichia coli 0157:H7 from non–0157:H7 E. coli serotypes using a gas sensor–based, computer–controlled detection system. Trans ASAE. 2002;45(5):1681–5.
30. Pereira JG, Gonçalves WB, Teixeira WSR, Sampaio ANCE, Mioni M R, Martins AO, Megid J, Gruber J. Fast detection of foodborne pathogens: an interdisciplinary approach. In: 30o Congresso Brasileiro de Microbiologia; 2019, Maceió; 2019.
31. Pereira JG, Gonçalves WB, Teixeira WSR, Sampaio ANCE, Mioni M R, Martins AO, Megid J, Gruber J. Electronic nose based on ionogel doped with Fe3O4 particles applied for discrimination of spoilage and pathogenic microorganisms in raw meats. In: 30o Congresso Brasileiro de Microbiologia; 2019, Maceió; 2019.
32. Keshri G, Magan N, Voysey P. Use of an electronic nose for the early detection and differentiation between spoilage fungi. Lett Appl Microbiol. 1998;27(5):261–4.
33. Gardner JW, Craven M, Dow C, Hines EL. The prediction of bacteria type and culture growth phase by an electronic nose with a multi-layer perceptron network. Meas Sci Technol. 1998;9(1):120–7.
34. Elliott-Martin RJ, Mottram TT, Gardner JW, Hobbs PJ, Bartlett PN. Preliminary investigation of breath sampling as a monitor of health in dairy cattle. J Agric Eng Res. 1997;67(4):267–75.
35. Medelius PJ. Nano sensors for gas detection in space and ground support applications. Proc MNT Aerosp Appl CANEUS2006. 2006;2006:1–5.
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2020-12-06
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Nunes de Moraes G, Pereira JG. EL USO DE NARIZ ELECTRÓNICA (e-nose) COMO HERRAMIENTA DE ANÁLISIS RÁPIDO DE ALIMENTOS. RVZ [Internet]. 6 de diciembre de 2020 [citado 21 de noviembre de 2024];27:1-10. Disponible en: https://rvz.emnuvens.com.br/rvz/article/view/524
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