VZL 2008, 77(2):66-70

Artificial Noses in Detection of Moulds and Mycotoxins

Vlastimil Dohnal1,2,3, Andrea Sládková1, Kamil Kuča ORCID...2,4, Daniel Jun ORCID...2,4
1 Mendelova zemědělská a lesnická univerzita v Brně, Ústav technologie potravin, Agronomická fakulta, Brno
2 Univerzita obrany, katedra toxikologie Fakulty vojenského zdravotnictví, Hradec Králové
3 Univerzita J. E. Purkyně, katedra chemie Přírodovědecké fakulty, Ústí nad Labem
4 Univerzita obrany, Centrum pokročilých studií Fakulty vojenského zdravotnictví, Hradec Králové

V současné době patří produkce zdravotně nezávadných potravin mezi priority každého vyspělého státu. Odhaduje se, že více než 25 % celosvětové produkce potravinářských plodin je zlikvidováno v důsledku napadení fusáriovými plísněmi. Kontaminace rostlinného materiálu (krmiv, potravin) toxinogenními houbami je nebezpečná z několika hledisek. Jednak mohou houby vytvářet dráždivé těkavé metabolity, toxické látky nebo spóry vyvolávající u některých citlivějších jedinců alergii. Napadené potraviny či krmiva mívají zpravidla nižší nutriční hodnotu a dochází u nich například ke snižování obsahu využitelných bílkovin a sacharidů. Produkce mykotoxinů však patří mezi nejzávažnější důsledky fungálního znečištění. Jednou z možností rychlé detekce fungální kontaminace potravin jsou i umělé nosy.

Keywords: Mykotoxiny; Plísně; Umělý nos; Umělé neuronové sítě

The production of safety food is the priority of developed countries. More than 25 % of worldwide production of cereals is contaminated with Fusarium fungi. Spoiled food/feed has a lower nutritional quality and also negative health effects. Fungi produce irritating volatile compounds, toxic compounds (mycotoxins) and allergizing spores. The most important metabolites from the toxicological point of view are mycotoxins. Several analytical methods are used for the detection of moulds in food/feed, urban dust or environmental samples. One of the most perspective methods is artificial nose which combines measurement using sensor array and signal evaluation using chemometrical methods, for example artificial neural networks.

Keywords: Mycotoxins; Fungi; Artificial nose; Artificial neural networks

Received: November 9, 2007; Published: June 1, 2008  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Dohnal, V., Sládková, A., Kuča, K., & Jun, D. (2008). Artificial Noses in Detection of Moulds and Mycotoxins. Vojenské Zdravotnické Listy, 77(2), 66-70
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. ABRAMSON, D., et al. Mycotoxins, ergosterol, and odor volatiles in durum wheat during granary storage at 16% and 20% moisture content. J. Stored Products Research, 2005, vol. 41, no. 1, p. 67-76. Go to original source...
    2. AISHIMA, T. Correlating sensory attributes to gas chromatography-mass spectrometry profiles and e-nose responses using partial least squares regression analysis. J. Chromatogr. A, 2004, vol. 1054, p. 36-46. Go to original source...
    3. AMPUERO, S. - BOSSET, JO. The electronic nose applied to dairy products: a review. Sensors and Actuators B: Chemica, 2003, vol. 94, no. 1, p. 1-12. Go to original source...
    4. BALASUBRAMANIAN, S., et al. Evaluation of an artificial olfactory system for grain quality discrimination. LWT - Food Science and Technology, 2007, vol. 40, no. 10, p. 1815-1825. Go to original source...
    5. BOGER, Z. Selection of quasi-optimal inputs in chemometrics modeling by artificial neural network analysis. Analytica Chimica Acta, 2003, vol. 490, no. 1/2, p. 31-40. Go to original source...
    6. BORJESSON, T. - STOLLMAN, U. - SCHNURER, J. Volatile metabolites produced by six fungal species compared with other indicators of fungal growth on cereal grains. Appl. Environ. Microbiol., 1992, vol. 58, p. 2599-2605. Go to original source... Go to PubMed...
    7. BORJESSON, T. Volatile fungal metabolites as indicators of mould growth in stored cereals. Dissertation, Uppsala, Swedish University of Agricultural Sciences, 1993, p. 44.
    8. CRESPO, R., et al. Volatile organic compounds released by the entomopathogenic fungus Beauveria bassiana. Microbiol. Res., in print.
    9. DOHNAL, V. - KUČA, K. - JUN, D. Metody umělé inteligence: Nový trend ve farmacii. Česká a slovenská farmacie, 2005a, roč. 54, č. 4, s. 163-167. Go to PubMed...
    10. DOHNAL, V. - KUČA, K. - JUN, D. What are artificial neural networks and what they can do? Biomed. Pap., 2005b, vol. 149, no. 2, p. 221-224. Go to original source... Go to PubMed...
    11. DOHNAL, V., et al. Quantitative analysis of chiral compounds from unresolved peaks in capillary electrophoresis using multivariate calibration with experimental design and artificial neural networks. Chirality, 2002, vol. 14, p. 509-518. Go to original source... Go to PubMed...
    12. HAUGEN, JE. - KVAAL, K. Electronic nose and artificial neural network. Meat Science, 1998, vol. 49, Supp. 1, p. S273-S286. Go to original source...
    13. JELEN, HH., et al. Production of volatile sesquiterpenes by Fusarium sambucinum strains with different abilities to synthesize trichothecens. Appl. Environ. Microbiol., 1995, vol. 61, p. 3815-3820. Go to original source... Go to PubMed...
    14. JONSON, A., et al. Electronic nose for microbial quality classification of grains. Int. J. Food Microbiol., 1997, vol. 35, p. 187-193. Go to original source... Go to PubMed...
    15. LARSEN, TO. - FRISVALD, JC. Characterisation of volatile metabolites from 47 Penicillium taxa. Mycol. Res., 1995, vol. 99, p. 1153-1166. Go to original source...
    16. LUNDSTROM, I., et al. From hydrogen sensors to olfactory images - twenty years with catalytic field-effect devices. Sensors Actuators B, 1993, p. 13-14; 16-23. Go to original source...
    17. MAGAN, N. - EVANS, P. Volatiles as an indicator of fungal activity and differentiation between species, and the potential use of electronic nose technology for early detection of grain spoilage. Journal of Stored Products Research, 2000, vol. 36, no. 4, p. 319-340. Go to original source... Go to PubMed...
    18. OLSSON, J., et al. Volatiles for mycological quality grading of barley: determination using gas chromatography-mass spectrometry and electronic nose. Int. J. Food Microbiol., 2000, vol. 59, p. 167-178. Go to original source... Go to PubMed...
    19. OLSSON, J., et al. Detection and quantification of ochratoxin A and deoxynivalenol in barley grains by GC-MS and electronic nose. Int. J. Food Microbiol., 2002, vol. 72, p. 203-214. Go to original source... Go to PubMed...
    20. PEARCE, TC. Computational parallels between the biological olfactory pathway and its analogue "The Electronic Nose": Part II. Sensor-based machine olfaction. Biosystems, 1997, vol. 41, no. 2, p. 69-90. Go to original source... Go to PubMed...
    21. SOLIS, JL., et al. Identifying natural and artificial odours through noise analysis with a sampling-and-hold electronic nose. Sensors and Actuators B, 2001, vol. 77, p. 312-315. Go to original source...
    22. SCHNURER, J. - OLSSON, J. - BORJESSON, T. Fungal volatiles as indicator of food and feeds spoilage. Fungal Genetics and Biology, 1999, vol. 27, p. 209-217. Go to original source... Go to PubMed...
    23. SMITH, EA. - CHAMBERS, IV E. - COLLEY, S. Development of vocabulary and references for describing off-odours in raw grains. Cereal Foods World, 1994, vol. 39, p. 495-499.
    24. SNOPOK, BA. - KRUGLENKO, IV. Multisensor systems for chemical analysis: state-of-the-art in Electronic Nose technology and new trends in machine olfaction. Thin Solid Films, 2002, vol. 418, no. 1, p. 21-41. Go to original source...
    25. WALINDER, R. - NORBACK, D. - JOHANSSON, G. Pulmonary reactions after exposure to 3-methylfuran vapour, a fungal metabolite. Int. J. Tubercul. Lung Dis., 1998, vol. 2, p. 1037-1039.
    26. WINQUIST, F., et al. Performance of an electronic nose for quality estimation of ground meat. Meas. Sci. Technol., 1993, vol. 4, p. 1493-1500. Go to original source...
    27. ZERINQUE, HJ. - BHATNAGAR, D. - CLEVELAND, TE. C15H24 volatile compounds unique to aflatoxigenic strains of Aspergillus flavus. Appl. Environ. Microbiol., 1993, vol. 59, p. 2264-2270. Go to original source... Go to PubMed...

    Return to the content