Technique potential for classification of honey by electronic tongue

Journal of Food Engineering

Volumn 94, Issue 3-4, 2009, Pages 260-266

  Wei, Zhenbo ^a   Wang, Jun ^a   Liao, Wenyan ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Artificial neural network; Cluster analysis; Electronic tongue; Honey; Principal component analysis

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ELECTRONIC TONGUE; FEATURE EXTRACTION METHODS; GEOGRAPHICAL ORIGINS; HONEY; PATTERN RECOGNITION TECHNIQUES; SOLUBLE SUGARS;

BACKPROPAGATION; CLUSTER ANALYSIS; FEATURE EXTRACTION; NEURAL NETWORKS; SUGAR (SUCROSE); SUGARS;

PRINCIPAL COMPONENT ANALYSIS;

ACACIA;

EID: 67349273777     PISSN: 02608774     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfoodeng.2009.03.016     Document Type: Article

References (27)

1. Abdul A.S., Sim M.M., Shakaff A.Y.M., Ahmad M.N., Dahari Z., Ismail Z., and Hitam M.S. A microcontroller-based taste sensing system for the verification of Eurycoma longifolia. Sensors and Actuators B 101 (2004) 191-198
2. Andre H. On the number of clusters. Computational Statistics and Data Analysis 23 (1996) 83-96
3. Anklam E. A review of the analytical methods to determine the geographical and botanical origin of honey. Food Chemistry 63 (1998) 549-562
4. Azeredo L., Da C., Azeredo M.A.A., De S.R., and Dutra V.M.L. Protein contents and physicochemical properties in honey samples of Apis mellifera of different floral origins. Food Chemistry 80 (2003) 249-254
5. Beullens K., Meszaros P., Vermeir S., Kirsanov D., Legin A., Buysens S., Capd N., NicolaI B.M., and Lammertyn J. Analysis of tomato taste using two types of electronic tongues. Sensors and Actuators B 131 (2008) 10-17
6. Bishop C.M. Neural Networks for Pattern Recognition (1995), Oxford University Press, Oxford (482p)
7. Calinski T., and Harabasz J. A dendrite method for cluster analysis. Communications in Statistics 3 (1974) 1-27
8. Calvo D., Dur A.A., and Del V.M. Use of pulse transient response as input information for an automated SIA electronic tongue. Sensors and Actuators B 131 (2008) 77-84
9. Chinese D., and Meneghetti A. Energy analysis in industrial districts: a statistics-based approach. International Journal of Global Energy Issues 21 (2004) 315-328
10. Ciosek P., Brzózka Z., and Wróblewski W. Classification of beverages using a reduced sensor array. Sensors and Actuators B 103 (2004) 76-83
11. Cortina M., Ecker C., Calvo D., and Del V.M. Automated electronic tongue based on potentiometric sensors for the determination of a trinary anionic surfactant mixture. Journal of Pharmaceutical and Biomedical Analysis 46 (2008) 213-218
12. Devillers J., Morlot M., Pham M.H., and Dor J.C. Classification of monofloral honeys based on their quality control data. Food Chemistry 86 (2004) 305-312
13. Gil L., Barat K., and Jose M. Fish freshness analysis using metallic potentiometric electrodes. Sensors and Actuators B 131 (2008) 362-370
14. Guti M., Alegret S., and Del V.M. Potentiometric bioelectronic tongue for the analysis of urea and alkaline ions in clinical samples. Biosensors and Bioelectronics 22 (2007) 2171-2178
15. Haykin S. Neural Networks, A Comprehensive Foundation. Englewood Cliffs (1999), Prentice Hall, New Jersey, USA 696p
16. Hernandez O.M., Fraga J.M.G., Jimenez A.I., Jimenez F., and Arias J.J. Characterization of honey from the Canary Islands: determination of the mineral content by atomic absorption spectrophotometry. Food Chemistry 93 (2005) 449-458
17. Kulapina E.G., and Mikhaleva N.M. The analysis of multicomponent solutions containing homologous ionic surfactant with sensor arrays. Sensors and Actuators B 106 (2005) 271-277
18. Legin A., Rudnitskaya A., Vlasov Y., Di Natale C., Mazzone E., and Damico A. Application of electronic tongue for qualitative and quantitative analysis of complex liquid media. Sensors and Actuators B 65 (2000) 232-234
19. Manly B.F.J. Multivariate Statistical Methods - A Primer. second ed. (1994), Chapman and Hall, London 129-133
20. Marini F., Magri{dotless} A.L., Balestrieri F., Fabretti F., and Marini D. Supervised pattern recognition applied to the discrimination of the floral origin of six types of Italian honey samples. Analytica Chimica Acta 515 (2004) 117-125
21. McKenna J.E. An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis. Environmental Modelling and Software 18 (2003) 205-220
22. Mottram T., Rudnitskaya A., Legin A., Fitzpatrick JulieL., and Eckersall P. Evaluation of a novel chemical sensor system to detect clinical mastitis in bovine milk. Biosensors and Bioelectronics 22 (2007) 2689-2693
23. Pisani A., Protano G., and Riccobono F. Minor and trace elements in different honey types produced in Siena County (Italy). Food Chemistry 107 (2008) 1553-1560
24. Radovica B.S., Goodacre R., and Anklam E. Contribution of pyrolysis-mass spectrometry (Py-MS) to authenticity testing of honey. Journal of Analytical and Applied Pyrolysis 60 (2001) 79-87
25. Tian S.Y., Deng S.P., and Chen Z.X. Multifrequency large amplitude pulse voltammetry: a novel electrochemical method for electronic tongue. Sensors and Actuators B 123 (2007) 1049-1056
26. Toko K. Electronic tongue. Biosensors and Bioelectronics 13 (1998) 701-709
27. Wold S., Esbensen K., and Geladi P. Principal component analysis - a tutorial. Chemometrics and Intelligent Laboratory Systems 2 (1987) 37-52