Detection of adulteration in cherry tomato juices based on electronic nose and tongue: Comparison of different data fusion approaches

Journal of Food Engineering

Volumn 126, Issue , 2014, Pages 89-97

  Hong, Xuezhen ^a   Wang, Jun ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Adulteration; Cherry tomato juice; Data fusion; Electronic nose; Electronic tongue; Feature selection

Indexed keywords

DATA FUSION; DISCRIMINANT ANALYSIS; DRIERS (MATERIALS); ELECTRONIC TONGUES; FEATURE EXTRACTION; FRUITS; SUPPORT VECTOR MACHINES;

ADULTERATION; CANONICAL DISCRIMINANT ANALYSIS; CHERRY TOMATOES; CLASSIFICATION PERFORMANCE; ELECTRONIC NOSE; PRINCIPLE COMPONENT ANALYSIS; QUANTITATIVE CALIBRATIONS; SIMULTANEOUS UTILIZATION;

PRINCIPAL COMPONENT ANALYSIS;

LYCOPERSICON ESCULENTUM; LYCOPERSICON ESCULENTUM VAR. CERASIFORME;

EID: 84889686866     PISSN: 02608774     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfoodeng.2013.11.008     Document Type: Article

References (43)

1. Agriculture, U.D.o., 1997. United States standards for grades of fresh tomatoes.
2. I. Apetrei, M. Rodríguez-Méndez, C. Apetrei, I. Nevares, M. Del Alamo, and J. De Saja Monitoring of evolution during red wine aging in oak barrels and alternative method by means of an electronic panel test Food Research International 45 1 2012 244 249
3. E. Baldwin, J. Scott, M. Einstein, T. Malundo, B. Carr, R. Shewfelt, and K. Tandon Relationship between sensory and instrumental analysis for tomato flavor Journal of the American Society for Horticultural Science 123 5 1998 906 915 (Pubitemid 28382822)
4. M. Benady, J. Simon, D. Charles, and G. Miles Fruit ripeness determination by electronic sensing of aromatic volatiles Transactions of the ASAE 38 1 1995 251 257
5. L.A. Berrueta, R.M. Alonso-Salces, and K. Héberger Supervised pattern recognition in food analysis Journal of Chromatography-A 1158 1 2007 196 214 (Pubitemid 47021153)
6. K. Beullens, D. Kirsanov, J. Irudayaraj, A. Rudnitskaya, A. Legin, B.M. Nicolaï, and J. Lammertyn The electronic tongue and ATR-FTIR for rapid detection of sugars and acids in tomatoes Sensors and Actuators B: Chemical 116 1 2006 107 115 (Pubitemid 43766124)
7. K. Beullens, P. Mészáros, S. Vermeir, D. Kirsanov, A. Legin, S. Buysens, N. Cap, B.M. Nicolaï, and J. Lammertyn Analysis of tomato taste using two types of electronic tongues Sensors and Actuators B: Chemical 131 1 2008 10 17 (Pubitemid 351467744)
8. J. Brezmes, B. Ferreras, E. Llobet, X. Vilanova, and X. Correig Neural network based electronic nose for the classification of aromatic species Analytica Chimica Acta 348 1 1997 503 509 (Pubitemid 27397454)
9. K. Brudzewski, S. Osowski, and T. Markiewicz Classification of milk by means of an electronic nose and SVM neural network Sensors and Actuators B: Chemical 98 2 2004 291 298
10. S. Buratti, D. Ballabio, S. Benedetti, and M. Cosio Prediction of Italian red wine sensorial descriptors from electronic nose, electronic tongue and spectrophotometric measurements by means of Genetic Algorithm regression models Food Chemistry 100 1 2007 211 218
11. C.-C. Chang, and C.-J. Lin LIBSVM: a library for support vector machines ACM Transactions on Intelligent Systems and Technology (TIST) 2 3 2011 27
12. P. Ciosek, Z. Brzózka, and W. Wróblewski Classification of beverages using a reduced sensor array Sensors and Actuators B: Chemical 103 1 2004 76 83 (Pubitemid 40329189)
13. M. Cole, J.A. Covington, and J.W. Gardner Combined electronic nose and tongue for a flavour sensing system Sensors and Actuators B: Chemical 156 2 2011 832 839
14. M. Cosio, D. Ballabio, S. Benedetti, and C. Gigliotti Evaluation of different storage conditions of extra virgin olive oils with an innovative recognition tool built by means of electronic nose and electronic tongue Food Chemistry 101 2 2007 485 491 (Pubitemid 44333182)
15. L.M.J. De Carvalho, I.M. De Castro, and C.A.B. Da Silva A study of retention of sugars in the process of clarification of pineapple juice (Ananas comosus, L. Merril) by micro-and ultra-filtration Journal of Food Engineering 87 4 2008 447 454
16. S. Derksen, and H. Keselman Backward, forward and stepwise automated subset selection algorithms: frequency of obtaining authentic and noise variables British Journal of Mathematical and Statistical Psychology 45 2 1992 265 282
17. C. Di Natale, R. Paolesse, A. Macagnano, A. Mantini, A. D'Amico, A. Legin, L. Lvova, A. Rudnitskaya, and Y. Vlasov Electronic nose and electronic tongue integration for improved classification of clinical and food samples Sensors and Actuators B: Chemical 64 1 2000 15 21
18. L. Escuder-Gilabert, and M. Peris Review: highlights in recent applications of electronic tongues in food analysis Analytica Chimica Acta 665 1 2010 15 25
19. M. Faria, A. Magalhães, M. Nunes, and M. Oliveira High resolution melting of trnL amplicons in fruit juices authentication 2013 Food Control
20. E.R. Farnworth, R.C. Mckellar, D. Chabot, S. Lapointe, M. Chicoine, and K.P. Knight Use of an electronic nose to study the contribution of volatiles to orange juice flavor Journal of Food Quality 25 6 2002 569 576 (Pubitemid 36191798)
21. M. García, M. Aleixandre, J. Gutiérrez, and M. Horrillo Electronic nose for wine discrimination Sensors and Actuators B: Chemical 113 2 2006 911 916 (Pubitemid 43184139)
22. L. Gil-Sánchez, J. Soto, R. Martínez-Máñez, E. Garcia-Breijo, J. Ibáñez, and E. Llobet A novel humid electronic nose combined with an electronic tongue for assessing deterioration of wine Sensors and Actuators A: Physical 171 2 2011 152 158
23. E. Gobbi, M. Falasconi, I. Concina, G. Mantero, F. Bianchi, M. Mattarozzi, M. Musci, and G. Sberveglieri Electronic nose and Alicyclobacillus spp. spoilage of fruit juices: an emerging diagnostic tool Food Control 21 10 2010 1374 1382
24. A.H. Gomez, J. Wang, G. Hu, and A.G. Pereira Monitoring storage shelf life of tomato using electronic nose technique Journal of Food Engineering 85 4 2008 625 631 (Pubitemid 350051528)
25. X. Hong, J. Wang, and Z. Hai Discrimination and prediction of multiple beef freshness indexes based on electronic nose Sensors and Actuators B: Chemical 161 1 2012 381 389
26. K. Karlshøj, P.V. Nielsen, and T.O. Larsen Prediction of Penicillium expansum spoilage and patulin concentration in apples used for apple juice production by electronic nose analysis Journal of Agricultural and Food Chemistry 55 11 2007 4289 4298 (Pubitemid 46932621)
27. A. Legin, A. Rudnitskaya, Y. Vlasov, C. Di Natale, F. Davide, and A. D'Amico Tasting of beverages using an electronic tongue Sensors and Actuators B: Chemical 44 1 1997 291 296 (Pubitemid 127437386)
28. M. Liu, M.J. Wang, J. Wang, and D. Li Comparison of random forest, support vector machine and back propagation neural network for electronic tongue data classification: application to the recognition of orange beverage and Chinese vinegar Sensors and Actuators B: Chemical 177 2013 970 980
29. M. Masnan, N. Mahat, A. Zakaria, A. Shakaff, A. Adom, and F. Sa'ad Enhancing classification performance of multisensory data through extraction and selection of features Procedia Chemistry 6 2012 132 140
30. S. Oshita, K. Shima, T. Haruta, Y. Seo, Y. Kawagoe, S. Nakayama, and H. Takahara Discrimination of odors emanating from 'La France'pear by semi-conducting polymer sensors Computers and Electronics in Agriculture 26 2 2000 209 216 (Pubitemid 30181238)
31. V. Parra, Á.A. Arrieta, J.-A. Fernández-Escudero, M.L. Rodríguez-Méndez, and J.A. De Saja Electronic tongue based on chemically modified electrodes and voltammetry for the detection of adulterations in wines Sensors and Actuators B: Chemical 118 1 2006 448 453 (Pubitemid 44308410)
32. N. Prieto, M. Gay, S. Vidal, O. Aagaard, J. De Saja, and M. Rodriguez-Mendez Analysis of the influence of the type of closure in the organoleptic characteristics of a red wine by using an electronic panel Food Chemistry 129 2 2011 589 594
33. H. Reinhard, F. Sager, and O. Zoller Citrus juice classification by SPME-GC-MS and electronic nose measurements LWT-Food Science and Technology 41 10 2008 1906 1912
34. L. Rong, W. Ping, and H. Wenlei A novel method for wine analysis based on sensor fusion technique Sensors and Actuators B: Chemical 66 1 2000 246 250
35. S. Saevels, J. Lammertyn, A.Z. Berna, E.A. Veraverbeke, C. Di Natale, and B.M. Nicolaï Electronic nose as a non-destructive tool to evaluate the optimal harvest date of apples Postharvest Biology and Technology 30 1 2003 3 14 (Pubitemid 37365307)
36. T. Sugiyama, J. Sugiyama, M. Tsuta, K. Fujita, M. Shibata, M. Kokawa, and Y. Sagara NIR spectral imaging with discriminant analysis for detecting foreign materials among blueberries Journal of Food Engineering 101 3 2010 244 252
37. B. Tudu, L. Shaw, A. Jana, N. Bhattacharyya, and R. Bandyopadhyay Instrumental testing of tea by combining the responses of electronic nose and tongue Journal of Food Engineering 110 3 2012 356 363
38. C. Turner, A. Rudnitskaya, and A. Legin Monitoring batch fermentations with an electronic tongue Journal of Biotechnology 103 1 2003 87 91 (Pubitemid 36588893)
39. Z. Wei, and J. Wang Detection of antibiotic residues in bovine milk by a voltammetric electronic tongue system Analytica Chimica Acta 694 1 2011 46 56
40. Z. Wei, J. Wang, and W. Liao Technique potential for classification of honey by electronic tongue Journal of Food Engineering 94 3 2009 260 266
41. F. Winquist, I. Lundström, and P. Wide The combination of an electronic tongue and an electronic nose Sensors and Actuators B: Chemical 58 1 1999 512 517
42. A. Zakaria, A.Y.M. Shakaff, A.H. Adom, M. Ahmad, M.J. Masnan, A.H.A. Aziz, N.A. Fikri, A.H. Abdullah, and L.M. Kamarudin Improved classification of orthosiphon stamineus by data fusion of electronic nose and tongue sensors Sensors 10 10 2010 8782 8796
43. H. Zhang, M. Chang, J. Wang, and S. Ye Evaluation of peach quality indices using an electronic nose by MLR, QPST and BP network Sensors and Actuators B: Chemical 134 1 2008 332 338