Classification and regression of ELM, LVQ and SVM for E-nose data of strawberry juice

Journal of Food Engineering

Volumn 144, Issue , 2014, Pages 77-85

  Qiu, Shanshan ^a   Gao, Liping ^a   Wang, Jun ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Classification; Electronic nose; Extreme Learning Machine; Pretreatments; Regression; Strawberry juice

Indexed keywords

BEVERAGES; CLASSIFICATION (OF INFORMATION); FRUITS; KNOWLEDGE ACQUISITION; LEAST SQUARES APPROXIMATIONS; LINEAR REGRESSION; PASTEURIZATION; SUPPORT VECTOR MACHINES; VECTOR QUANTIZATION;

ELECTRONIC NOSE; EXTREME LEARNING MACHINE; PRE-TREATMENTS; REGRESSION; STRAWBERRY JUICE;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84906316865     PISSN: 02608774     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfoodeng.2014.07.015     Document Type: Article

References (50)

1. K. Aaby, S. Mazur, A. Nes, and G. Skrede Phenolic compounds in strawberry (Fragaria x ananassa, Duch.) fruits: composition in 27 cultivars and changes during ripening Food Chem. 132 1 2012 86 97
2. S. Aguilar-Rosas, M. Ballinas-Casarrubias, G. Nevarez-Moorillon, O. Martin-Belloso, and E. Ortega-Rivas Thermal and pulsed electric fields pasteurization of apple juice: effects on physicochemical properties and flavour compounds J. Food Eng. 83 1 2007 41 46 (Pubitemid 46802874)
3. D.d. Ancos, M.P. Cano, A. Hernandez, and M. Monreal Effects of microwave heating on pigment composition and colour of fruit purees J. Sci. Food Agric. 79 5 1999 663 670 (Pubitemid 29194480)
4. K.S. Bahçeci, A. Serpen, V. Gökmen, and J. Acar Study of lipoxygenase and peroxidase as indicator enzymes in green beans: change of enzyme activity, ascorbic acid and chlorophylls during frozen storage J. Food Eng. 66 2 2005 187 192
5. R.N. Banerjee, B. Tudu, L. Shaw, A. Jana, N. Bhattacharyya, and R. Bandyopadhyay Instrumental testing of tea by combining the responses of electronic nose and tongue J. Food Eng. 110 3 2012 356 363
6. A.Z. Berna, J. Lammertyn, S. Saevels, C.D. Natale, and B.M. Nicolaï Electronic nose systems to study shelf life and cultivar effect on tomato aroma profile Sens. Actuators, B 97 2 2004 324 333
7. J. Brezmes, E. Llobet, X. Vilanova, J. Orts, G. Saiz, and X. Correig Correlation between electronic nose signals and fruit quality indicators on shelf-life measurements with pinklady apples Sens. Actuators, B 80 1 2001 41 50 (Pubitemid 32933860)
8. K. Brudzewski, S. Osowski, and T. Markiewicz Classification of milk by means of an electronic nose and SVM neural network Sens. Actuators, B 98 2 2004 291 298
9. C.-C. Chang, and C.-J. Lin LIBSVM: a library for support vector machines ACM Trans Intell. Syst. Technol. (TIST) 2 3 2011 27
10. L. Chen, and G. Dai The influence on the preservation rate of vitamin C with different measures in the process of strawberry juice Food Res. Dev. 2 28 2007 115 117
11. K. Choi, K.-A. Toh, and H. Byun Incremental face recognition for large-scale social network services Pattern Recogn. 45 8 2012 2868 2883
12. C. Cortes, and V. Vapnik Support-vector networks Mach. Learning 20 3 1995 273 297
13. R. Cruz, M.C. Vieira, and C.L. Silva Effect of heat and thermosonication treatments on watercress (Nasturtium officinale) vitamin C degradation kinetics Innovative Food Sci. Emerg. Technol. 9 4 2008 483 488
14. L. Dias, A.M. Peres, T.P. Barcelos, J. Sá Morais, and A.A. Machado Semi-quantitative and quantitative analysis of soft drinks using an electronic tongue Sens. Actuators, B 154 2 2011 111 118
15. GB 6195-86, 1986. Determination of vitamin C in vegetables and fruits (2,6-dichloro-indophenol titration method). Standard of the People's Republic of China.
16. GB/T 12456-2008, 2008. Determination of total acid in foods. National Standard of the People's Republic of China.
17. 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
18. A.H. Gomez, J. Wang, G. Hu, and A.G. Pereira Monitoring storage shelf life of tomato using electronic nose technique J. Food Eng. 85 4 2008 625 631 (Pubitemid 350051528)
19. P. Hartyáni, I. Dalmadi, and D. Knorr Electronic nose investigation of Alicyclobacillus acidoterrestris inoculated apple and orange juice treated by high hydrostatic pressure Food Control 1 32 2013 262 269
20. D.M. Holcroft, and A.A. Kader Controlled atmosphere-induced changes in pH and organic acid metabolism may affect color of stored strawberry fruit Postharvest Biol. Technol. 17 1 1999 19 32 (Pubitemid 29456305)
21. M. Holzwarth, S. Korhummel, R. Carle, and D.R. Kammerer Evaluation of the effects of different freezing and thawing methods on color, polyphenol and ascorbic acid retention in strawberries (Fragaria × ananassa Duch.) Food Res. Int. 48 1 2012 241 248
22. X. Hong, and J. Wang Detection of adulteration in cherry tomato juices based on electronic nose and tongue: comparison of different data fusion approaches J. Food Eng. 126 2014 89 97
23. G.B. Huang, H. Zhou, X. Ding, and R. Zhang Extreme learning machine for regression and multiclass classification Systems, Man, Cybern., Part B: Cybern., IEEE Trans. 42 2 2012 513 529
24. Huang, G.B., Zhu, Q.Y., Siew, C.-K., 2004. Extreme learning machine: a new learning scheme of feedforward neural networks, Neural Networks, 2004. In: Proceedings, 2004 IEEE International Joint Conference on. IEEE, pp. 985-990. (Pubitemid 40011594)
25. G.B. Huang, Q.Y. Zhu, and C.-K. Siew Extreme learning machine: theory and applications Neurocomputing 70 1 2006 489 501 (Pubitemid 44615772)
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 J. Agric. Food Chem. 55 11 2007 4289 4298 (Pubitemid 46932621)
27. D. Kohl Fundamentals and recent developments of homogeneous semiconducting sensors Sens. Sens. Syst. Electron. Nose 1992 53 76 Springer
28. Kohonen, T., 1990. Improved versions of learning vector quantization, Neural Networks, 1990. In: 1990 IJCNN International Joint Conference on. IEEE, pp. 545-550.
29. J. KLozano, J.P. Santos, T. Arroyo, M. Aznar, J.M. Cabellos, M. Gil, and M.D.C. Horrillo Correlating e-nose responses to wine sensorial descriptors and gas chromatography-mass spectrometry profiles using partial least squares regression analysis Sens. Actuators, B 127 1 2007 267 276 (Pubitemid 47503734)
30. P. Komthong, N. Igura, and M. Shimoda Effect of ascorbic acid on the odours of cloudy apple juice Food Chem. 100 4 2007 1342 1349 (Pubitemid 44164423)
31. M. Luo, and K. Zhang A hybrid approach combining extreme learning machine and sparse representation for image classification Eng. Appl. Artif. Intell. 27 2014 228 235
32. C. Ndiaye, S.-Y. Xu, and Z. Wang Steam blanching effect on polyphenoloxidase, peroxidase and colour of mango (Mangifera indica) slices Food Chem. 113 1 2009 92 95
33. M.O. Nisperos-Carriedo, and P.E. Shaw Comparison of volatile flavor components in fresh and processed orange juices J. Agric. Food Chem. 38 4 1990 1048 1052
34. I. Odriozola-Serrano, R. Soliva-Fortuny, and O. Martín-Belloso Phenolic acids, flavonoids, vitamin C and antioxidant capacity of strawberry juices processed by high-intensity pulsed electric fields or heat treatments Eur. Food Res. Technol. 228 2 2008 239 248
35. I. Oey, M. Lille, A. Van Loey, and M. Hendrickx Effect of high-pressure processing on colour, texture and flavour of fruit-and vegetable-based food products: a review Trends Food Sci. Technol. 19 6 2008 320 328 (Pubitemid 351756530)
36. S.O. Olatunji, A. Selamat, and A. Abdulraheem A hybrid model through the fusion of type-2 fuzzy logic systems and extreme learning machines for modelling permeability prediction Inf. Fusion 16 2014 29 45
37. L. Pang, J. Wang, X. Lu, and H. Yu Discrimination of storage age for wheat by E-nose Trans. ASABE 51 5 2008 1707 1712
38. I. Peinado, E. Rosa, A. Heredia, I. Escriche, and A. Andres Influence of processing on the volatile profile of strawberry spreads made with isomaltulose Food Chem. 138 1 2013 621 629
39. P. Piyasena, R. McKellar, and F. Bartlett Thermal inactivation of Pediococcus sp. in simulated apple cider during high-temperature short-time pasteurization Int. J. Food Microbiol. 82 1 2003 25 31 (Pubitemid 36043924)
40. L.M. Reid, T. Woodcock, C.P. O'Donnell, J.D. Kelly, and G. Downey Differentiation of apple juice samples on the basis of heat treatment and variety using chemometric analysis of MIR and NIR data Food Res. Int. 38 10 2005 1109 1115 (Pubitemid 41102213)
41. H. Reinhard, F. Sager, and O. Zoller Citrus juice classification by SPME-GC-MS and electronic nose measurements LWT-Food Sci. Technol. 41 10 2008 1906 1912
42. N. Sadrieh, J. Brower, L. Yu, W. Doub, A. Straughn, S. Machado, F. Pelsor, E. Saint Martin, T. Moore, and J. Reepmeyer Stability, dose uniformity, and palatability of three counterterrorism drugs - human subject and electronic tongue studies Pharm. Res. 22 10 2005 1747 1756 (Pubitemid 41355915)
43. N.P. Seeram, R. Lee, H.S. Scheuller, and D. Heber Identification of phenolic compounds in strawberries by liquid chromatography electrospray ionization mass spectroscopy Food Chem. 97 1 2006 1 11 (Pubitemid 41773934)
44. K. Sturm, D. Koron, and F. Stampar The composition of fruit of different strawberry varieties depending on maturity stage Food Chem. 83 3 2003 417 422 (Pubitemid 37108705)
45. K.A. Taiwo, M.N. Eshtiaghi, B.I. Ade-Omowaye, and D. Knorr Osmotic dehydration of strawberry halves: influence of osmotic agents and pretreatment methods on mass transfer and product characteristics Int. J. Food Sci. Technol. 38 6 2003 693 707 (Pubitemid 37179686)
46. A. Versari, G.P. Parpinello, A.U. Mattioli, and S. Galassi Characterisation of Italian commercial apricot juices by high-performance liquid chromatography analysis and multivariate analysis Food Chem. 108 1 2008 334 340
47. S. Wold, A. Ruhe, H. Wold, and W.J. Dunn III The collinearity problem in linear regression. The partial least squares (PLS) approach to generalized inverses SIAM J. Sci. Stat. Comput. 5 3 1984 735 743
48. Y.X. Xu, M. Zhang, Z.X. Fang, J.C. Sun, and Y.Q. Wang How to improve bayberry (Myrica rubra Sieb. et Zucc.) juice flavour quality: effect of juice processing and storage on volatile compounds Food Chem. 151 2014 40 46
49. H. Zhang, M. Chang, J. Wang, and S. Ye Evaluation of peach quality indices using an electronic nose by MLR, QPST and BP network Sens. Actuators, B 134 1 2008 332 338
50. H. Zhang, J. Wang, and S. Ye Predictions of acidity, soluble solids and firmness of pear using electronic nose technique J. Food Eng. 86 3 2008 370 378 (Pubitemid 350297504)