Optical method for predicting total soluble solids in pears using radial basis function networks

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5587, Issue , 2004, Pages 198-212

  Liu, Yande ^a,b   Ying, Yibin ^a   Lu, Huishan ^a  

^a ZHEJIANG UNIVERSITY   (China)

^b JIANGXI AGRICULTURAL UNIVERSITY   (China)

Author keywords

Near infrared (NIR) spectroscopy; Non destructive prediction; Radial basis function networks (RBFN); Total soluble solids

Indexed keywords

ALGORITHMS; CALIBRATION; ERROR DETECTION; FUNCTIONS; NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; PATTERN RECOGNITION; SOLID SOLUTIONS;

NEAR INFRARED (NIR) SPECTROSCOPY; NON-DESTRUCTIVE PREDICTION; RADIAL BASIS FUNCTION NETWORKS (RBFN); TOTAL SOLUBLE SOLIDS;

RADIAL BASIS FUNCTION NETWORKS;

EID: 16644384206     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.569967     Document Type: Conference Paper

References (35)

1. R. B. H. Wills, W. B. McGlasson, D. Graham, T.H.Lee and E.G. Hall. Postharvest: An Introduction to the Physiology and Handling of Fruit and Vegetables. BSP Professional Books, Oxford, 1989.
2. P. H. Fidêncio, R. J. Poppi, J. C. de Andrade, "Determination of organic matter in soils using radial basis function networks and near infrared spectroscopy". Analytica Chimica Acta 45, pp. 125-134, 2002.
3. I. Walinga, M. Kithome, I. Novozamsky, V.J.G. Houba, J.J. van der Lee, Commun. Soil Sci. Plant Anal. 23, PP. 1935-, 1992.
4. P. Geladi, B. Kowalski, PLS tutorial, Anal. Chim. Acta 185 (1986) 1.
5. H. Martens, T. Naes, Multivariate Calibration, Wiley, New York, 1989.
6. M. Blanco, J. Coello, H. Iturriaga, S. Maspoch and J. Pages, "NIR calibration in non-linear systems: different PLS approaches and artificial neural networks". Chemometrics and Intelligent Laboratory Systems 50, pp. 75-82, 2000.
7. J.R.M. Smits, W.J. Melssen, L.M.C. Buydens and G. Kateman, Chemom. Intell. Lab. Syst. 22, pp.165-, 1994.
8. M. Blanco, J. Coello, H. Iturriaga, S. Maspoch and E. Bertran, "Analysis of cotton-polyestor yarns by near-infrared reflectance spectroscopy", Analyst 119, pp. 1779-1785, 1994.
9. K. Esbensen, P. Geladi, S. Wold, Chem. Intell. Lab. Syst. 2, pp. 37-52, 1987.
10. D.M. Haaland and E.V. Thomas, "Partial least-square methods for spectral analyses. 1.Relation to other quantitative calibration methods and the extraction of qualitative information", Anal. Chem. 60, pp. 1193-1202, 1988.
11. P. Geladi and B.R. Kowalski, Anal. Chim. Acta. 185, pp.1-17, 1986.
12. M. Blanco, J. Coello, H. Iturriaga, S. Maspoch and J. Pages, "NIR calibration in non-linear systems: different PLS approaches and artificial neural networks", Chemometrics and Intelligent Laboratory Systems 50, pp. 75-82, 2003
13. H. Swierenga, P.J. de Groot, A.P. de Weijer, M.W.J. Derk sen and L.M.C. Buydens, "Improvement of PLS model transferability by rubust wavelength selection", Chem. Intell. Lab. Syst. 41, pp. 237-248, 1998.
14. W. Windig and D.A. Stephenson, "Self-modeling mixture analysis of second-derivative near-infrared spectral data using the SIMPLISMA approach", Anal. Chem. 64, pp. 2735-2742, 1992
15. A.M.C. Davies, NIR News 4 (4), pp. 10-11, 1993
16. C. Fischbacher, K.U. Jagemann, K. Danzer, U.A. Muller, L.Papenkordt, J. Schuler and J. Fresenius, Anal. Chem. 359, pp. 78-, 1997.
17. M. Carlin, T. Kavli and B. Lillekjendlie, Chemometr. Intell. Lab. 23, pp. 163-, 1994.
18. S. Haykin, "Neural Networks a Comprehensive Foundation, 2nd Edition, Prentice-Hall, Englewood Cliffs", NJ, 1999.
19. S. Chen, C.F.N. Cowan and P.M. Grant, IEEE Trans. Neural Networks 2, pp. 302-, 1991.
20. M.J.L. Orr, Neural Comp. 7, pp. 606-, 1995.
21. J. Zupan and J. Gasteige, Anal. Chim. Acta. 248, pp. 1-30. 1991
22. S. Wold, N. Kettaneh-Wold and B. Skagerberg, Chem. Intell. Lab. Syst. 7, pp.53-65, 1989.
23. K. Stokbro, D.K. Umberger and J.A. Hertz, "Exploiting neurons with localized receptive fields to learn chaos", Complex Syst. 4, pp. 603-622, 1990.
24. R.D. Jones, Y.C. Lee, C.W. Barnes, G.W. Flake, K. Lee, S.P. Lewis and S. Qian, "Function approximation and time-series prediction with neural networks", IJCNN International Joint Conference, IEEE, pp. 649-665, 1990.
25. T.A. Johansen and B.A. "Foss, Representing and learning unmodeled dynamics with neural network memories", Proc. Am. Control Conf. 3037-3043, 1992.
26. K.M. Tao, "Extended radial basis function (ERBF) networks linear extension and connections, Proceedings of Asilomar Conference on Signals", Systems and Computers, IEEE, pp. 907-911, 1995.
27. K.J. Hunt, R. Haas and R.M. Smith, "Extending the functional equivalence of radial basis function networks and fuzzy inference systems", IEEE Trans. Neural Netw. 7: 776- 78, 1996.
28. B. Walczak and D.L. Massart, "The radial basis functions - partial least squares approach as a flexible non-linear regression technique", Anal. Chim. Acta 33, pp. 177-185, 1996.
29. B. Walczak and D.L. Massart, "Application of radial basis functions - partial least squares to non-linear pattern recognition problems: diagnosis of process faults", Anal. Chim. Acta 331, pp. 187-193, 1996.
30. J. S. R. Jang and C.T. Sun, "Functional equivalence between radial basis function networks and fuzzy inference systems", IEEE Trans. Neural Netw. 4, pp. 156-159, 1994.
31. H. Wang, Z.Y. Liu, Q.B. Li and K.X. Xu, "Application of radial basis function networks in fundamental study of noninvasive measurement of human blood glucose concentration with near infrared spectroscopy", Chinese Journal of Analytical Chemistry.4, pp. 440-443, 2003.
32. S. Chen, C.F.N. Cowan and P.M. Grant, "Orthogonal least squares learning algorithm for radial basis function networks", IEEE Trans. Neural Netw. 2, pp. 302-309, 1991.
33. C.C. Lee, P.C. Chung, J.R. Tsai and C.I. Chang, "Robust radial basis function neural networks", IEEE Trans. Syst. Man Cybern., Part B, Cybern. 29, pp.674-685, 1999.
34. M.J.D. Powell, "Radial basis functions for multivariable interpolation: a review, Algorithms for Approximation", Oxford Univ. Press, Oxford, 1987.
35. Y. Liu and Y. Ying, "Measurement of sugar content in Fuji apples by FT-NIR spectroscory", Journal of Zhejiang University SCIENCE 5(6), pp. 651-655, 2004.