Table of Contents
ISRN Spectroscopy
Volume 2013 (2013), Article ID 642190, 9 pages
http://dx.doi.org/10.1155/2013/642190
Research Article

The Combined Optimization of Savitzky-Golay Smoothing and Multiplicative Scatter Correction for FT-NIR PLS Models

1College of Science, Guilin University of Technology, Guilin, Guangxi 541004, China
2Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin, Guangxi 541004, China

Received 26 November 2012; Accepted 18 December 2012

Academic Editors: G. D'Errico, A. Huczynski, and Y. Ueno

Copyright © 2013 Huazhou Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. A. Burns and E. W. Ciurczak, Handbook of Near-Infrared Analysis, Marcel dekker, New York, NY, USA, 2nd edition, 2001.
  2. W. Z. Lu, Modern Near Infrared Spectroscopy Analytical Technology, Petrochemical press, Beijing, China, 2nd edition, 2007.
  3. J. G. Wu, Modern Fourier Transform Near-Infrared Spectroscopy and Applications, Science and Technology Literature Press, Beijing, China, 1995.
  4. V. R. Sinija and H. N. Mishra, “FT-NIR spectroscopy for caffeine estimation in instant green tea powder and granules,” Food Science and Technology, vol. 42, no. 5, pp. 998–1002, 2009. View at Publisher · View at Google Scholar · View at Scopus
  5. R. M. Mosley and R. R. Williams, “Fourier transform near infrared absorption spectroscopy of gases,” Journal of Near Infrared Spectroscopy, vol. 2, no. 3, pp. 119–125, 1994. View at Publisher · View at Google Scholar
  6. M. Manley, A. van Zyl, and E. E. H. Wolf, “The evaluation of the applicability of Fourier transform near-infrared (FT-NIR) sppectroscopy in the measurement of analytical parameters in must and wine,” South African Journal for Enology and Viticulture, vol. 22, no. 2, pp. 93–100, 2001. View at Google Scholar
  7. P. Geladi and B. R. Kowalski, “An example of 2-block predictive partial least-squares regression with simulated data,” Analytica Chimica Acta, vol. 185, pp. 19–32, 1986. View at Google Scholar · View at Scopus
  8. J. Verdú-Andrésa, D. L. Massart, C. Menardo, and C. Sterna, “Correction of non-linearities in spectroscopic multivariate calibration by using transformed original variables and PLS regression,” Analytica Chimica Acta, vol. 349, no. 1–3, pp. 271–282, 1997. View at Publisher · View at Google Scholar · View at Scopus
  9. S. Kasemsumran, Y. P. Du, K. Maruo et al., “Improvement of partial least squares models for in vitro and in vivo glucose quantifications by using near-infrared spectroscopy and searching combination moving window partial least squares,” Chemometrics and Intelligent Laboratory Systems, vol. 82, no. 1-2, pp. 97–103, 2006. View at Publisher · View at Google Scholar
  10. B. Igne, J. B. Reeves, G. McCarty, W. D. Hively, E. Lundc, and C. R. Hurburgh, “Evaluation of spectral pretreatments, partial least squares, least squares support vector machines and locally weighted regression for quantitative spectroscopic analysis of soils,” Journal of Near Infrared Spectroscopy, vol. 18, no. 3, pp. 167–176, 2010. View at Publisher · View at Google Scholar · View at Scopus
  11. M. J. McShane, G. L. Coté, and C. H. Spiegelman, “Assessment of partial least-squares calibration and wavelength selection for complex near-infrared spectra,” Applied Spectroscopy, vol. 52, no. 6, pp. 878–884, 1998. View at Publisher · View at Google Scholar · View at Scopus
  12. S. R. Delwiche and J. B. Reeves, “The effect of spectral pre-treatments on the partial least squares modelling of agricultural products,” Journal of Near Infrared Spectroscopy, vol. 12, no. 3, pp. 177–182, 2004. View at Google Scholar · View at Scopus
  13. L. Seemann, J. Shulman, and G. H. Gunaratne, “A robust topology-based algorithm for gene expression profiling,” ISRN Bioinformatics, vol. 2012, Article ID 381023, 11 pages, 2012. View at Publisher · View at Google Scholar
  14. A. Savitzky and M. J. E. Golay, “Smoothing and differentiation of data by simplified least squares procedures,” Analytical Chemistry, vol. 36, no. 8, pp. 1627–1639, 1964. View at Google Scholar · View at Scopus
  15. P. A. Gorry, “General least-squares smoothing and differentiation by the convolution (Savitzky-Golay) method,” Analytical Chemistry, vol. 62, no. 6, pp. 570–573, 1990. View at Google Scholar · View at Scopus
  16. S. F. Xie, B. R. Xiang, L. Y. Yu, and H. S. Deng, “Tailoring noise frequency spectrum to improve NIR determinations,” Talanta, vol. 80, no. 2, pp. 895–902, 2009. View at Publisher · View at Google Scholar · View at Scopus
  17. S. R. Delwiche and J. B. Reeves, “A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with savitzky-golay filters and partial least squares regression,” Applied Spectroscopy, vol. 64, no. 1, pp. 73–82, 2010. View at Google Scholar · View at Scopus
  18. Å. Rinnan, F. V. D. Berg, and S. B. Engelsen, “Review of the most common pre-processing techniques for near-infrared spectra,” Trends in Analytical Chemistry, vol. 28, no. 10, pp. 1201–1222, 2009. View at Publisher · View at Google Scholar · View at Scopus
  19. H. Z. Chen, T. Pan, J. M. Chen, and Q. P. Lu, “Waveband selection for NIR spectroscopy analysis of soil organic matter based on SG smoothing and MWPLS methods,” Chemometrics and Intelligent Laboratory Systems, vol. 107, no. 1, pp. 139–1146, 2011. View at Publisher · View at Google Scholar
  20. P. Geladi, D. MacDougall, and H. Martens, “Linearization and scatter-correction for near-infrared reflectance spectra of meat,” Applied Spectroscopy, vol. 39, no. 3, pp. 491–500, 1985. View at Google Scholar · View at Scopus
  21. B. Ludwig, R. Nitschke, T. Terhoeven-Urselmans, K. Michel, and H. Flessa, “Use of mid-infrared spectroscopy in the diffuse-reflectance mode for the prediction of the composition of organic matter in soil and litter,” Journal of Plant Nutrition and Soil Science, vol. 171, no. 3, pp. 384–391, 2008. View at Publisher · View at Google Scholar · View at Scopus
  22. R. J. Barnes, M. S. Dhanoa, and S. J. Lister, “Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra,” Applied Spectroscopy, vol. 43, no. 5, pp. 772–777, 1989. View at Google Scholar
  23. M. Silva, M. H. Ferreira, J. W. Braga, M. Sena, and Talanta, “Development and analytical validation of a multivariate calibration method for determination of amoxicillin in suspension formulations by near infrared spectroscopy,” Talanta, vol. 89, pp. 342–351, 2012. View at Google Scholar
  24. D. Cozzolino and A. Morón, “Potential of near-infrared reflectance spectroscopy and chemometrics to predict soil organic carbon fractions,” Soil and Tillage Research, vol. 85, no. 1-2, pp. 78–85, 2006. View at Publisher · View at Google Scholar · View at Scopus
  25. M. Confalonieri, F. Fornasier, A. Ursino, F. Boccardi, B. Pintus, and M. Odoardi, “The potential of near infrared reflectance spectroscopy as a tool for the chemical characterisation of agricultural soils,” Journal of Near Infrared Spectroscopy, vol. 9, no. 2, pp. 123–131, 2001. View at Google Scholar · View at Scopus
  26. R. A. V. Rossel and T. Behrens, “Using data mining to model and interpret soil diffuse reflectance spectra,” Geoderma, vol. 158, no. 1-2, pp. 46–54, 2010. View at Publisher · View at Google Scholar · View at Scopus
  27. T. Terhoeven-Urselmans, K. Michel, M. Helfrich, H. Flessa, and B. Ludwig, “Near-infrared spectroscopy can predict the composition of organic matter in soil and litter,” Journal of Plant Nutrition and Soil Science, vol. 169, no. 2, pp. 168–174, 2006. View at Publisher · View at Google Scholar · View at Scopus
  28. O. Viikki and K. Laurila, “Cepstral domain segmental feature vector normalization for noise robust speech recognition,” Speech Communication, vol. 25, no. 1–3, pp. 133–147, 1998. View at Google Scholar · View at Scopus
  29. W. Wu, S. E. Wildsmith, A. J. Winkley, R. Yallop, F. J. Elcock, and P. J. Bugelski, “Chemometric strategies for normalisation of gene expression data obtained from cDNA microarrays,” Analytica Chimica Acta, vol. 446, no. 1-2, pp. 449–464, 2001. View at Google Scholar · View at Scopus
  30. I. A. Vasilieva, “On normalization of scattering matrices of polarized radiation,” Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 101, no. 1, pp. 159–165, 2006. View at Publisher · View at Google Scholar · View at Scopus