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Analytical and Bioanalytical Chemistry

, Volume 387, Issue 3, pp 879–888 | Cite as

Comparison of multivariate calibration models for glucose, urea, and lactate from near-infrared and Raman spectra

  • Min Ren
  • Mark A. Arnold
Paper in Forefront

Abstract

Partial least-squares (PLS) calibration models have been generated from a series of near-infrared (near-IR) and Raman spectra acquired separately from sixty different mixed solutions of glucose, lactate, and urea in aqueous phosphate buffer. Independent PLS models were prepared and compared for glucose, lactate, and urea. Near-IR and Raman spectral features differed substantially for these solutes, with Raman spectra enabling greater distinction with less spectral overlap than features in the near-IR spectra. Despite this, PLS models derived from near-IR spectra outperformed those from Raman spectra. Standard errors of prediction were 0.24, 0.11, and 0.14 mmol L−1 for glucose, lactate, and urea, respectively, from near-IR spectra and 0.40, 0.42, and 0.36 mmol L−1 for glucose, lactate, and urea, respectively, from Raman spectra. Differences between instrumental signal-to-noise ratios were responsible for the better performance of the near-IR models. The chemical basis of model selectivity was examined for each model by using a pure component selectivity analysis combined with analysis of the net analyte signal for each solute. This selectivity analysis showed that models based on either near-IR or Raman spectra had excellent selectivity for the targeted analyte. The net analyte signal analysis also revealed that analytical sensitivity was higher for the models generated from near-IR spectra. This is consistent with the lower standard errors of prediction.

Keywords

Near-infrared spectroscopy Raman spectroscopy Noninvasive glucose sensing Multivariate calibration 

Notes

Acknowledgements

This work was supported by a grant from the National Institute of Diabetes and Digestive and Kidney Diseases (DK-60657). Professor Julie Jessop’s assistance with the Raman spectrometer is greatly appreciated.

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  1. 1.Department of Chemistry and Optical Science and Technology CenterUniversity of IowaIowa CityUSA

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