Equidistant Five Wavenumbers Selection for NIR Spectroscopy Analysis of Glucose in Human Serum

Article Preview

Abstract:

Using Fourier transform near-infrared (FTNIR) transmission spectroscopy and multiple linear regression (MLR) method of the equidistant wavenumbers combination, the quantitative analysis models of human serum glucose were established, and discrete wavenumbers combination was optimized. The optimal models were found in the five equidistant wavenumbers combinations with 7 and 40 gaps.The center wavenumber of the optimal models with 40 gaps in the first overtone region and combination region were 7970 and 5880 cm-1 respectively, and the corresponding RMSEP were 0.371 and 0.389 mmol/L respectively. While the center wavenumber of the optimal models with 7 gaps in the combination region and first overtone region were 5795 and 8041 cm-1 respectively, and the corresponding RMSEP were 0.395 and 0.407 mmol/L respectively. The above four models had a good prediction effect, and could provide basis for designing minitype special NIR spectroscopy instrument.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 181-182)

Pages:

647-650

Citation:

Online since:

January 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] D.A. Burns, E.W. Ciurczak: Handbook of near-infrared analysis, 2nd ed., Marcel dekker inc: New York, (2001).

Google Scholar

[2] W.Z. Lu: Modern near infrared spectroscopy analytical technology, 2nd ed., (China petrochemical press, Beijing 2007).

Google Scholar

[3] J. Xie, T. Pan, J.M. Chen, H.Z. Chen, X.H. Ren: Joint optimization of savitzky-golay smoothing models and partial least squares factors for near-infrared spectroscopic analysis of serum glucose, Chinese Joumal of Analytical Chemistry 38(3) (2010).

DOI: 10.3724/sp.j.1096.2010.00342

Google Scholar

[4] P. Cao, T. Pan, X.D. Chen: Choice of Wave Band In Design of Minitype Near-Infrared Corn Protein Content Analyzer, Optics and Precision Engineering 15(12) (2007), p.1952-(1958).

Google Scholar

[5] J.H. Jiang, R.J. Berry, H.W. Siesler, Y. Ozaki: Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and hear-infrared spectroscopic data, Anal. Chem. 74 (2002).

DOI: 10.1021/ac011177u

Google Scholar

[6] S. Kasemsumran, Y.P. Du, K. Murayama, M. Huehne, Y. Ozaki: Near-infrared spectroscopic determination of human serum albumin, γ-globulin, and glucose in a control serum solution with searching combination moving window partial least squares, Anal. Chim. Acta 512 (2004).

DOI: 10.1016/j.aca.2004.02.045

Google Scholar

[7] Y.P. Du, Y.Z. Liang, J.H. Jiang, R.J. Berry, Y. Ozaki: Spectral regions to improve prediction ability of PLS modes by changeable size moving window partial least squares and searching combination moving window partial least squares, Anal. Chim. Acta 501 (2004).

DOI: 10.1016/j.aca.2003.09.041

Google Scholar

[8] H.C. Chen, Z.G. Yang, H.Y. Li, X.D. Chen: Rapid determination of glucose in human serum using fourier transform near infrared spectroscopy, Journal of China Jiliang University, 15 (3) (2004), pp.0235-0237.

Google Scholar

[9] Y.P. Luo, J. Zhang, R.F. Zheng, Y. Cao, W.R. Weng, X.D. Chen: Study of Orthogonal Signal Correction Analyze in Human Serum Glucose with Near Infrared Spectroscopy, 24 (5) (2007), pp.773-777.

Google Scholar

[10] L.N. Lu, R. Liu: Application of O-PLS in Fundamental Study of Non-Invasive Measurement of Human Blood Glucose Concentration with Near Infrared Spectroscopy, Spectroscopy and Spectral Analysis, 25(12) (2005), p.1950-(1954).

Google Scholar

[11] X.D. Chen: Possibility of noninvasive clinical biochemical examination by near infrared spectroscopy, Optics and Precision Engineering, 16(5) (2008), pp.759-763.

Google Scholar