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

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

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  • Comparison of multivariate calibration models for glucose, urea, and lactate from near-infrared and Raman spectra. Abstract Text:

    min renMin Ren,mark a arnoldMark A Arnold,

    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.

    Comparison of multivariate calibration models for glucose, urea, and lactate from near-infrared and Raman spectra. Publishing Authors By Initials

    m renM Ren,ma arnoldMA Arnold,

    For similar organic chemicals: urea research abstracts see: organic chemicals: urea research

    PUBMED ID PMID:

    MEDLINE DATE:

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

    PUBLICATION TYPE: Research Support, N.I.H., Extr

    Journal: Analytical and bioanalytical chemistry

    VOLUME: 387

    Page Numbers: 879-88

    Journal Abbreviation:

    ISSN: 1618-2642

    DAY: 3

    MONTH: 01

    YEAR: 2007

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

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 101134327

    Comparison of multivariate calibration models for glucose, urea, and lactate from near-infrared and Raman spectra. Keywords Mesh Terms:

    KEYWORDS: Urea

    MESH TERMS: chemistry

    Chemical & Substance for Abstract: Comparison of multivariate calibration models for glucose, urea, and lactate from near-infrared and Raman spectra. Information

    Substance Name: Urea

    Registry Number: 57-13-6

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

    AFFILIATION: Department of Chemistry and Optical Science and Technology Center, University of Iowa, Iowa City, IA 52242, USA.

    Country: Germany

    Germany Research PublicationGermany Research Publication

    AGENCY: United States NIDDK

    GRANT: DK-60657

    ACRONYM: DK

    MEDLINETA: Anal Bioanal Chem

    REFSOURCE:

    DATABASENAME:

    ACCESSION NUMBER:

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