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Multivariate calibrations in UV spectrophotometric analysis.

M Saeed Arayne1, Najma Sultana, Saima Sher Bahadur

  • 1Department of Chemistry, University of Karachi, Karachi-75270, Pakistan.

Pakistan Journal of Pharmaceutical Sciences
|April 10, 2007
PubMed
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Multivariate calibration models instrumental measurements to analyze multiple samples. This two-step process calibrates data and predicts analyte levels, aiding in sample analysis and interference separation.

Area of Science:

  • Analytical Chemistry
  • Chemometrics

Background:

  • Calibration is essential for relating instrumental measurements to sample properties.
  • Multivariate calibration handles multiple measurements across various samples.

Purpose of the Study:

  • To explain the two-step procedure of multivariate calibration: data calibration and prediction.
  • To detail the construction and application of calibration models.

Main Methods:

  • Utilizes a calibration set of indirect measurements with predetermined analyte levels.
  • Develops a model relating sample measurements to instrument readings.
  • Employs calibration techniques to determine coefficient values for predictive equations.

Main Results:

  • Calibration models can predict analyte levels in new samples.

Related Experiment Videos

  • The method facilitates sample separation from interferences.
  • Model construction complexity varies, with some cases being time-consuming.

    • Conclusions:

    • Multivariate calibration provides a framework for analyzing complex sample matrices.
    • The predictive models derived are valuable for quantitative analysis.
    • This approach enhances the utility of instrumental measurements in diverse applications.