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Related Experiment Videos

Detection of specific sugars in dairy process samples using multivariate curve resolution.

P W Hansen1, A S Van Brakel, J Garman

  • 1Foss Electric A/S, R&D Greenhouse, Hillerød, Denmark.

Journal of Dairy Science
|July 23, 1999
PubMed
Summary

This study demonstrates multivariate curve resolution using alternating least squares (ALS) for dairy process monitoring. ALS effectively tracks lactose hydrolysis via Fourier transform infrared spectroscopy without reference analysis, achieving high accuracy.

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Area of Science:

  • Analytical Chemistry
  • Process Engineering
  • Spectroscopy

Background:

  • Dairy processing involves complex chemical transformations.
  • Accurate monitoring of components like lactose is crucial for quality control.
  • Fourier transform infrared (FTIR) spectroscopy offers rich chemical information.

Purpose of the Study:

  • To apply multivariate curve resolution using alternating least squares (MCR-ALS) for dairy process monitoring.
  • To resolve and track key compounds during enzymatic lactose hydrolysis.
  • To evaluate MCR-ALS performance against traditional methods.

Main Methods:

  • Alternating least squares (ALS) applied to FTIR spectral data.
  • Resolution of spectral data from multiple dairy batch process runs.

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  • Monitoring of extracted compound concentrations in new process runs.

    • Main Results:

    • Successfully extracted pure spectra for four compounds: fat, lactose, glucose, and galactose.
    • MCR-ALS enabled real-time monitoring of lactose hydrolysis.
    • Lactose monitoring accuracy (correlation 0.980) was comparable to partial least squares regression (0.987).

    Conclusions:

    • MCR-ALS is a viable tool for label-free dairy process monitoring.
    • FTIR coupled with MCR-ALS can track enzymatic hydrolysis without reference analyses.
    • This method offers a powerful alternative for process analytical technology in the dairy industry.