Mutual factor analysis for quantitative analysis by temperature dependent near infrared spectra.

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Chemometrics

Background:

• Near-infrared (NIR) spectroscopy is valuable for analyzing mixtures and molecular interactions.
• Temperature variations can significantly influence spectral data, complicating analysis.
• Understanding these temperature-induced spectral changes is crucial for accurate quantification.

Purpose of the Study:

• To develop and validate a chemometric method for analyzing temperature-dependent NIR spectra.
• To quantify glucose concentrations in serum samples using NIR spectroscopy.
• To explore a new method for quantitative analysis of bio-systems based on solvent-analyte interactions.

Main Methods:

• Application of Mutual Factor Analysis (MFA) to temperature-dependent NIR spectral data.
• Analysis of water-glucose mixtures to correlate spectral features with temperature and concentration.
• Validation of the MFA method using serum samples for glucose measurement.

Main Results:

• MFA successfully extracted spectral features related to temperature and concentration in water-glucose mixtures.
• A good linear correlation was observed between spectral variations and their inducing factors (temperature/concentration).
• An acceptable calibration model for glucose measurement in serum yielded a high correlation coefficient (R² = 0.8639) with reasonable deviations (-18.7-8.52%).

Conclusions:

• Mutual Factor Analysis is a robust method for analyzing temperature-dependent NIR spectra.
• The method provides accurate glucose quantification in serum, suitable for clinical applications.
• This approach, focusing on solvent-analyte spectral interactions, offers a novel pathway for bio-system analysis.