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

Temperature dependent near infrared (NIR) spectroscopy has been developed for analyzing multi–component mixtures and understanding the molecular interactions in solutions. In this work, a chemometric method named as mutual factor analysis (MFA) was proposed for the analysis of temperature dependent NIR spectra. The method extracts the common spectral feature contained in the spectra of different temperature or different concentration. The relative quantity of the extracted spectral feature is proportional to the temperature or concentration. From the spectra of water–glucose mixtures, both the spectral variations induced by temperature and concentration are obtained and the variations are correlated with the inducements, respectively, in a very good linearity. Serum samples were used for validation of the method. An acceptable calibration model with a good correlation coefficient (R2 = 0.8639) was obtained for glucose measurement. The relative deviations of the measured concentrations from the calibration model are in the range of –18.7–8.52%, which are in a reasonable level for clinical uses. More importantly, the calculations are based on the spectral information of water that has interactions with the analyte. This provides a new way for quantitative analyses of bio–systems. A novel method named as mutual factor analysis (MFA) was proposed to extract the spectral features from temperature dependent near infrared spectra for detecting the glucose content in serum. [Display omitted] •Temperature dependent NIR spectroscopy was used for glucose detection.•A novel method was proposed for analyzing temperature dependent NIR spectra.•Temperature– and concentration–induced spectral variation can be obtained.•Spectral variation of water can be used for quantitative determination of analyte.•Glucose in serum can be detected by the proposed method.