Abstract

We have investigated the use of principal component analysis (PCA) to describe and assess mid-infrared spectral data obtained from complex biological samples containing sucrose, fructose, and glucose. The correlation coefficients between spectral data and chemical values of each variable (sucrose, glucose, fructose, total sugars, and reducing sugars) showed that in each case, axes 1, 3, 4, and 5 had the highest values. These values also indicated which axes each variable was mostly correlated with. The results also showed that the samples were distributed according to their sucrose concentrations (or total sugars) along a concentration gradient in the projection plan formed between axes 1 and 3. No clear discrimination according to concentration was observed with other factorial maps. Prediction equations that linked sucrose, fructose, glucose, total sugar, and reducing sugars concentrations to the spectral data were established by regression on the principal component. Very high correlation coefficients values between the first 10 axes and the chemical values were obtained (between 0.9757 and 0.998). From such aqueous biological samples containing a ternary mixture of sucrose, fructose, and glucose, it was possible to (1) identify the characteristic IR bands of these different sugars (and their combination: reducing sugars/total sugars) and (2) to specifically measure their concentrations with a relatively good accuracy.

Identification of pure component spectra by independent component analysis in glucose prediction based on mid-infrared spectroscopy

Sangjoon Hahn and Gilwon Yoon
Appl. Opt. 45(32) 8374-8380 (2006)

Continuous noninvasive monitoring of changes in human skin optical properties during oral intake of different sugars with optical coherence tomography

Yuqing Zhang, Guoyong Wu, Huajiang Wei, Zhouyi Guo, Hongqin Yang, Yonghong He, Shusen Xie, and Ying Liu
Biomed. Opt. Express 5(4) 990-999 (2014)

Determination of glucose in whole blood samples by mid-infrared spectroscopy

Yoen-Joo Kim, Sangjoon Hahn, and Gilwon Yoon
Appl. Opt. 42(4) 745-749 (2003)

Biocompatible spider silk-based metal-dielectric fiber optic sugar sensor

Hsuan-Pei E, Jelene Antonicole Ngan Kong, Wei-Chun Chen, Che-Chin Chen, Chia-Hsiung Cheng, and Cheng-Yang Liu
Biomed. Opt. Express 13(9) 4483-4493 (2022)

In vitro measurements of physiological glucose concentrations in biological fluids using mid-infrared light

Sabbir Liakat, Kevin A. Bors, Tzu-Yung Huang, Anna P. M. Michel, Eric Zanghi, and Claire F. Gmachl
Biomed. Opt. Express 4(7) 1083-1090 (2013)