Fast analysis of blood glucose in whole blood by near-infrared spectroscopy

doi:10.5246/jcps.2025.11.079

Abstract

Abstract:

Diabetes remains one of the most pressing global metabolic disorders, necessitating regular and precise monitoring of blood glucose levels for effective disease management. In this study, we developed a rapid and reliable method for quantifying glucose in whole blood using near-infrared (NIR) spectroscopy. A diabetic rat model was established through a high-fat, high-sugar diet followed by administration of streptozotocin (STZ) over a period of 4 weeks. To construct the NIR calibration model, partial least-squares (PLS) regression was employed, with optimization tailored to spectral range, preprocessing techniques, and the number of latent variables. The optimal model was achieved within the spectral window of 7502.0–5446.2 cm^–1, using Constant Offset Elimination for spectral pretreatment and a factor number of 10. This optimized model yielded a strong correlation coefficient (R) of 0.9621, with a root mean square error of cross-validation (RMSECV) of 0.612, a residual predictive deviation (RPD) of 3.48, and a root mean square error of prediction (RMSEP) of 0.420. Additionally, biochemical indices were evaluated across all experimental groups to validate the model’s performance. Overall, the proposed NIR-based analytical strategy demonstrated high accuracy, robustness, and reproducibility, offering a promising tool for rapid glucose assessment in whole blood.

Key words: Near-infrared spectroscopy, Blood glucose assay, Whole blood, Partial least squares, Diabetes

Supporting:

Chunyan Li, Jintao Xue, Liming Ye. Fast analysis of blood glucose in whole blood by near-infrared spectroscopy[J]. Journal of Chinese Pharmaceutical Sciences, 2025, 34(11): 1051-1057.

Figures/Tables 5

References 16

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