Abstract
The performances of three multivariate analysis methods—partial least squares (PLS) regression, secured principal component regression (sPCR) and modified secured principal component regression (msPCR)—are compared and tested for the determination of human serum albumin (HSA), γ-globulin, and glucose in phosphate buffer solutions and blood glucose quantification by near-infrared (NIR) spectroscopy. Results from the application of PLS, sPCR and msPCR are presented, showing that the three methods can determine the concentrations of HSA, γ-globulin and glucose in phosphate buffer solutions almost equally well provided that the prediction samples contain the same spectral information as the calibration samples. On the other hand, when some potential spectral features appear in new measurements, sPCR and msPCR outperform PLS significantly. The reason for this is that such spectral features are not included during calibration, which leads to a degradation in PLS prediction performance, while sPCR and msPCR can improve their predictions for the concentrations of the analytes by removing the uncalibrated features from the original spectra. This point is demonstrated by successfully applying sPCR and msPCR to in vivo blood glucose measurements. This work therefore shows that sPCR and msPCR may provide possible alternatives to PLS in cases where some uncalibrated spectral features are present in measurements used for concentration prediction.
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Acknowledgements
We thank Prof. Qingsong Xu (ChemoAC, Vrije Universiteit Brussel, Farmaceutisch Instituut) for helpful discussion. The authors at Central South University are supported by the project from National Natural Science Foundation of China (Grant No.: 20235020).
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Li, BY., Kasemsumran, S., Hu, Y. et al. Comparison of performance of partial least squares regression, secured principal component regression, and modified secured principal component regression for determination of human serum albumin, γ-globulin and glucose in buffer solutions and in vivo blood glucose quantification by near-infrared spectroscopy. Anal Bioanal Chem 387, 603–611 (2007). https://doi.org/10.1007/s00216-006-0977-1
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DOI: https://doi.org/10.1007/s00216-006-0977-1