Method of multirange models by near-infrared spectral analysis for nonlinear optics of organic materials

Xuedian D. Zhang; Min Chang; Kexin X. Xu

doi:10.1117/12.559078

15 October 2004 Method of multirange models by near-infrared spectral analysis for nonlinear optics of organic materials

Xuedian D. Zhang, Min Chang, Kexin X. Xu

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Proceedings Volume 5517, Linear and Nonlinear Optics of Organic Materials IV; (2004) https://doi.org/10.1117/12.559078
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

Near-infrared (NIR) spectroscopy has gained wide spread acceptance in recent years as a powerful diagnostic tool, particularly for the concentrations of Components of Organic Materials. Unfortunately, most systems in practice are not perfectly linear; they show non-linear behavior of different types. Any model's capacity of information is not infinity, and it is founded that the calibration model is of a strong selectivity caused by non-linear, i.e. the model will provide satisfactory predict results for the samples in the appropriate ranges of the measurements, but make poor ones for the samples in the regions, especially for the extremes of the measurements. Reality has thus created a need for methods that can handle such non-linearities. A new technique of Multi-Region Model (MRM) instead of unique model is presented in the work. To validate the calibration, 198 milk samples were employed in this study, the comparison with the MRM method was based on the root mean square error of prediction (RMSEP) and Correlation coefficient (R2). The study result shows that the MRM accuracy for individual component's prediction is reliable. The predicted results of MRM exhibit values of R2 of 98.63% and 95.07%, and RMSEP of 0.116% and 0.101% for fat and protein, respectively.

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Xuedian D. Zhang, Min Chang, and Kexin X. Xu "Method of multirange models by near-infrared spectral analysis for nonlinear optics of organic materials", Proc. SPIE 5517, Linear and Nonlinear Optics of Organic Materials IV, (15 October 2004); https://doi.org/10.1117/12.559078

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KEYWORDS

Calibration

Statistical modeling

Data modeling

Near infrared

Systems modeling

Near infrared spectroscopy

Organic materials

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