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Fluorescencespectroscopicdetermination oftriglyceride in humanserum with windowgenetic algorithmpartial least squares Xiangzhen KongWeihua ZhuZhimin Zhao2012 год

Fluorescence spectroscopic determination of triglyceride in human serum with window genetic algorithm partial least squares
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Аннотация: Fluorescence spectrum, as well as the first and second derivative spectra in the region of 220–900 nm, was utilized to determine the concentration of triglyceride in human serum. Nonlinear partial least squares regression with cubic B‐spline‐function‐based nonlinear transformation was employed as the chemometric method. Window genetic algorithms partial least squares (WGAPLS) was proposed as a new wavelength selection method to find the optimized spectra wavelengths combination. Study shows that when WGAPLS is applied within the optimized regions ascertained by changeable size moving window partial least squares (CSMWPLS) or searching combination moving window partial least squares (SCMWPLS), the calibration and prediction performance of the model can be further improved at a reasonable latent variable number. SCMWPLS should start from the sub‐region found by CSMWPLS with the smallest root mean squares error of calibration ( RMSEC ). In addition, WGAPLS should be utilized within the region of smallest RMSEC whether it is the sub‐region found by CSMWPLS or region combination found by SCMWPLS. Moreover, the prediction ability of nonlinear models was better than the linear models significantly. The prediction performance of the three spectra was in the following order: second derivative spectrum < original spectrum < first derivative spectrum. Wavelengths within the region of 300–367 nm and 386–392 nm in the first derivative of the original fluorescence spectrum were the optimized wavelength combination for the prediction model. Copyright © 2012 John Wiley & Sons, Ltd.
Год издания: 2012
Авторы: Xiangzhen Kong, Weihua Zhu, Zhimin Zhao, Xiangyan Li, Hui Wang, Ran Chen, Chuchu Chen, Feng Zhu, Xiaoying Guo
Издательство: Wiley
Источник: Journal of Chemometrics
Ключевые слова: Spectroscopy and Chemometric Analyses, Water Quality Monitoring and Analysis, Spectroscopy Techniques in Biomedical and Chemical Research