Utilization of ultraviolet-visible spectrophotometry in conjunction with wrapper method and correlated component regression for nitrite prediction outside the Beer-Lambert domain
JOURNAL OF CHEMOMETRICS(2023)
摘要
The determination of nitrite concentration is crucial due to its toxicity. A novel model has been developed to accurately determine nitrite concentration within the non-linear range, utilizing the Zambelli method. Previously, techniques for measure nitrite concentration were primarily restricted to the linear range. This new method employs UV-Visible absorption spectra and correlated component regression (CCR) to determine nitrite concentration within the range of 0.27-11.34 ppm. A wavelength selection strategy in conjunction with partial least squares (PLS) was implemented prior to applying CCR. The spectral data underwent pre-processing using standard normal variant (SNV) and Savitzky Golay (SG) techniques, and a backward selection (BS) strategy with PLS was applied to select wavelengths. The 15 most sensitive wavelengths, determined through the RMSECV criterion, were utilized to create a PLS model within the range 377-497 nm, resulting in a model with R-C(2) = 0.9999 and R-CV(2) = 0.9999, RMSEC = 0.006, RMSECV = 0.027. A CCR model was then established using the 15selected wavelengths and nitrite concentration. The results yielded strong correlation between predicted and measured nitrite values with R-C(2) = 0.9996, RMSEC = 4.7491 E-15, RMSECV = 0.0004, and MAPE = 0.68%. The method has been validated through an accuracy profile, which demonstrates that 80% of future results will fall within the 10% acceptability limit within the validation range of 1.30-8.83 mg/L.
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关键词
accuracy profile,correlated component regression,nitrite,partial least square,wrapper method
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