Abstract
A weighted parallel factor analysis (W-PARAFAC) model is applied to excitation−emission matrix (EEM) fluorescence spectra of carbamate pesticides to aid with calibration in the presence of Raman scattering. Traditional PARAFAC inefficiently models the Raman scattering, resulting in prediction and calibration errors when a significant background is present. Four different weighting strategies were investigated and compared with subtraction of the appropriate sample background. Using a binary weighting strategy produced superior results, compared with a continuous distribution of weights. Further choice of weighting strategies, which are optimized to include either maximum analyte signal or to exclude a maximum amount of background scattering, is dependent on the degree of overlap and relative signal intensity.
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