A method for correction of pathlength effects in near-infrared (NIR) spectra is presented. This method, called Pathlength Correction with Chemical Modeling (PLC-MC), requires the use of standards in which the chemistry varies but the pathlength remains constant. Principal Components Analysis (PCA) is used to model the chemical variations in the spectra of the standards. The PCA model can then be used to estimate the pathlength of a future sample from the spectrum of the sample. Theoretical and experimental comparisons of the PLC-MC correction method with the Multiplicative Scatter Correction (MSC) method indicate that the PLC-MC method is more accurate than the MSC method if spectral variability from chemical variations is large.

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