Abstract

Fourier coefficients computed from the NIR spectra of pulverized tobacco samples can be used to estimate certain chemical constituents in the samples. As few as 11 coefficients from the Fourier domain used in a stepwise multiple linear regression (SMLR) model provide results equivalent to a 7-term SMLR model using log I/<i>R</i> from the wavelength domain. The Fourier model reduces the computation time for calibration by 96% compared to the wavelength model, and reduces the magnetic storage space requirements by 98%. Removing the mean term from the Fourier model partially corrects the particle size anomaly encountered in pulverized samples.

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