Over the past 10 years near-infrared researchers predominantly have been concerned with mathematical manipulations which provide more reliable calibrations. Considerable emphasis in the last five year has been placed on the use of principal components (PCA) and partial least squares (PLS) both being artificial variates computed from Log (1/R) data as a viable manipulation for solving some of the problems associated with qualitative and quantitative NIR analyses. However it remains to be proven that the variates from PCA and PLS are better for quantitative analysis than the original Log (1/R) data from which the variates are computed. Fourier analysis is proposed in this paper as an alternative data treatment for both quantitative and qualitative work. Spectra of whole-kernel and ground wheat with protein analyses are used to demonstrate the use of Fourier transforms in the analysis of NIR data. 1.