Comparison of Dispersive and Fourier-Transform Nir Instruments for Measuring Grain and Flour Attributes

Dispersive and Fourier-transform (FT) near-infrared (NIR) instruments were compared for their predictiveperformance of several wheat flour and grain constituents. Protein, moisture, and hardness index of whole grain wheat andprotein, ash, and amylose of wheat flour were used to develop prediction equations between reference data of theseconstituents and their spectra. Partial Least Squares (PLS) regression was used to develop the prediction equations. Modelswere selected using F-test criteria (. = 0.05). NIR and FT-NIR spectrometers collected spectra over the wavelength rangesof 1100 to 2498 nm and 1142 to 2502 nm, respectively. Results show that FT-NIR and NIR instruments were comparable inprediction performance and there is no apparent advantage of one over the other. Wheat flour protein and ash, whole grainwheat protein, and moisture models had good quantitative prediction based on ratios of the standard error of prediction tothe standard deviation of the reference data (RPD), i.e. RPD values were greater than 5. Wheat flour amylose and whole grainwheat hardness index predictions were qualitative with RPD values near 3.