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