Granulation sensing of first-break ground wheat using a near-infrared reflectance spectrometer: studies with soft red winter wheats

A near-infrared reflectance spectrometer, previously evaluated as a granulation sensor for first-break ground wheat from six wheat classes and hard red winter (HRW) wheats, was further evaluated for soft red winter (SRW) wheats. Two sets of 35 wheat samples, representing seven cultivars of SRW wheat ground by an experimental roller mill at five roll gap settings (0.38, 0.51, 0.63, 0.75 and 0.88 mm), were used for calibration and validation. Partial least squares regression was applied to develop the granulation models using combinations of four data pretreatments (log(1/R), baseline correction, unit area normalisation and derivatives) and subregions of the 400-1700 nm wavelength range. Cumulative mass of size fraction was used as reference value. Models that corrected for path length effects (those that used unit area normalisation) predicted the bigger size fractions well. The model based on unit area normalisation/first derivative predicted 34 out of 35 validation spectra with standard errors of prediction of 3.53, 1.83, 1.43 and 1.30 for the >1041, >375, >240 and >136 µm size fractions respectively. Because of less variation in mass of each size fraction, SRW wheat granulation models performed better than the previously reported models for six wheat classes. However, because of SRW wheat flour's tendency to stick to the underside of sieves, the finest size fraction of these models did not perform as well as the HRW wheat models.