Evaluation of a near-infrared reflectance spectrometer as a granulation sensor for first-break ground wheat: Studies with six wheat classes

In flour milling, a granulation sensor for ground wheat is needed for autom atic control of a roller mill's roll gap. A near-infrared (NIR) reflectance spectrometer was evaluated as a potential granulation sensor of first-brea k ground wheat using offline methods. Sixty wheat samples, ground independe ntly, representing six classes and five roller mill gaps, were each used fo r calibration and validation sets. Partial least squares regression was use d to develop the models with cumulative mass of size fraction as the refere nce value. Combinations of four data pretreatments (log (1/R), baseline cor rection, unit area normalization, and derivatives) and three wavelength reg ions (700-1,500, 800-1,600, and 600-1,700 nm) were evaluated. Unit area nor malization combined with baseline correction or second derivative yielded m odels that predicted well each size fraction of first-break ground wheat. S tandard errors of performance of 4.07, 1.75, 1.03, and 1.40 and r(2) of 0.9 3, 0.90, 0.88, and 0.38 for the >1,041-, >375-, >240-, and >136-mum size ra nges, respectively, were obtained for the best model. Results indicate that the granulation sensing technique based on NIR reflectance is ready for on line evaluation.