Prediction of wheat milling characteristics by near-infrared reflectance spectroscopy

Abstract

The aim of this study was to explore the use of NIR spectroscopy of laboratory milled flour to predict the milling characteristics of wheat. Quantitative traits of the milling process of wheat were predicted by analyses of NIR spectra of six sets consisting of 94 samples. Reference data were obtained by grinding the samples on the laboratory mill Chopin CD1-auto (France), spectral data were measured on spectrograph NIRSystem 6500. Commercial spectral analysis software WINISI II was used to collect spectra, develop calibration equations and evaluate calibration performance. The quality of prediction was evaluated by coefficients of correlation between the measured and the predicted values from cross and independent validation. MPLS/PLS regression and ANN methods were used. A statistically significant dependence (at the probability level of 99%) was determined for all traits studied in the case of cross-validation. Satisfactory accuracy of the prediction models by independent validation was achieved only for semolina extraction rate, models for other characteristics did not show acceptable precision.