Particle size and bulk density are two important fundamental properties of food powder that directly affect processing and final product quality. The objective of this study was to evaluate and compare two optical sensing methods, i.e. visible/shortwave near infrared spectroscopy and hyperspectral scattering, for bulk density determination and particle size classification of wheat flour. Hyperspectral scattering images over the spectral region of 500–1000 nm and visible/shortwave near infrared reflectance spectra covering the spectral region of 400–1000 nm were acquired for 474 wheat flour samples. Partial least squares regression and discriminant analysis models for visible/shortwave near infrared spectra and mean spectra extracted from the hyperspectral scattering profiles were developed for determining the bulk density and classifying the particle size, of wheat flour samples. Hyperspectral scattering gave much better prediction results for bulk density, with the r2 (the coefficient of determination for prediction) value of 0.87 and the root mean squares error of prediction value of 30.20 mg ml−1, compared with the r2 of 0.55 and root mean squares error of prediction of 57.13 mg ml−1 obtained by visible/shortwave near infrared spectroscopy. Moreover, hyperspectral scattering resulted in 98.2% classification accuracy for particle size, versus 96.8% by visible/shortwave near infrared spectroscopy. This research suggested that hyperspectral scattering is more suitable than visible/shortwave near infrared spectroscopy for bulk density determination and particle size classification of food powder.
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