Prediction of some quality properties of rice and its flour by near-infrared spectroscopy (NIRS) analysis.

The measurement of different quality properties requires particular tools and chemical materials, most of which are time-using. The present research was accomplished to survey the possibility of using NIRS (870-2450 nm) to predict the amylose content (AC), protein content (PC), breakdown (BDV), and setback viscosity (SBV) of white rice ( variety) and its flour. Determination coefficients of calibration models to flour samples of AC, PC, BDV, and SBV generated by the partial least-squares (PLS) regression were obtained as  ≥ .

Mathematical modeling for the prediction of some quality parameters of white rice based on the strength properties of samples using response surface methodology (RSM).

One of the major problems in predicting the quality properties of rice is that conducting experiments in the food industry can be highly expensive. The objective of this study was to predict some quality properties in varieties (, and ) via compression test at moisture levels 9 and 14% w.b.