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

Abstract

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 (Khazar 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 R2cal ≥.85 and R2pre ≥.80. Root mean square error of calibration (RMSEC) was calculated as 0.393, 0.07, 2.55, and 1.33, respectively. Similarly to grain samples, were obtained as R2cal ≥.88 and R2pre ≥.71 for calibration and prediction. RMSEC was measured as 0.303, 0.27, 2.59, and 3.11, respectively. NIRS has the potential to be used as a quick technique for predicting the quality attributes of kernel specimens.