Texture evaluation of cooked parboiled rice using nondestructive milled whole grain near infrared spectroscopy

One consumer acceptability criterion of cooked parboiled rice is its texture, particularly hardness and toughness. The samples were obtained from parboiled rice factory for export. The hardness and toughness calibration models based on milled whole grain near infrared spectroscopy was developed. The ISO 11747 Rice-Determination of Rice Kernel Resistance to Extrusion after Cooking method was used as reference test. The models were established using partial least squares regression (PLSR), principal component regression (PCR) and support vector machine regression (SVM). The PLSR optimal calibration model of hardness with moving average smoothing pre-processing gave coefficient of determination of validation (r²), root mean square error of prediction (RMSEP) and ratio of prediction to deviation (RPD) of 0.70, 7.24 N and 1.93, respectively. The PCR optimal model of toughness using mean normalization preprocessing provided r², RMSEP and RPD of 0.66, 38.00 Nmm and 1.75, respectively. According to RPD threshold, the models were fair for prediction application. This feasibility study suggested that the NIR protocol developed was applicable for real use due to the error of the NIR scanning and other unexplained errors was only 5% and 1% for hardness and toughness models, respectively. However, the sample preparation before texture analysis has to be improved.