Milling quality assessment of Khao Dok Mali 105 milled rice by near-infrared reflectance spectroscopy technique

Abstract

The objective of this study was to assess milling quality of Khao Dok Mali 105 milled rice. The physicochemical properties of milled rice can be analyzed in values of milling quality as degree of milling (DOM), surface lipid content (SLC), color as L*, a*and b*, and the whiteness index using various kinds of measuring instrument. However in this study, the calibration models were developed using only the near infrared reflectance spectroscopy (NIRS) to determine the various physicochemical properties at wavelengths between 1,100 and 2,500 nm. The signal pretreatment and partial least square (PLS) regression were used to validate the models for the measurement of DOM, SLC, L*, a*, b* and whiteness index. Six calibration models of these properties were optimized based on the cross validation correlations (Rcv), standard error of cross validation (SECV), the external validation correlations (Rv) and standard error of prediction (SEP). It was found that the Rcv for these six models were 0.98, 0.99, 0.98, 0.95, 0.85 and 0.98 while the Rv for those were 0.99, 0.99, 0.98, 0.96, 0.88 and 0.99, the correlation were closed to 1 which shown that the agreement between data and the models were satisfied. In the meantime, the SECV and the SEP of these six calibration models shew less fluctuation of data and models. As the results, the calibration models developed in this study can be used to predict the milling quality of KDML 105 milled rice. The relationships between DOM and the five parameters were also investigated in this study.