Effect of drying conditions on the quality of IRGA 424 rice.

BACKROUND: The objective of this research was to investigate the effects of drying temperature (40, 50, and 60 °C), tempering time (40, 80, and 120 min), and initial moisture content at onset of tempering (15, 17, and 19% dry basis) on head rice yield, milled rice yield, and total processing time of IRGA 424 rice. RESULTS: The most significant effects were the drying temperature and its interaction with initial moisture content at onset of tempering. The optimum conditions predicted to reach the highest total yield (74.1%) included drying at 46.6 °C, 49 min of tempering time, and initial moisture content at onset of tempering of 19%. To achieve the maximum value of whole grain yield (52.9%), drying at 40 °C, 40 min of tempering, and an initial moisture content of 19% at the initiation of tempering were required. Under these conditions, the grain reached a moisture content of 13% in 84 min. CONCLUSION: Whole-grain rice yields may be maximized through the optimization of the drying process. This may result in a larger fraction of the crop entering the human food chain, enhancing the value of the crop, and resulting in a smaller fraction of broken grain, which commands a lower market value. © 2018 Society of Chemical Industry.

Comparison of mathematical models to predict glass transition temperature of rice (cultivar IRGA 424) measured by dynamic mechanical analysis.

Dynamic mechanical analysis (DMA) was applied to measure the Tg of rice IRGA 424 at different moisture content values (9.3%-22.3% wet basis). To conduct temperature sweeps, the samples were heated at a rate of 2°C/min from 20 to 120°C keeping frequency to 1 Hz. Tg was measured both from the E″ peak temperature (Tgmidpoint) and from the tan (δ) peak temperature (Tgendset). Tgmidpoint and Tgendset increased from 31.8 to 86.6°C and 42.1 to 104.7°C, respectively, as moisture content decreased from 22.3 to 9.3%. Six models were tested for their ability to predict Tg as a function of the moisture content. As all residuals were normally distributed and homoskedastic, standard metrics were used to assess the fitted models. Goodness of fit by these models was established by comparing the coefficient of determination (R 2), standard error of the estimate (SEE), and mean relative deviation (MRD). The Gordon-Taylor linearized equation was the most accurate in predicting Tg. To predict Tg from the moisture content of the rice samples, a new expression was proposed. For the conditions considered in this work, the developed equation satisfactorily predicts the Tg of rice IRGA 424 without needing prior linearization.