HighlightsThe impact of parboiling process parameters on the feasibility of one-pass microwave drying of high-moisture parboiled rough rice was investigated.Rough rice was parboiled by 3 hours of soaking in water at 71°C, 73°C, or 76°C and then steamed for 5, 10, or 15 min prior to microwave drying at 915 MHz.Moisture content following parboiling at the studied conditions ranged from 42.59% to 48.21% dry basis.Microwave specific energies ranging from 0.04 to 0.29 kWh per kg of parboiled rough rice dry matter (kWh kg-DM-1) were used to dry the parboiled rough rice.Soaking at 73°C and steaming for 10 min followed by one-pass microwave drying at 0.29 kWh kg-DM-1 gave the best results in terms of parboiled rough rice final moisture content and post-drying milling and physiochemical properties.Microwave treatment can provide one-pass drying of parboiled rough rice.Abstract. The volumetric heating phenomenon of microwaves (MW) offers a means to quickly dry high moisture content (MC) parboiled rough rice in one pass. However, to successfully dry parboiled rough rice in one pass using MW while preserving the milled rice yield and quality characteristics, it is vital to investigate the impacts of the pre-drying parboiling conditions on the drying process and the resulting product characteristics. The objectives of this study were to explore the feasibility of using MW at 915 MHz to dry high-MC parboiled rough rice and to determine the implications of the pre-drying soaking and steaming conditions on the parboiled rough rice final moisture content (FMC), milled rice yield (MRY), head rice yield (HRY), and the milled rice physiochemical properties. Freshly harvested, long-grain rough rice of the cultivar Mermentau at MC of 31.58% dry basis (d.b.) was used in this study. The parboiling process involved soaking the rough rice in water at temperatures of 71°C, 73°C, or 76°C and steaming for 5, 10, or 15 min. After parboiling, samples of rough rice for the controlled experiment were gently dried with natural air at 25°C and 65% relative humidity, while samples for MW treatment were dried using a 915 MHz MW dryer, which was set to deliver energy ranging from 0.04 to 0.29 kWh per kg of rough rice dry matter content (kWh kg-DM-1). The MW power applied during treatment ranged from 1 to 8 kW with heating durations of up to 6 min. The rough rice MC immediately increased after the soaking and steaming processes and ranged from 42.59% to 48.21% d.b. Increased soaking temperature led to increased uptake of water after parboiling, decreases in MRY, HRY, protein content, and milled rice surface lipid content (SLC), and increases in total color difference (TCD). Increased steaming duration led to decreased moisture uptake during steaming, decreased MRY, protein content, SLC, and TCD, and increased HRY. Increased MW specific energy led to decreased FMC, HRY, protein content, and SLC and increased TCD. It is recommended that long-grain rough rice should be soaked at 73°C, steamed for 10 min, and then treated at MW specific energy of 0.29 kWh kg-DM-1 in one pass to achieve parboiled rough rice FMC of 18.79% d.b., HRY of 69.33%, and desirable parboiled milled rice physicochemical and sensory properties. At the same parboiling conditions, the control samples had MRY of 74.98% and HRY of 74.07%. MW specific energy greater than 0.29 kWh kg-DM-1 was necessary to dry the parboiled rough rice to MC safe for long-term storage (14.29% to 15.61% d.b.). However, the application of specific energy beyond 0.29 kWh kg-DM-1 caused a reduction of HRY below that of the control samples. Therefore, to preserve HRY, rice processors should use MW specific energy of 0.29 kWh kg-DM-1 to partially dry parboiled rice and then complete the drying to a safe storage MC by using natural or slightly heated air. This study demonstrates the feasibility of using 915 MHz MW heating of high-MC parboiled rough rice to achieve one-pass drying. Keywords: 915 MHz microwaves, Milling yields, One-pass drying, Parboiled rough rice, Physicochemical properties, Rice quality.
Estimation of Rice Protein Content Using Ground-Based Hyperspectral Remote Sensing
