Study on Optimization of Hot Air Drying Process and Nutrient Quality
Model of Rice Driven by Accumulated Temperature
LI Jin-quan1,2, YIN Jun2,3, JIN Yi2,3*, YI Xiao-kang1*, ZHANG Zhong-jie2,3
(1. Modern Agricultural Engineering Key Laboratory at Universities of Education Department of Xinjiang Uygur Autonomous Region, Xinjiang Production and Construction Corps（XPCC）Key Laboratory of Utilization and Equipment of Special Agricultural and Forestry Products in Southern Xinjiang, College of Mechanical and Electrical Engineering, Tarim University, Alar, Xinjiang 843300, China; 2. Institute of Grain Storage and Logistics, Academy of National Food and Strategic Reserves Administration, Beijing 100037, China; 3. National Engineering Research Centre of Grain Storage and Logistics, Beijing 100037, China)
Abstract: The study undertook a thin-layer hot air-drying experiment on rice, and an orthogonal testing approach was used to explore the drying characteristics under diverse conditions of hot air temperature, humidity, initial moisture content, airflow velocity, and tempering ratio. It compared the applicability of nine different accumulated temperature-nutritional index (protein, fat, starch) mathematical models in the hot air drying process of rice. The results showed that the experimental scheme was designed using Central- Composite design, and the parameter combination was optimized through a regression model to hot air temperature hot air temperature (T) at 38.5 ℃, humidity (RH) at 48.086%, initial moisture content (MC) at 19.82%, airflow velocity (V) at 0.70 m/s, and tempering ratio (TR) at 1.45. The relative error between the experimental results and the optimized results was 3.65%, and the relative error of the accumulated temperature-nutritional quality model was 5.92%. Through mathematical model fitting, it was found that the accumulated temperature-protein content was best fitted by the modified Page II model, while the accumulated temperature-fat content was best fitted by the Thompson equation. The accumulated temperature-amylose content was best fitted by the Midilli equation, and the accumulated temperature- amylopectin content was best fitted by the Weibull II equation. All models were highly significant. The optimized drying process maintained nutritional quality and improved drying efficiency. This study could provide a new approach for in-depth exploration of the mechanism of rice quality changes and lay a foundation for the subsequent development of intelligent control systems.
Key words: accumulated temperature; nutritional quality; process optimization; drying model
Chinese Library Classification Number: TS203
Documentary Identification Code: A Article ID: 1007-7561(2024)05-0001-10
Published time on CNKI: 2024-09-01 16:56:49
Published address on CNKI: https://link.cnki.net/urlid/11.3863.TS.20240830.0921.002
