Comprehensive modeling of far-infrared drying process for rough rice in a combined FIR dryer

This study introduces a novel single-parameter model for the far-infrared (FIR) drying process of rough rice in a combined FIR dryer, aiming to streamline the prediction process and enhance its efficiency. The experiments involved three levels of FIR intensity (0, 500, and 1000 W m−2) and three levels of inlet air temperature (30, 40, and 50 °C), with a comprehensive examination of various mathematical thin-layer models to predict the drying process. The study developed a comprehensive single-parameter model by investigating the interrelationship of the models’ coefficients under distinct drying conditions, demonstrating its capability to faithfully depict the drying characteristics of rough rice within the combined FIR dryer with an R2 exceeding 0.99. The findings also provide valuable insights into the impact of drying conditions on the drying time, percentage of cracked kernels (PCK), and amylose content of rough rice, revealing increasing trends in PCK and amylose content with higher drying temperature and FIR intensity, offering practical and efficient tools for optimizing the drying process and enhancing the quality of dried rice products. Overall, this research significantly advances rice drying technology and offers practical solutions for improving the efficiency and quality of rice drying processes.

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Publication Details

Journal
Discover Food
Published
2024-09-05
DOI
https://doi.org/10.1007/s44187-024-00113-8
Citations
3
Primary Topic
Food Drying and Modeling
Type
article
Field-Weighted Citation Impact
1.05
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article

Comprehensive modeling of far-infrared drying process for rough rice in a combined FIR dryer

Alireza Rafati, Mojtaba Nosrati, Omid Davari
3 citations
Discover Food
Food Drying and Modeling
1.05
article

Comprehensive modeling of far-infrared drying process for rough rice in a combined FIR dryer

Alireza Rafati, Mojtaba Nosrati, Omid Davari
article en
3 citations

Abstract

This study introduces a novel single-parameter model for the far-infrared (FIR) drying process of rough rice in a combined FIR dryer, aiming to streamline the prediction process and enhance its efficiency. The experiments involved three levels of FIR intensity (0, 500, and 1000 W m−2) and three levels of inlet air temperature (30, 40, and 50 °C), with a comprehensive examination of various mathematical thin-layer models to predict the drying process. The study developed a comprehensive single-parameter model by investigating the interrelationship of the models’ coefficients under distinct drying conditions, demonstrating its capability to faithfully depict the drying characteristics of rough rice within the combined FIR dryer with an R2 exceeding 0.99. The findings also provide valuable insights into the impact of drying conditions on the drying time, percentage of cracked kernels (PCK), and amylose content of rough rice, revealing increasing trends in PCK and amylose content with higher drying temperature and FIR intensity, offering practical and efficient tools for optimizing the drying process and enhancing the quality of dried rice products. Overall, this research significantly advances rice drying technology and offers practical solutions for improving the efficiency and quality of rice drying processes.

Discover FoodVol. 4(1)
Islamic Azad University, Tehran (IR), Shiraz University (IR)
Zero hunger
Openalex Percentile: Top 23%
Food Drying and Modeling
1.05
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Comprehensive modeling of far-infrared drying process for rough rice in a combined FIR dryer — Alireza Rafati, Mojtaba Nosrati, et al. · Discover Food (2024) | TGRS Research Map | TGRS