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  5. Modeling and Quality Analysis of Radio Frequency Heating of Low Moisture Foods
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Modeling and Quality Analysis of Radio Frequency Heating of Low Moisture Foods

Date Issued
December 1, 2021
Author(s)
Chen, Qianyi
Advisor(s)
Jiajia Chen
Additional Advisor(s)
Tao Wu, Mark Morgan
Abstract

Low moisture food is usually considered as high safety food. Since its low water activity (aw < 7), this would be a strict environment for pathogen microbes to grow in the low moisture food. However, the recent outbreaks of Salmonella in low moisture foods indicated the possibility of microbiological contamination happened during the harvesting, processing or transportation of food products. Since the bad heat conduction of conventional thermal process on low moisture food, radiofrequency (RF) treatment is a promising technology to improve the heating efficiency with its volumetric heating. Nevertheless, non-uniformity heating is still a challenge in RF technology. There are two research chapters in this study. The first research chapter was to use computer modeling to understand the improvement of applied immersion fluids on the RF heating of the cornflour. The model had a good agreement with the experiment results. The modeling results showed that the soybean oil immersion could reduce the electric field distortion to get the best heating uniformity. Also, the higher sample heating rate caused by soybean oil immersion was mainly because of higher electromagnetic power absorption and lower surface heat loss. The heating efficiency of RF was improved but less study focused on the quality analysis of flour. Therefore, the second research study is to evaluate the effect of RF and extensive hot air oven processing on the quality and functionality of all-purposed flour.

Subjects

Low moisture foods

Radio frequency

Computer simulation

Heating uniformity

Quality analysis

Heat treatment

Disciplines
Food Processing
Degree
Master of Science
Major
Food Science
Embargo Date
December 15, 2022
File(s)
Thumbnail Image
Name

Thesis_final_draft_QC_081321.pdf

Size

2.69 MB

Format

Adobe PDF

Checksum (MD5)

da6b47bba32af9d8c650e0022f602453

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