Issue |
E3S Web Conf.
Volume 189, 2020
2020 International Conference on Agricultural Science and Technology and Food Engineering (ASTFE 2020)
|
|
---|---|---|
Article Number | 01016 | |
Number of page(s) | 6 | |
Section | Agricultural Resources and Agricultural Automation | |
DOI | https://doi.org/10.1051/e3sconf/202018901016 | |
Published online | 15 September 2020 |
Radio frequency heating for corn seeds: Model development and uniformity optimization
College of Engineering, China Agricultural University, 100083 Beijing, China
* Corresponding author: ydy@cau.edu.cn
Radio frequency (RF) heating has been considered as a promising method for food pasteurization and disinfestations, materials and heating uniformity are the main considerations in developing and scaling-up RF treatment protocols. In this study, an experimentally validated model of corn seeds was developed to investigate its RF heating characteristics and effects of sample shape on heating uniformity. Results showed that hot spots distributed in the corners and edges but cold ones in the centre of the rectangular sample, which led to the concentration of electric field at the sample edges, thus increased their electric field intensity and loss power. Comparing the temperature distributions of corn samples in six shapes, the best heating uniformity was observed in the special round sample (round corners, edges and surfaces), its uniformity index was 0.04, as its special round surface made the direction of the electromagnetic field in the sample incline to the centre, and homogenized the electric field intensity and loss power density. The results provide an evidence for temperature prediction and uniformity improvement of corn seeds during RF heating.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.