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Mathematical Modelling of Food Processing
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Mathematical Modelling of Food Processing

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Engineering and Technology".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 1670

Special Issue Editors

Prof. Dr. Sakamon Devahastin

E-Mail Website
Guest Editor
Department of Food Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, 126 Pracha u‐tid Road, Tungkru, Bangkok 10140, Thailand
Interests: drying; novel food proceesing; food property characterization; mathematical modeling of food processing operations
Dr. Somkiat Prachayawarakorn

E-Mail Website
Guest Editor
Department of Chemical Engineering, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
Interests: food drying; fruits and grains

Special Issue Information

Dear Colleagues,

Modelling is an important tool for devising and improving food processing systems since it allows the generation of valuable data necessary for such activities without having to heavily rely on tedious and, in most cases, expensive experiments. This would lead in turn to the availability of higher-efficiency devices, equipment and optimal operating processing conditions. Modelling can be performed either through the use of analytical, numerical or empirical tools and can include the prediction and understanding of complex transport processes, physicochemical property changes and even oral mastication as well as gastro-intestinal digestion. Modelling is beneficial in understanding the nature of a process and determining the relevant effective and/or optimal process parameters and conditions. Simulation strategies in modelling could be beneficial in the visualization of the effects of process parameters, determination of the optimal process conditions or design parameters for the scaling-up of industrial lines, and their validation.

This Special Issue aims to serve as an outlet for high-quality, state-of-the art articles dealing with all aspects of mathematical modelling as related to foods. Potential topics include, but are not limited to, numerical methods in mathematical modelling, computational simulations, trends in modelling procedures for food processing, modelling-based optimization and design of food processing operations/systems and their validation, and life cycle analysis.

Prof. Dr. Sakamon Devahastin
Dr. Somkiat Prachayawarakorn
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • modelling
  • computational
  • numerical
  • optimization
  • transport phenomena
  • quality
  • human-food relations
  • equipment
  • scale-up

Published Papers (2 papers)

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Research

27 pages, 11541 KiB  
Article
Mathematical Modeling and Design of Parboiled Paddy-Impinging Stream Dryer Using the CFD-DEM Model
by Thanit Swasdisevi, Wut Thianngoen and Somkiat Prachayawarakorn
Foods 2024, 13(10), 1559; https://doi.org/10.3390/foods13101559 - 16 May 2024
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Abstract
Impinging stream dryers (ISDs) are effective for removing moisture from particulate materials because of the complex multiphase transport of air particles in ISDs. Nowadays, computational techniques are powerful to simulate multiphase flows, including dilute and dense-phase gas–solid flows and hence, the use of [...] Read more.
Impinging stream dryers (ISDs) are effective for removing moisture from particulate materials because of the complex multiphase transport of air particles in ISDs. Nowadays, computational techniques are powerful to simulate multiphase flows, including dilute and dense-phase gas–solid flows and hence, the use of a reliable computational model to simulate the phenomena and design a dryer has recently received more attention. In this study, computational fluid dynamics, combined with the discrete element method (CFD-DEM) and falling drying rate model, were used to predict the multiphase transport phenomena of parboiled paddy in a coaxial ISD. The design of an impinging stream pattern for improving residence time in a drying chamber of ISD was also investigated. The results showed that the CFD-DEM, in combination with the falling drying model, could be well-utilized to predict the particle motion behavior and lead to more physically realistic results. The predicted change of moisture content in parboiled paddy was in good agreement with the experimental data for 17 cycles of drying. Although the prediction of mean residence time was lower than the experimental data, the predicted mean residence time was a similar trend to the experimental data. For ISD design, the simulation revealed that the use of two stages of impinging stream region (two streams collide at the top of the drying chamber at the first stage and then the gas particles flow on the incline floor to collide with the other stream at second stage) in a drying chamber could increase the residence time approximately 75% and reduce drying cycle from 17 to 10 cycles when it was considered at the same final moisture content. Full article
(This article belongs to the Special Issue Mathematical Modelling of Food Processing)
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15 pages, 4404 KiB  
Article
Analysis of Mass Transfer and Shrinkage Characteristics of Chinese Cabbage (Brassica rapa L. ssp. pekinensis) Leaves during Osmotic Dehydration
by Timilehin Martins Oyinloye and Won Byong Yoon
Foods 2024, 13(2), 332; https://doi.org/10.3390/foods13020332 - 20 Jan 2024
Viewed by 831
Abstract
The mass transfer and shrinkage characteristics of Chinese cabbage (CC) during osmotic dehydration (OD) were investigated. The leaves were grouped into four sections and analyzed based on their morphological characteristics (i.e., maturity, width, and thickness). The sections were immersed in 2.0 mol/m3 [...] Read more.
The mass transfer and shrinkage characteristics of Chinese cabbage (CC) during osmotic dehydration (OD) were investigated. The leaves were grouped into four sections and analyzed based on their morphological characteristics (i.e., maturity, width, and thickness). The sections were immersed in 2.0 mol/m3 NaCl for 120 h at 25 ± 2 °C. The diffusion coefficient (D) of the leaf blade was not significantly different with respect to the sections that were formed, but it was significantly different in the midrib in the increasing order of P1, P4, P3, and P2, with values of 1.12, 1.61, 1.84, and 2.06 (× 10−6), respectively, after a 1 h soaking period due to the different characteristics in morphology and structure, such as porosity (0.31, 0.41, 0.42, and 0.38 for positions 1, 2, 3, and 4, respectively) and fiber contents. Numerical simulation (NS) for CC was conducted with and without the consideration of shrinkage during OD. The shrinkage effect on the NaCl uptake analyzed using NS indicated no significant difference between 0 to 48 h for both models. However, changes in the NaCl concentration were observed from 48 h onwards, with a lesser concentration in the model with shrinkage for all sections. The difference in NaCl concentration for the models with and without shrinkage was within the standard error range (±0.2 mol/m3) observed during experimental analysis. This implies that the shrinkage effect can be overlooked during the modeling of CC to reduce computational power. Full article
(This article belongs to the Special Issue Mathematical Modelling of Food Processing)
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