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Applications of Modeling and Simulation in Food Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Food Science and Technology".

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 3333

Special Issue Editors


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Guest Editor
Koszalin University of Technology, Department of Food Industry Processes and Facilities, Koszalin, Poland
Interests: modeling; CFD and FEM simulation; PIV; poly-optimization; physical properties of food

E-Mail Website1 Website2
Guest Editor
Department of Food Engineering and Process Management, Warsaw University of Life Sciences, 02-787 Warsaw, Poland
Interests: sustainable food production; carbon footprint; structure; fruit waste; osmotic dehydration; food engineering; food design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the Food Engineering field the practical application of modeling, simulation and optimization is well-known. The development of modeling and simulation methods, new models and algorithms provide possibilities for the analysis of previously non solve problems. This is of fundamental importance to progress in the Food Science field, especially in Food Engineering. This area of scientific activity is developing as a response to the challenges of the contemporary food market. The development of new technologies requires a model approach, simulation research and optimization of production solutions. Special Issue entitled Applications of Modeling, Simulation and Optimization in Food Engineering seems an adequate platform for the presentation and exchange of knowledge and experience in this field.

Prof. Dr. Marek Jakubowski
Prof. Dr. Monika Janowicz
Guest Editors

Manuscript Submission Information

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Keywords

  • Food engineering
  • Modeling
  • Simulation
  • Optimization
  • Physical properties of food

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Published Papers (1 paper)

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Research

16 pages, 3230 KiB  
Article
Numerical Simulation on Spatial-Frequency Domain Imaging for Estimating Optical Absorption and Scattering Properties of Two-Layered Horticultural Products
by Dong Hu, Yuping Huang, Qiang Zhang, Lijian Yao, Zidong Yang and Tong Sun
Appl. Sci. 2021, 11(2), 617; https://doi.org/10.3390/app11020617 - 10 Jan 2021
Cited by 4 | Viewed by 2341
Abstract
Spatial-frequency domain imaging (SFDI) is a wide-field, noncontact, and label-free imaging modality that is currently being explored as a new means for estimating optical absorption and scattering properties of two-layered turbid materials. The accuracy of SFDI for optical property estimation, however, depends on [...] Read more.
Spatial-frequency domain imaging (SFDI) is a wide-field, noncontact, and label-free imaging modality that is currently being explored as a new means for estimating optical absorption and scattering properties of two-layered turbid materials. The accuracy of SFDI for optical property estimation, however, depends on light transfer model and inverse algorithm. This study was therefore aimed at providing theoretical analyses of the diffusion model and inverse algorithm through numerical simulation, so as to evaluate the potential for estimating optical absorption and reduced scattering coefficients of two-layered horticultural products. The effect of varying optical properties on reflectance prediction was first simulated, which indicated that there is good separation in diffuse reflectance over a large range of spatial frequencies for different reduced scattering values in the top layer, whereas there is less separation in diffuse reflectance for different values of absorption in the top layer, and even less separation for optical properties in the bottom layer. To implement the nonlinear least-square method for extracting the optical properties of two-layered samples from Monte Carlo-generated reflectance, five curve fitting strategies with different constrained parameters were conducted and compared. The results confirmed that estimation accuracy improved as fewer variables were to be estimated each time. A stepwise method was thus suggested for estimating optical properties of two-layered samples. Four factors influencing optical property estimation of the top layer, which is the basis for accurately implementing the stepwise method, were investigated by generating absolute error contour maps. Finally, the relationship between light penetration depth and spatial frequency was studied. The results showed that penetration depth decreased with the increased spatial frequency and also optical properties, suggesting that appropriate selection of spatial frequencies for a stepwise method to estimate optical properties from two-layered samples provides potential for estimation accuracy improvement. This work lays a foundation for improving optical property estimation of two-layered horticultural products using SFDI. Full article
(This article belongs to the Special Issue Applications of Modeling and Simulation in Food Engineering)
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