Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.1
2.8
Journals
Processes
Special Issues
Experimentation, Optimization and Simulation of Drying Processes of Agricultural Food...
share announcement

Experimentation, Optimization and Simulation of Drying Processes of Agricultural Food Products and Materials

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Food Process Engineering".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 2556

Special Issue Editors

Dr. Oldřich Dajbych

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Faculty of Engineering, Czech University of Life Sciences, 16521 Prague, Czech Republic
Interests: drying behaviour; experimental design; modelling; spectral analysis; thermal properties
Dr. Kemal Çağatay Selvi

E-Mail Website
Guest Editor
Department of Agricultural Machinery and Technologies Engineering, Faculty of Agriculture, University of Ondokuz Mayis, Samsun 55139, Turkey
Interests: drying agricultural products; processing technologies; physical properties; chemical properties; agricultural tools and machines
Dr. Alfadhl Alkhaled

E-Mail Website
Guest Editor
Department of Horticulture, College of Agricultural & Life Sciences, University of Wisconsin, Madison, WI 53705, USA
Interests: remote sensing; agriculture engineering; hyperspectral imaging system; spectroscopy technology; smart farming; precision agriculture; machine learning; data science; agricultural informatics; instrumentation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We would like to invite you to contribute to our Special Issue ‘Experimentation, Optimization and Simulation of Drying Processes of Agricultural Food Products and Materials’.

This Special Issue will provide an in-depth understanding of the complexities and computational solutions of the drying processes of agricultural food products and materials. The use of models or simulations is the most popular way to sound engineering decisions concerning new process concepts involved in drying processes to achieve optimal energy utilization, environmental protection, and quality improvement of dried products for consumer acceptability, food sustainability, security, and prolonged storage periods.

The topics include, but are not limited to:

  • The design of experiments and optimization techniques of processing factors and parameters using different drying methods;
  • Thermal, physical, mechanical, chemical, and biological phenomena of different drying methods;
  • The numerical analysis and model validation of the drying experiments;
  • The development of models/simulations describing the drying processes and mechanisms;
  • Spectral profiles and quality assessment parameters of drying processes of agricultural food products and materials;
  • The determination of bioactive compounds of agricultural food products using different drying techniques;
  • The energy analysis of drying processes and pretreatment techniques across different drying methods;
  • Drying kinetics and empirical/mathematical modelling approaches used for agricultural food products and materials.

We look forward to your participation in this Special Issue.

Dr. Oldřich Dajbych
Dr. Kemal Çağatay Selvi
Dr. Alfadhl Alkhaled
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. Processes is an international peer-reviewed open access monthly 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 2400 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

  • agricultural products
  • post-harvest processing
  • drying methods
  • drying kinetics
  • machine learning
  • computational intelligence
  • quality assessment
  • transport mechanisms
  • spectral and thermal analyses
  • agri-food quality assessment

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

17 pages, 2791 KiB  
Article
Comprehensive Analysis and Optimization of Peach (Prunus persica) Vacuum Drying: Employing Principal Component Analysis, Artificial Neural Networks and the Standard Score Approach
by Zdravko Šumić, Aleksandra Tepić Horecki, Lato Pezo, Branimir Pavlić, Nataša Nastić and Anita Milić
Processes 2024, 12(12), 2643; https://doi.org/10.3390/pr12122643 - 23 Nov 2024
Viewed by 483
Abstract
Dried peaches are widely consumed as a snack food product and used as an ingredient in cereals as well in chocolate and energy bars. Accordingly, the main objective of this investigation was to optimize the vacuum-drying process for peaches using a combination of [...] Read more.
Dried peaches are widely consumed as a snack food product and used as an ingredient in cereals as well in chocolate and energy bars. Accordingly, the main objective of this investigation was to optimize the vacuum-drying process for peaches using a combination of three different statistical methods: principal component analysis, the standard score method and an artificial neural network approach. Applied input drying parameters were temperature (50–70 °C), pressure (20–120 mbar) and time (6–10 h), while the investigated output parameters were moisture content, water activity, total color change, phenolic and flavonoid contents and antioxidant activity. It was noted that all investigated output parameters constantly decreased (moisture content, water activity) and increased (total color change, total phenolic and flavonoid contents and antioxidant activity (FRAP, DPPH and ABTS assays)) in accordance with the applied drying temperature. The key variables accounted for 86.33% of data variance based on the PCA results, while the SS and ANN method resulted in the same optimal drying conditions: 60 °C, 70 mbar and 6 h, which indicated the effectiveness of the applied statistical methods. Full article
(This article belongs to the Special Issue Experimentation, Optimization and Simulation of Drying Processes of Agricultural Food Products and Materials)
►▼ Show Figures

Figure 1

18 pages, 5792 KiB  
Article
Artificial Neural Network Modeling Techniques for Drying Kinetics of Citrus medica Fruit during the Freeze-Drying Process
by Muhammed Emin Topal, Birol Şahin and Serkan Vela
Processes 2024, 12(7), 1362; https://doi.org/10.3390/pr12071362 - 29 Jun 2024
Cited by 1 | Viewed by 1550
Abstract
The main objective of this study is to analyze the drying kinetics of Citrus medica by using the freeze-drying method at various thicknesses (3, 5, and 7 mm) and cabin pressures (0.008, 0.010, and 0.012 mbar). Additionally, the study aims to evaluate the [...] Read more.
The main objective of this study is to analyze the drying kinetics of Citrus medica by using the freeze-drying method at various thicknesses (3, 5, and 7 mm) and cabin pressures (0.008, 0.010, and 0.012 mbar). Additionally, the study aims to evaluate the efficacy of an artificial neural network (ANN) in estimating crucial parameters like dimensionless mass loss ratio (MR), moisture content, and drying rate. Feedforward multilayer perceptron (MLP) neural network architecture was employed to model the freeze-drying process of Citrus medica. The ANN architecture was trained using a dataset covering various drying conditions and product characteristics. The training process, including hyperparameter optimization, is detailed and the performance of the ANN is evaluated using robust metrics such as RMSE and R2. As a result of comparing the experimental MR with the predicted MR of the ANN modeling created by considering various product thicknesses and cabin pressures, the R2 was found to be 0.998 and the RMSE was 0.010574. Additionally, color change, water activity, and effective moisture diffusivity were examined in this study. As a result of the experiments, the color change in freeze-dried Citrus medica fruits was between 6.9 ± 0.2 and 21.0 ± 0.6, water activity was between 0.4086 ± 0.0104 and 0.5925 ± 0.0064, effective moisture diffusivity was between 4.19 × 10−11 and 21.4 × 10−11, respectively. In freeze-drying experiments conducted at various cabin pressures, it was observed that increasing the slice thickness of Citrus medica fruit resulted in longer drying times, higher water activity, greater color changes, and increased effective moisture diffusivity. By applying the experimental data to mathematical models and an ANN, the optimal process conditions were determined. The results of this study indicate that ANNs can potentially be applied to characterize the freeze-drying process of Citrus medica. Full article
(This article belongs to the Special Issue Experimentation, Optimization and Simulation of Drying Processes of Agricultural Food Products and Materials)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop