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Processes
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Mathematical Modeling of Drying Kinetics in Food and Biomass Processing
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Mathematical Modeling of Drying Kinetics in Food and Biomass Processing

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

Deadline for manuscript submissions: 15 December 2024 | Viewed by 6545

Special Issue Editors

Dr. Ashutosh Singh

E-Mail Website
Guest Editor
School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada
Interests: molecular dynamics of food components; high electric field processing of thermo-sensitive food products; development of new food products and processes
Dr. Gopu Raveendran Nair

E-Mail Website
Guest Editor
Agricultural and Biological Engineering Department, University of Illinois Urbana Champaign, Champaign, IL 61801, USA
Interests: agricultural operations (harvesting, drying, storage, transportation etc.); postharvest processing technologies (microwave, radiofrequency, pulse electric field, high electric field); natural fiber and bio composites from forest biomass; biomass pre-treatment and conversion
Dr. Winny Routray

E-Mail Website
Guest Editor
Department of Food Process Engineering, National Institute of Technology Rourkela, Sundargarh 769008, Odisha, India
Interests: food engineering; storage and packaging; bioprocessing; byproduct valorization; data science and ML in food process engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Fruits and vegetables are preserved by drying using a simultaneous heat, mass, and momentum transfer process that extends the food product’s shelf life. Drying is a crucial step in the conversion of biomass; for instance, pre-drying is necessary when using biomass to generate electricity in order to improve the combustion efficiency. Mathematical models should be used to simulate and validate the drying process. It is possible to obtain results through the use of virtual laboratories that would be difficult or impractical to attain at the conceptual stage of research. The use of mathematical equations to anticipate the behavior of the drying process is known as mathematical modeling of food and biomass processing.

This Special Issue titled “Mathematical Modeling of Drying Kinetics in Food and Biomass Processing” invites high-quality research articles on the mathematical modeling of various drying methods, such as oven drying, solar drying, infrared drying, radiofrequency drying, microwave drying, ohmic heating, high-electric-field drying or similar drying systems for a variety of food and biomass.

Dr. Ashutosh Singh
Dr. Gopu Raveendran Nair
Dr. Winny Routray
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

  • mathematical modeling of food and biomass processing
  • drying process
  • various drying methods
  • drying systems for a variety of food and biomass

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Published Papers (3 papers)

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Research

16 pages, 1078 KiB  
Article
Drying Kinetics of Industrial Pineapple Waste: Effective Diffusivity and Thermodynamic Properties Resulting from New Mathematical Models Derived from the Fick Equation
by Mário Eduardo Cavalcanti-Mata, Maria Elita Duarte, Manoel Tolentino, Francisco Assis Mendes, Leonardo Batista, Janaína Maria de Lima, Alexandre Lúcio, Amanda Priscila Nascimento, Rafaela D. Almeida and Hugo M. Lisboa
Processes 2024, 12(6), 1198; https://doi.org/10.3390/pr12061198 - 11 Jun 2024
Cited by 2 | Viewed by 1037
Abstract
This research focuses on the drying kinetics of industrial pineapple processing waste on a flat plate, revealing a two-phase drying process: an initial phase with a constant drying rate followed by a phase with a decreasing drying rate. During the constant rate phase, [...] Read more.
This research focuses on the drying kinetics of industrial pineapple processing waste on a flat plate, revealing a two-phase drying process: an initial phase with a constant drying rate followed by a phase with a decreasing drying rate. During the constant rate phase, the convective mass transfer coefficient, influenced by temperature variations from 40 to 70 °C, ranged from 5.69 × 10−7 to 2.79 × 10−7 m s−1. The study introduced a novel approach to modeling the decreasing drying rate phase, applying equations derived from the Fick equation. This process involved determining the activation energy and thermodynamic properties of drying using an experimental forced convection dryer at temperatures of 40, 50, 60, and 70 °C, and an air velocity of 1.5 m/s. Data were fitted to several mathematical models, including Fick’s with four series terms, and versions of the Henderson–Pabis and Page models modified by Cavalcanti-Mata, among others. The Cavalcanti-Mata and modified Page models provided the most accurate fit to the experimental data. Results showed that diffusion coefficients vary per model yet align with literature values. Additionally, enthalpy (ΔH) and entropy (ΔS) values decreased with temperature, while Gibbs free energy (ΔG) increased, indicating that drying is an energy-dependent, non-spontaneous process. Full article
(This article belongs to the Special Issue Mathematical Modeling of Drying Kinetics in Food and Biomass Processing)
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16 pages, 4543 KiB  
Article
Convective Hot Air Drying of Red Cabbage (Brassica oleracea var. Capitata Rubra): Mathematical Modeling, Energy Consumption and Microstructure
by Antonio Vega-Galvez, Luis S. Gomez-Perez, Kong Shun Ah-Hen, Francisca Zepeda, Purificación García-Segovia, Cristina Bilbao-Sainz, Nicol Mejías and Alexis Pasten
Processes 2024, 12(3), 509; https://doi.org/10.3390/pr12030509 - 29 Feb 2024
Viewed by 1227
Abstract
This study examined the convective drying of red cabbage at temperatures ranging from 50 to 90 °C. Mathematical modeling was used to describe isotherms, drying kinetics and rehydration process. The effects of drying conditions on energy consumption and microstructure were also evaluated. The [...] Read more.
This study examined the convective drying of red cabbage at temperatures ranging from 50 to 90 °C. Mathematical modeling was used to describe isotherms, drying kinetics and rehydration process. The effects of drying conditions on energy consumption and microstructure were also evaluated. The Halsey model had the best fit to the isotherm data and the equilibrium moisture was determined to be 0.0672, 0.0490, 0 0.0379, 0.0324 and 0.0279 g water/g d.m. at 50, 60, 70, 80 and 90 °C, respectively. Drying kinetics were described most accurately by the Midilli and Kuçuk model. Also, the diffusion coefficient values increased with drying temperature. Lower energy consumption was found for drying at 90 °C and the rehydration process was best described by the Weibull model. Samples dehydrated at 90 °C showed high water holding capacity and better maintenance of microstructure. These results could be used to foster a sustainable drying process for red cabbage. Full article
(This article belongs to the Special Issue Mathematical Modeling of Drying Kinetics in Food and Biomass Processing)
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18 pages, 3552 KiB  
Article
Drying Kinetics, Physicochemical and Thermal Analysis of Onion Puree Dried Using a Refractance Window Dryer
by Ruchika Zalpouri, Manpreet Singh, Preetinder Kaur, Amrit Kaur, Kirtiraj K. Gaikwad and Ashutosh Singh
Processes 2023, 11(3), 700; https://doi.org/10.3390/pr11030700 - 26 Feb 2023
Cited by 14 | Viewed by 2988
Abstract
Onions have a high moisture content, which makes them more susceptible to microbial growth. Drying is one of the postharvest preservation methods applied to decrease onion moisture content, thereby increasing its storage life. In this study, onions were peeled, washed, cut into quarters, [...] Read more.
Onions have a high moisture content, which makes them more susceptible to microbial growth. Drying is one of the postharvest preservation methods applied to decrease onion moisture content, thereby increasing its storage life. In this study, onions were peeled, washed, cut into quarters, hot water blanched, and pureed. The puree was further dried using two different drying methods: refractance window drying (RWD) (water temperature: 70 °C) and convective drying (CD) (50 °C). The puree was spread on prefabricated trays at varying thicknesses of 2 mm, 4 mm, and 6 mm. It was observed that, irrespective of the drying method, moisture ratio (MR) decreased and drying time and effective moisture diffusivity increased with respect to the thickness of the puree. In addition, the Lewis model and the Wang and Singh model showed the highest R2 and lowest SEE value for RWD and CD, respectively. Moreover, the MR of onion puree during RWD and CD was predicted using a multi-layer feed-forward (MLF) artificial neural network (ANN) with a back-propagation algorithm. The result showed that the ANN model with 12 and 18 neurons in the hidden layer could predict the MR, with a high R2 value for RWD and CD, respectively. The results also showed that the thickness of the puree and drying method significantly affected the physicochemical quality (color characteristics, pyruvic acid content, total phenolic content, total flavonoid content, antioxidant capacity, and hygroscopicity) of onion powder. It was concluded that RWD proved to be a better drying method than CD in terms of the quality of dried powder and reduced drying time. Irrespective of the drying method, 2 mm-thick puree dried yielded the best-dried onion powder in terms of physicochemical quality, as well yielding the lowest drying time. These samples were further analyzed for calculating the glass transition temperature. Full article
(This article belongs to the Special Issue Mathematical Modeling of Drying Kinetics in Food and Biomass Processing)
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