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Processes
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Processes in Agri-Food Technology
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Processes in Agri-Food Technology

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

Deadline for manuscript submissions: 15 September 2025 | Viewed by 2468

Special Issue Editor

Dr. Jingfeng Huang

E-Mail Website
Guest Editor
Republic Polytechnic, School of Engineering, 9 Woodlands Ave 9, Singapore 738964, Singapore
Interests: electrochemical water splitting; sustainability; novel carbon materials; biosensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Special Issue “Processes in Agri-Food Technology” aims to explore innovative processes and engineering that enhance agrifood productivity, sustainability, and quality. This Issue invites original research and review articles that address advancements in food processing, agricultural engineering, smart farming, and the integration of IoT and AI in food systems. Topics may include but are not limited to novel food preservation methods, sustainable agricultural practices, resource optimization, and innovative processing engineering that contribute to global food security.

Dr. Jingfeng Huang
Guest Editor

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

  • agri-food productivity
  • sustainable and climate-resilient food systems
  • precision agriculture
  • IoT and AI-enabled urban farming
  • food resiliency and security
  • food innovation and sustainability
  • waste valorisation for a circular food economy

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

Published Papers (4 papers)

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Research

16 pages, 3339 KiB  
Article
Impact of Spectral Irradiance Control on Bioactive Compounds and Color Preservation in Solar-Dried Papaya
by Diana Paola García-Moreira, Erick César López-Vidaña, Ivan Moreno and Lucía Delgadillo-Ruiz
Processes 2025, 13(7), 2311; https://doi.org/10.3390/pr13072311 - 20 Jul 2025
Viewed by 723
Abstract
The quality effects of spectral irradiance conditions during papaya (Carica papaya L.) drying were investigated using three different dryers: a solar dryer with dynamic irradiance control (SDIC), a cylindrical solar dryer (CSD), and a solar simulator dryer (SSD). This study builds upon [...] Read more.
The quality effects of spectral irradiance conditions during papaya (Carica papaya L.) drying were investigated using three different dryers: a solar dryer with dynamic irradiance control (SDIC), a cylindrical solar dryer (CSD), and a solar simulator dryer (SSD). This study builds upon previous PDLC film applications in solar drying by specifically examining its impact on phytochemical preservation and color degradation, addressing gaps in spectral-specific effects on food quality parameters. The drying conditions were as follows: a temperature of 50 °C for each method, 700 w/m2 for both SDIC and solar simulator dryers (SSD), and full solar irradiance for the cylindrical solar dryer (CSD). The cylindrical solar dryer exhibited 210 min of drying time due to higher solar irradiance than SDIC (300 min), while SSD lasted 180 min. Drying rates were highest for CSD (0.056 g H2O/g d.m. min−1), followed by SDIC (0.027 g H2O/g d.m. min−1). Color analysis revealed that CSD resulted in the most significant color degradation, followed by SSD and SDIC. This was attributed to the varying spectral composition of radiation in each method. The CSD, with a full solar spectrum, including higher UV and visible radiation, induced more pronounced color changes than SDIC, which received lower intensity radiation in these ranges. Chemical analyses showed that SSD samples had the highest antioxidant activity (1432.91 µmol TE/g dw by ABTS) and phenolic content (58.92 mg GAE/100 g), suggesting simulated conditions may better preserve certain phytochemicals. SDIC maintained better carotenoid-related color parameters while showing intermediate antioxidant levels (1084.09 µmol TE/g dw). These results demonstrate that irradiance control significantly impacts drying efficiency and quality parameters. Full article
(This article belongs to the Special Issue Processes in Agri-Food Technology)
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18 pages, 4067 KiB  
Article
Oxidative Degradation of Anthocyanins in Red Wine: Kinetic Characterization Under Accelerated Aging Conditions
by Khulood Fahad Saud Alabbosh, Violeta Jevtovic, Jelena Mitić, Zoran Pržić, Vesna Stankov Jovanović, Reem Ali Alyami, Maha Raghyan Alshammari, Badriah Alshammari and Milan Mitić
Processes 2025, 13(7), 2245; https://doi.org/10.3390/pr13072245 - 14 Jul 2025
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Abstract
The oxidative degradation of anthocyanins in red wine was investigated under controlled conditions using hydroxyl radicals generated in the presence of Cu (II) as a catalyst. A full factorial experimental design with 23 replicates was used to evaluate the effects of hydrogen peroxide [...] Read more.
The oxidative degradation of anthocyanins in red wine was investigated under controlled conditions using hydroxyl radicals generated in the presence of Cu (II) as a catalyst. A full factorial experimental design with 23 replicates was used to evaluate the effects of hydrogen peroxide concentration, catalyst dosage, and reaction temperature on anthocyanin degradation over a fixed time. Statistical analysis (ANOVA and multiple regression) showed that all three variables and the main interactions significantly affected anthocyanin loss, with temperature identified as the most influential factor. The combined effects were described by a first-order polynomial model. The activation energies for degradation ranged from 56.62 kJ/mol (cyanidin-3-O-glucoside) to 40.58 kJ/mol (peonidin-3-O-glucoside acetate). Increasing the temperature from 30 °C to 40 °C accelerated the degradation kinetics, almost doubled the rate constants and shortened the half-life of the pigments. At 40 °C, the half-lives ranged from 62.3 min to 154.0 min, depending on the anthocyanin structure. These results contribute to a deeper understanding of the stability of anthocyanins in red wine under oxidative stress and provide insights into the chemical behavior of derived pigments. The results are of practical importance for both oenology and viticulture and support efforts to improve the color stability of wine and extend the shelf life of grape-based products. Full article
(This article belongs to the Special Issue Processes in Agri-Food Technology)
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18 pages, 954 KiB  
Article
Phytochemical Value and Bioactive Properties of Sweet Potato Peel Across Varieties and Drying Techniques
by Gordana Ćetković, Anja Vučetić, Teodora Cvanić, Olja Šovljanski, Aleksandra Ranitović, Biljana Lončar, Vladimir Filipović and Vanja Travičić
Processes 2025, 13(7), 2004; https://doi.org/10.3390/pr13072004 - 25 Jun 2025
Viewed by 509
Abstract
The aim of the present study was to investigate how different drying techniques (lyophilization, convective drying, and osmotic dehydration) affect the phytochemical profile, biological activities, color parameters, and antimicrobial potential of sweet potato peel from four varieties (white, pink, orange, and purple). Lyophilized [...] Read more.
The aim of the present study was to investigate how different drying techniques (lyophilization, convective drying, and osmotic dehydration) affect the phytochemical profile, biological activities, color parameters, and antimicrobial potential of sweet potato peel from four varieties (white, pink, orange, and purple). Lyophilized orange peel showed the highest carotenoid content (21.31 mg β-carotene/100 g), while osmotic dehydration resulted in the highest retention of anthocyanins in purple peel (229.58 mg cyanidin-3-glucoside/100 g). Among phenolic compounds, the most abundant were caffeic and cinnamic acids, reaching up to 434.57 mg/100 g and 430.91 mg/100 g, respectively, in white peel. Antioxidant activity was strongest in purple peel, particularly in lyophilized samples. Convective drying enhanced anti-inflammatory activity in orange peel (68.25% inhibition), and all samples demonstrated significant α-glucosidase inhibition, with values up to 96.93%. Antimicrobial effects were observed only in purple peel extracts, which showed strong antifungal activity, especially against Saccharomyces cerevisiae (inhibition zone >50 mm). These results confirm that sweet potato peel holds considerable potential as a functional ingredient and that its bioactive value can be significantly influenced by the drying method applied. Full article
(This article belongs to the Special Issue Processes in Agri-Food Technology)
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25 pages, 36638 KiB  
Article
Integrating Machine Learning and In Vitro Screening to Evaluate Drought and Temperature Stress Responses for Vicia Species
by Onur Okumuş, Özhan Şimşek, Musab A. Isak, Nilüfer Koçak Şahin, Adnan Aydin, Barış Eren, Fatih Demirel, Cansu Telci Kahramanoğulları, Satı Uzun and Mehmet Yaman
Processes 2025, 13(6), 1845; https://doi.org/10.3390/pr13061845 - 11 Jun 2025
Viewed by 711
Abstract
Drought and temperature extremes are major abiotic stressors limiting legume productivity worldwide. This study investigates the germination and early seedling responses of six cultivars belonging to three Vicia species (V. sativa, V. pannonica, and V. narbonensis) under varying levels [...] Read more.
Drought and temperature extremes are major abiotic stressors limiting legume productivity worldwide. This study investigates the germination and early seedling responses of six cultivars belonging to three Vicia species (V. sativa, V. pannonica, and V. narbonensis) under varying levels of polyethylene glycol (PEG)-induced drought and temperature conditions (12 °C, 18 °C, and 24 °C) in vitro. Significant cultivar-dependent differences were observed in the germination rate (GR), shoot and root length (SL and RL), fresh and dry weight (FW and DW), and vigor index (VI). The Ayaz cultivar exhibited superior performance, particularly under severe drought (10% PEG) and optimal temperature (24 °C), while Özgen and Balkan were most sensitive to stress. Principal component and correlation analyses revealed strong associations between the vigor index, shoot height, and fresh and dry weight, particularly in high-performing genotypes. To further model and predict stress responses, four machine learning (ML) algorithms—Random Forest (RF), k-Nearest Neighbors (k-NNs), Multilayer Perceptron (MLP), and Support Vector Machines (SVMs)—were employed. Based on model performance metrics, and considering high R2 values along with low RMSE and MAE values, the MLP model demonstrated the most accurate predictions for the GR (R2 = 0.95, RMSE = 0.06, MAE = 0.05) and VI (R2 = 0.99, RMSE = 0.02, MAE = 0.01) parameters. In contrast, the RF model yielded the best results for the SL (R2 = 0.98, RMSE = 0.02, MAE = 0.02) and DW (R2 = 0.93, RMSE = 0.06, MAE = 0.04) parameters, while the highest prediction accuracy for the RL (R2 = 0.83, RMSE = 0.09, MAE = 0.07) and FW (R2 = 0.97, RMSE = 0.05, MAE = 0.03) parameters was achieved using the SVM model. Comparative analysis with recent studies confirmed the applicability of ML in stress physiology and genotype screening. This integrative approach offers a robust framework for genotype selection and stress tolerance modeling in legumes, contributing to developing climate-resilient crops. Full article
(This article belongs to the Special Issue Processes in Agri-Food Technology)
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