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Drying Kinetics and Quality Control in Food Processing, 2nd Edition

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

Deadline for manuscript submissions: closed (28 February 2026) | Viewed by 24837

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Prof. Dr. Won Byong Yoon

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Food Science and Biotechnology, Kangwon National University, Chuncheon 24341, Republic of Korea
Interests: mathematical modelling in food and bioprocesses; computer simulations; biopolymer rheology
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Meng-I Kuo (Marie)

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Guest Editor

Department of Food Science, Fu Jen Catholic University, New Taipei City 24205, Taiwan
Interests: novel food ingredients; innovative food processing technology; texture tailoring; sustainable upcycling
Special Issues, Collections and Topics in MDPI journals

Dr. Huai-Wen Yang

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Guest Editor

Department of Food Sceince, National Chiayi University, Chiayi City 60004, Taiwan
Interests: food engineering simulation; food texture modification; dysphagia-friendly formulation; sustainable processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The kinetic characteristics of food during dehydration play an important role in the final product quality, as well as the cost of the operation. The physico-chemical changes that occur during drying are highly related to the drying temperature and time, as well as the food compositions and matrix. The unstable properties of food could be improved under various drying conditions. Previous drying-related research has focused on characterizing the relationship between the moisture content changes and drying conditions, such as the drying temperature and time. The analytical, semi-empirical, and numerical models used to predict the moisture contents during drying have been well developed. However, relatively few studies on the mathematical or empirical analysis of the kinetic characteristics of food during rehydration have been reported. The kinetics characteristics of food are connected to the drying operations and the final quality of the dried food.

This Special Issue on "Drying Kinetics and Quality Control in Food Processing, 2nd Edition" aims to integrate novel advances in the mathematical modeling of the drying operations and kinetic changes in food. The topics include, but are not limited to, the following:

Integrated (or multidisciplinary) studies on quality changes in food or bioresource product during drying;
Novel technologies to control food quality during drying;
The optimization of the quality parameters involved in drying operations;
Fundamental and applied aspects of drying and dryers;
Transport phenomena in food- or bio-porous media;
The design, scale-up, and control of dryers in food or bioproduct processing.

Prof. Dr. Won Byong Yoon
Prof. Dr. Meng-I Kuo (Marie)
Dr. Huai-Wen Yang
Guest Editors

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Keywords

drying
kinetics
dehydration
rehydration
modeling
simulation
texture
shelf life
mass transfer
transport phenomena

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Published Papers (11 papers)

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Editorial

Jump to: Research

4 pages, 152 KB

Open AccessEditorial

Editorial: Advances in Drying Kinetics and Quality Control in Food Processing, 2nd Edition

by Won Byong Yoon

Processes 2026, 14(12), 1894; https://doi.org/10.3390/pr14121894 - 10 Jun 2026

Viewed by 266

Abstract

The second edition of the Special Issue, “Drying Kinetics and Quality Control in Food Processing”, serves as a comprehensive platform for discussing the latest innovations in dehydration technologies [...] Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

Research

Jump to: Editorial

17 pages, 279 KB

Open AccessArticle

Sorghum and Wheat-Based Extruded Aquatic Feed—Impact of Drying Parameters on Pellet Quality and Energy Efficiency

by Tucker Graff, Eric W. Maichel and Sajid Alavi

Processes 2026, 14(10), 1541; https://doi.org/10.3390/pr14101541 - 10 May 2026

Cited by 1 | Viewed by 476

Abstract

Energy consumption and different methods for determining energy efficiency were evaluated for drying of extruded rainbow trout feed pellets using a pilot-scale, heated air, integrated conveyor dryer and cooler. Impact of drying parameters on product quality, especially final moisture and pellet durability index (PDI), was also studied. From an initial moisture of 21.2 to 22.1% wet basis (wb), the drying–cooling process reduced the pellet moisture to 3.5 to 5.0% wb. Dryer throughput (82–121 kg/h) did not have statistically significant impact on final moisture (p = 0.0965) although the highest throughput corresponded to highest moisture; but increase in drying temperature from 93 to 115 °C led to a significant decrease in final moisture (p = 0.0285). Increase in dryer throughput led to a significant increase in PDI from 82.8 to 88.0% (p = 0.0003), while increase in drying temperature resulted in a slight decrease in PDI from 84.3 to 83.6%, although not statistically significant (p = 0.0811). Sorghum-based aquatic feed had a slightly lower PDI than wheat-based feed (82.8 versus 83.7%, respectively), but the difference was not statistically significant (p = 0.3009). Differences in pellet durability were attributed primarily to structural weakness induced by product shrinkage during drying, which in turn was impacted by drying rates. Specific energy consumption (SEC) during drying decreased from 136.3 to 101.1 MJ/kg-water with increase in throughput and increased from 122.5 to 150.1 MJ/kg-water with increase in drying temperature. An inverse trend was observed for various measures of dryer energy efficiency, with increase in efficiency for higher throughput and decrease for higher temperature. Sorghum-based aquatic feed had a higher drying SEC as compared to wheat-based feed and a lower energy efficiency. Overall, the results highlighted trade-offs between throughput, drying efficiency and pellet quality during drying of aquatic feeds. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

22 pages, 1481 KB

Open AccessArticle

Drying Kinetics and Variations in Chemical and Antioxidant Properties of Cauliflower (Brassica oleracea L. var. botrytis) at Different Vacuum Drying Temperatures

by Elsa Uribe, Jéssica López, Antonio Vega-Galvez, Nicol Mejias, Paz Hidalgo and Alexis Pasten

Processes 2026, 14(9), 1336; https://doi.org/10.3390/pr14091336 - 22 Apr 2026

Cited by 1 | Viewed by 646

Abstract

Vacuum drying is a promising alternative to conventional dehydration for heat-sensitive vegetables, although process temperature can significantly affect both drying behavior and product quality. In this study, vacuum drying of cauliflower florets (Brassica oleracea) was evaluated at 40, 50, 60, 70, and 80 °C under 10 kPa, using freeze-drying as a reference. Desorption isotherms were determined at 50 and 70 °C and fitted to common models, where the GAB model provided excellent fits (R² = 0.9999 and 0.9997, respectively). The drying kinetics were successfully described by four thin-layer models, with the Midilli–Kucuk and Weibull models performing best overall. Color was significantly affected, with total color differences (ΔE) ranging from 15.9 to 20.6 and higher browning indices at elevated temperatures. Bioactive compounds (total phenols, flavonoids, and glucosinolates) and antioxidant potential (by DPPH and ORAC assays) were quantified to assess changes in functional quality across treatments. Bioactive compounds showed the highest values at the highest temperatures (60–80 °C). The DPPH assay remained stable between 50 and 80 °C, but ORAC assay decreased with increasing temperature, suggesting that vacuum drying at 60–70 °C offers the best balance between overall bioactive retention and functionality for producing cauliflower powder. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

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32 pages, 4024 KB

Open AccessArticle

Mechanistic Modeling of Carrot Slice Drying: Lattice Boltzmann Simulation Coupled with Weibull-Based Quality Kinetics

by Monia Kheredine, Mohamed Hamdi and Daoued Mihoubi

Processes 2026, 14(7), 1169; https://doi.org/10.3390/pr14071169 - 4 Apr 2026

Cited by 2 | Viewed by 641

Abstract

The prediction of drying kinetics in hygroscopic biological materials remains challenging due to the strong coupling between internal moisture diffusion, evolving surface wettability, material deformation and thermolabile bioactive compounds degradation. In this context, periodic temperature variations are inherent to many industrial and solar drying systems, yet most experimental and modeling studies evaluate product quality under constant-temperature conditions. This work provides a demonstration that periodic drying can alter quality degradation pathways in ways that may not be captured by constant-temperature experiments. A coupled non-isothermal lattice Boltzmann method (LBM) model for heat and moisture transport was integrated with a Weibull kinetic formulation to describe the degradation of total carotenoids, total polyphenols, and antioxidant activity in carrot slices. Validation against experimental data across 50–70 °C demonstrates excellent agreement (R² > 0.96 for moisture ratio; quality retention within ±2% of the literature values). Seven drying scenarios were systematically evaluated: constant temperature (60 °C), fast and slow periodic oscillations, high-amplitude cycles, a mixed strategy combining constant initial drying with subsequent oscillations, and two intermittent ON/OFF profiles. Results reveal that while total polyphenol degradation within the present model is constrained to ~13.3% retention under the adopted kinetic parameters, carotenoid and antioxidant retention are highly sensitive to temperature history. The mixed strategy (60 °C for 2 h followed by 50–60 °C oscillations) achieves the highest quality retention (TC: 51.6%, AA: 34.4%) while requiring the lowest energy input (0.512 kJ), outperforming constant drying (TC: 48.8%, AA: 32.9%, 0.563 kJ). Conversely, high-amplitude intermittent drying (70/25 °C) accelerates carotenoid degradation (TC: 46.7%) despite shorter drying time (8.81 h), and low-amplitude intermittent cycling (65/55 °C) yields the poorest mean quality (31.4%) with the highest energy consumption (0.583 kJ). The framework reveals that oscillation frequency critically determines quality outcomes: slow cycles (8 h period) marginally improve retention, while fast cycles (2 h) offer no benefit over constant drying. These findings provide quantitative insights toward the design of drying strategies, demonstrating that optimal strategies must account for the coupling between temperature history and moisture-dependent vulnerability, with the mixed strategy emerging as the best-performing strategy among the tested scenarios. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

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19 pages, 539 KB

Open AccessFeature PaperEditor’s ChoiceArticle

Drying Kinetics and Physicochemical Characteristics of Dehydrated Jerusalem Artichoke (Helianthus tuberosus L.)

by Stanisław Rudy, Dariusz Dziki, Beata Biernacka, Renata Polak, Andrzej Krzykowski, Marek Domin, Grzegorz Rudzki and Magdalena Kachel-Górecka

Processes 2025, 13(8), 2553; https://doi.org/10.3390/pr13082553 - 13 Aug 2025

Cited by 3 | Viewed by 1634

Abstract

Jerusalem artichoke (Helianthus tuberosus L.) is a valuable source of inulin and fructooligosaccharides—compounds with well-documented prebiotic and functional food properties. However, its high moisture content significantly limits storage stability. This study aimed to assess the effects of drying method and process temperature on the drying kinetics and selected physicochemical properties of Jerusalem artichoke. Convective drying (AD) and combined convective–microwave drying (AMD), using a microwave power of 100 W, were employed. Drying was conducted at air temperatures of 40 °C, 60 °C, and 80 °C. Among the mathematical models evaluated, the Page model provided the best fit to the experimental drying data for both methods. Samples dried at 80 °C using the AMD technique exhibited the most pronounced changes in color, significant polyphenol losses, and a substantial reduction in antioxidant capacity compared to the fresh material. The lowest polyphenol degradation and the highest retention were observed in products dried at 40 °C using both AD and AMD methods. Notably, the AMD method significantly reduced drying time and improved the grindability of the dried Jerusalem artichoke samples. Although AMD contributed to certain quality deterioration, it also promoted a higher degree of particle size reduction. However, this increased degree of particle size reduction had only a limited effect on the extraction efficiency of fructooligosaccharides and inulin. The results of the present study suggest that AMD may serve as a competitive alternative to AD for drying Jerusalem artichoke, particularly when processing time and grindability are critical considerations. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

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21 pages, 1725 KB

Open AccessArticle

Impact of Ultrasound Pretreatment and Temperature on Drying Kinetics and Quality Characteristics of Blood Orange Slices: Comparison with Different Drying Methods

by Damla Yilmaz, Zeynep Hazal Tekin-Cakmak and Salih Karasu

Processes 2025, 13(5), 1596; https://doi.org/10.3390/pr13051596 - 20 May 2025

Cited by 8 | Viewed by 1925

Abstract

This study aimed to investigate the impact of ultrasonic pretreatment vacuum drying (UAVD) and temperature on drying kinetics and qualitative attributes of blood oranges in comparison to several drying methods: hot air drying (HAD), vacuum drying (VD), and freeze drying (FD). The drying kinetics and modeling, total phenolic content (TPC), antioxidant capability (assessed using DPPH and ABTS tests), individual phenolic profiles, vitamin C concentration, and color factors were meticulously examined. Drying times were recorded as 22.5 h, 12.5 h, and 9 h for HAD; 11.5 h, 9.5 h, and 8.5 h for VD; and 10 h, 8.5 h, and 7.5 h for UAVD at 50, 60, and 70 °C, respectively. The HAD, VD, and UAVD procedures were conducted at 50, 60, and 70 °C, resulting in reduced drying periods with increasing temperature. The integration of ultrasound markedly lowered drying durations. Eleven thin-layer drying models were utilized to recreate the drying process precisely. The D_eff values of the HAD, VD, and UAVD dried samples varied from 9.08 × 10⁻⁶ to 2.82 × 10⁻⁵ m²/s, from 2.60 × 10⁻⁵ to 2.96 × 10⁻⁵ m²/s, and from 2.20 × 10⁻⁵ to 2.99 × 10⁻⁵, respectively. Among the desiccated blood orange slices, the greatest total phenolic content (TPC) was observed in freeze-dried samples (131.27 mg GAE/100 g), followed by those dried using ultrasonic-assisted vacuum drying (UAVD) at 50 °C (128.77 mg GAE/g DM). Dried blood orange slices had a vitamin C content of 29.79 to 49.01 mg/100. The drying process substantially impacted the color parameters L*, a*, and b*. These findings highlight the efficacy of ultrasound-assisted drying in decreasing drying duration while improving the retention of bioactive components in blood orange slices. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

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18 pages, 11416 KB

Open AccessArticle

Monitoring Agitation Intensity in Fluidized Beds Containing Inert Particles via Acoustic Emissions and Neural Networks

by Willian Velloso Metzner and Gustavo Cesar Dacanal

Processes 2024, 12(12), 2691; https://doi.org/10.3390/pr12122691 - 29 Nov 2024

Cited by 4 | Viewed by 2550

Abstract

This study utilized passive acoustic emissions from a fluidized bed containing spherical inert ABS particles, captured by an external piezoelectric microphone, to monitor fluidization agitation intensity. Acoustic signals were recorded during fluidization profiles achieved under air velocities ranging from 0.5 to 3.0 m/s and during the drying of water or maltodextrin aqueous solution (1:5 w/w) introduced as droplets. Analyzing audio features like waveforms, the Discrete Fourier Transform (DFT), and Mel Frequency Cepstral Coefficients (MFCCs) revealed changes corresponding to the agitation intensity of the particles. The MFCC coefficients were input into a three-layer artificial neural network (ANN) to predict fluidization dynamics based on air velocity, liquid flow rate, and drying time. The ANN efficiently learned from the data, achieving high predictive accuracy (R² > 0.8) after 15 epochs of training, showcasing the robustness of MFCC coefficients for modeling. This approach highlights that the application of passive acoustic signals and neural networks allows for real-time monitoring of fluidization behavior during drying processes. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

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16 pages, 3875 KB

Open AccessArticle

Temperature Effect of Cocoa (Theobroma cacao L.) Drying on Energy Consumption, Bioactive Composition and Vibrational Changes

by David J. Jiménez-Rodríguez, Pedro García-Alamilla, Facundo J. Márquez-Rocha, Rubén Vázquez-Medina, Areli Carrera-Lanestosa, Fanny A. González-Alejo, Carlos A. Sánchez-Ramos and Franco L. Ruiz-Santiago

Processes 2024, 12(11), 2523; https://doi.org/10.3390/pr12112523 - 12 Nov 2024

Cited by 8 | Viewed by 6941

Abstract

Cocoa drying is the post-harvest thermal process used to condition the beans to a moisture content between 6.5 and 7% for storage and further processing. Convective drying is an energy-intensive process where time and temperature are considered critical factors for the degradation of bioactive compounds in edible products. In the present study, the energy parameters, vibrational spectroscopy, and changes in bioactive compounds of cocoa beans were studied during thin-layer hot air drying at 50 °C, 60 °C, and 70 °C. Moisture loss, specific energy consumption (SEC), energy efficiency, total phenolics (TPs), total flavonoids (TFs), and antioxidant activity (DPPH) were determined. Fourier transform infrared (FT-IR) spectroscopy with attenuated total reflectance (ATR) was used to characterize the samples, and a multivariate analysis was applied to find interactions among the components. The obtained SEC was 18,947.30–24,469.51 kJ/kg, and the energy efficiency was 9.73–12.31%. When the temperature was 70 °C, the best values for SEC and energy efficiency were obtained. The results also showed that the convective drying generated changes in the TP levels for the three temperatures, mainly after 300 min, with maximum levels between 360 and 600 min, at 70 °C; however, it does not have a clear relationship with the TFs and the antioxidant activity. The FT-IR and the multivariate analysis revealed changes in several signals in the 1800 to 400 cm⁻¹ range, confirming the variation in the associated signal with phenolic compounds. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

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12 pages, 2367 KB

Open AccessFeature PaperEditor’s ChoiceArticle

Optimization of Steaming Conditions for Bellflower Root (Platycodon grandiflorus) Using K-Means Clustering-Based Morphological Grading System

by Timilehin Martins Oyinloye, Seohee An, Chang-Won Cho and Won Byong Yoon

Processes 2024, 12(11), 2347; https://doi.org/10.3390/pr12112347 - 25 Oct 2024

Cited by 4 | Viewed by 1752

Abstract

Bellflower roots were categorized into three clusters (class 0, class 1, and class 2) using K-means clustering based on their morphological factors: length (282.8 ± 29.53, 138.75 ± 26.8, and 209.89 ± 20.49 mm), thickness (16.25 ± 2.82, 16.77 ± 3.35, and 16.52 ± 3.05 mm), and body shape coefficient (5.80 ± 1.15, 12.73 ± 4.82, and 7.95 ± 1.71). Internal void formation, a key quality factor for bellflower root, was analyzed under pre-steaming conditions, identifying temperatures between 20 and 25 °C as optimal for storage. Within the clustered class, steaming for a prolonged duration increased the formation of internal voids and caused a decrease in normal stress values, total dissolved solids (TDS), and pectin content. Class 0, with larger and thicker roots, exhibited higher internal voids (57% void rate) due to uneven heat distribution and incomplete starch gelatinization. Class 2 roots demonstrated better structural integrity, with a void rate of 26% and a stress value of 48 kN/m². These findings highlight the importance of morphological classification and optimal storage temperatures to improve the quality of steamed bellflower roots. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

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18 pages, 7952 KB

Open AccessArticle

Deep Learning Prediction of Moisture and Color Kinetics of Apple Slices by Long Short-Term Memory as Affected by Blanching and Hot-Air Drying Conditions

by Zehui Jia, Yanhong Liu and Hongwei Xiao

Processes 2024, 12(8), 1724; https://doi.org/10.3390/pr12081724 - 16 Aug 2024

Cited by 21 | Viewed by 3891

Abstract

This study aimed to improve apple slices’ color and drying kinetics by optimizing the hot-air drying process, utilizing machine and deep learning models. Different steam blanching times (30, 60, 90, and 120 s), drying temperatures (50, 55, 60, 65, and 70 °C), and humidity control methods (full humidity removal or temperature–humidity control) were examined. These factors significantly affected the quality of apple slices. 60 s blanching, 60 °C temperature, and full dehumidification represented the optimal drying conditions for apple slices’ dehydration, achieving better drying kinetics and the best color quality. However, the fastest drying process (40 min) was obtained at a 60 °C drying temperature combined with complete dehumidification after 90 s blanching. Furthermore, machine and deep learning models, including backpropagation (BP), convolutional neural network–long short-term memory (CNN-LSTM), temporal convolutional network (TCN), and long short-term memory (LSTM) networks, effectively predicted the moisture content and color variation in apple slices. Among these, LSTM networks demonstrated exceptional predictive performance with an R² value exceeding 0.98, indicating superior accuracy. This study provides a scientific foundation for optimizing the drying process of apple slices and illustrates the potential application of deep learning in the agricultural processing and engineering fields. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

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15 pages, 770 KB

Open AccessArticle

Modifications on the Processing Parameters of Traditional Pineapple Slices by Stabilized Sound Pressure of Multiple Frequency Ultrasonic-Assisted Osmotic Dehydration

by Yu-Wen Lin, Yueh-An Yao, Da-Wei Huang, Chung-Jen Chen and Ping-Hsiu Huang

Processes 2024, 12(6), 1109; https://doi.org/10.3390/pr12061109 - 28 May 2024

Cited by 11 | Viewed by 2574

Abstract

This study investigated the practical feasibility of synergistically and optimally applying ultrasound-assisted osmotic dehydration (UAOD) practices for the pineapple slice picking process (in sugar osmotic solution), with potential implications for improving current practices. This study was carried out to evaluate the effects of different treatment conditions of single (40 and 80 kHz)/multiple (40/80 kHz) frequencies, output powers (300, 450, and 600 W), and treatment time (5–40 min) at 30, 45, and 60 °Brix applied, respectively, on the pineapple slices picking process. The sound pressure of the UA was also measured to confirm that it provided the corresponding effect stably under different conditions. The ideal UAOD operating condition for pineapple slices is a 45 °Brix sugar osmotic solution, with frequency multiplexing at 40/80 kHz and an output power of 450 W for 25 min, which yields the optimal solids gain (SG) rate of 7.58%. The above results of this study indicated that UAOD could improve the accelerated quality transfer of pineapple slices and enhance the final product quality, thereby increasing the efficiency of the dehydration process and saving processing costs and time. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing, 2nd Edition)

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