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AgriEngineering
Special Issues
Food Drying and Storage Technologies
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Food Drying and Storage Technologies

A special issue of AgriEngineering (ISSN 2624-7402).

Deadline for manuscript submissions: closed (21 June 2023) | Viewed by 19621

Special Issue Editor

Prof. Dr. Paulo Carteri Coradi

E-Mail Website
Guest Editor
Department Agricultural Engineering, Campus Cachoeira do Sul, Federal University of Santa Maria, Santa Maria, Brazil
Interests: postharvest, processing, drying, and storage of grains and cereals
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue seeks contributions covering all aspects of post-harvest research involving drying technology and food quality and storage technology and food quality. Topics include, but are not limited to, the following:

  • Mathematical modeling and computer modeling of food drying;
  • Design, scale-up, and control of drying food systems;
  • Drying instrumentation and control including sensors;
  • Innovative and emerging drying technologies of food;
  • Technical and economic aspects involving energy and the environment;
  • Post-harvest and food quality treatments;
  • Packaging processes including modified atmosphere, and intelligent packaging;
  • Food freezing and frozen food storage;
  • Food handling, distribution, and preservation;
  • Innovative and emerging storage technologies and food quality;
  • Sensors, Internet of Things and Artificial Intelligence applied to the storage of agricultural products.

Dr. Paulo Carteri Coradi
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. AgriEngineering is an international peer-reviewed open access quarterly 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 1600 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 and computer modeling of food drying
  • design, scale-up, and control of drying food systems
  • drying instrumentation and control including sensors
  • innovative and emerging drying technologies of food
  • post-harvest and food quality treatments
  • packaging processes including modified atmosphere and intelligent packaging
  • food freezing and frozen food storage
  • food handling, distribution, and preservation

Published Papers (4 papers)

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Research

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20 pages, 4683 KiB  
Article
Characterizing and Predicting the Quality of Milled Rice Grains Using Machine Learning Models
by Letícia de Oliveira Carneiro, Paulo Carteri Coradi, Dágila Melo Rodrigues, Roney Eloy Lima, Larissa Pereira Ribeiro Teodoro, Rosana Santos de Moraes, Paulo Eduardo Teodoro, Marcela Trojahn Nunes, Marisa Menezes Leal, Lhais Rodrigues Lopes, Tiago Arabites Vendrusculo, Jean Carlos Robattini, Anderson Henrique Soares and Nairiane dos Santos Bilhalva
AgriEngineering 2023, 5(3), 1196-1215; https://doi.org/10.3390/agriengineering5030076 - 4 Jul 2023
Cited by 3 | Viewed by 2040
Abstract
Physical classification is the procedure adopted by the rice unloading, delivery, storage, and processing units for the commercial characterization of the quality of the grains. This step occurs mostly by the conventional method, which demands more time and specialized labor, and the results [...] Read more.
Physical classification is the procedure adopted by the rice unloading, delivery, storage, and processing units for the commercial characterization of the quality of the grains. This step occurs mostly by the conventional method, which demands more time and specialized labor, and the results are subjective since the evaluation is visual. In order to make the operation faster, more accurate, and less dependent, non-destructive technologies and computational intelligence can be applied to characterize grain quality. Therefore, this study aimed to characterize and predict the quality of whole, processed rice grains, as well as classify any defects present. This was achieved by sampling from the upper and lower points of four silo dryers with capacities of up to 40,000 sacks. The grain samples had moisture contents of 16%, 17%, 18%, and 19% and were subjected to drying-aeration until reaching 12% moisture content (w.b.). Near-infrared spectroscopy technology and Machine Learning algorithm models (Artificial Neural Networks, decision tree algorithms Quinlan’s algorithm, Random Tree, REPTree, and Random Forest) were employed for this purpose. By analyzing Pearson’s correlation statistics, a strong negative correlation (R2 = 0.98) was found between moisture content and the yield of whole grains. Conversely, a strong positive correlation (R2 = 0.97) was observed between moisture content and classified physical defects across the various characterized physicochemical constituents. These findings indicate the effectiveness of near-infrared spectroscopy technology. The Random Tree model (RandT) successfully predicted the grain quality outcomes and is therefore recommended as the model of choice, obtained Pearson’s correlation coefficient (r = 0.96), mean absolute error (MAE = 0.017), and coefficient of determination (R2 = 0.92). The results obtained here reveal that the combination of near-infrared spectroscopy technology and Machine Learning algorithm models is an excellent non-destructive alternative to manual physical classification for characterizing the physicochemical quality of whole and defective rice grains. Full article
(This article belongs to the Special Issue Food Drying and Storage Technologies)
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12 pages, 2468 KiB  
Article
Drying of Gymnema sylvestre Using Far-Infrared Radiation: Antioxidant Activity and Optimization of Drying Conditions
by Gunaratnam Abhiram, Abhiram Briyangari and Rasu Eeswaran
AgriEngineering 2023, 5(1), 611-622; https://doi.org/10.3390/agriengineering5010038 - 9 Mar 2023
Cited by 2 | Viewed by 1797
Abstract
The leaf extracts of Gymnema sylvestre consist of secondary metabolites which are well known for antioxidant activity. This study aimed to measure the drying characteristics of G. sylvestre leaves under far-infrared radiation (FIR) and to optimize the specific energy consumption for drying and [...] Read more.
The leaf extracts of Gymnema sylvestre consist of secondary metabolites which are well known for antioxidant activity. This study aimed to measure the drying characteristics of G. sylvestre leaves under far-infrared radiation (FIR) and to optimize the specific energy consumption for drying and antioxidant activity of ethanol-water extract of dried leaves. Fresh leaves were harvested and exposed to combinations of four different temperatures (125, 150, 175 and 200 °C) and exposure times (5, 10, 15 and 20 min). Drying kinetics, energy consumption, color changes, total phenolic content (TPC) and antioxidant activities were quantified. Both temperature and drying time have significant (p < 0.05) effects on drying characteristics and antioxidant activity. The equilibrium moisture content was achieved at 200 °C and 18 min. The specific energy decreased and total color changes increased with temperature. Under lower temperatures (125 and 150 °C), TPC and antioxidant activity increased with exposure time, whereas higher exposure time (20 min) with high temperatures (175 and 200 °C) significantly decreased TPC and antioxidant activity. The highest TPC of 30.5 mg TAE/g leaf-fresh weight was achieved at 200 °C and 15 min. The optimal drying conditions achieved from the dissimilarity function method were 200 °C and 8.4 min. Full article
(This article belongs to the Special Issue Food Drying and Storage Technologies)
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23 pages, 3491 KiB  
Article
Phenolic Profiles, Antioxidant, Antibacterial Activities and Nutritional Value of Vietnamese Honey from Different Botanical and Geographical Sources
by Tri Nhut Pham, Thanh Viet Nguyen, Dang Truong Le, Le Minh Nhat Diep, Kieu Ngoan Nguyen, Thi Huynh Nhu To, Tien Hung Le and Quang Vinh Nguyen
AgriEngineering 2022, 4(4), 1116-1138; https://doi.org/10.3390/agriengineering4040069 - 14 Nov 2022
Cited by 5 | Viewed by 2498
Abstract
Honey is a natural product made by honeybees, its composition depends on factors such as climate, soil and plant source. In this study, the nutritional parameters, phenolic composition, antioxidant activity and antibacterial ability of 30 different types of honey of different botanical and [...] Read more.
Honey is a natural product made by honeybees, its composition depends on factors such as climate, soil and plant source. In this study, the nutritional parameters, phenolic composition, antioxidant activity and antibacterial ability of 30 different types of honey of different botanical and geographical origins in Vietnam were investigated. The study focused on the characterization and evaluation of the influence of plant origin and geographical location on physical–chemical properties and biological activities (antioxidant and antibacterial). The obtained results show that all honey samples meet quality standards according to international standards and Vietnamese standards, except for some exceptions recorded in moisture, 5-hydroxymethylfurfural (HMF) value and ash. These samples were explored for the detection of 13 polyphenols by using high-performance liquid chromatography (HPLC). The classification of honey samples collected from different regions and botanical sources was performed by principal component analysis (PCA), and it was observed that certain phenolic compounds contributed to the identification of honey samples. In addition, the correlation between physicochemical properties, chemical composition and biological activity of most honeys was also first clarified in this study. Overall, our data provide an overview data set and essential results in creating a database on the world honey trait map. Full article
(This article belongs to the Special Issue Food Drying and Storage Technologies)
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Review

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17 pages, 805 KiB  
Review
Application of Edible Coating in Extension of Fruit Shelf Life: Review
by Thanh Tung Pham, Lien Le Phuong Nguyen, Mai Sao Dam and Laszlo Baranyai
AgriEngineering 2023, 5(1), 520-536; https://doi.org/10.3390/agriengineering5010034 - 2 Mar 2023
Cited by 38 | Viewed by 12464
Abstract
In the past few decades, fruits have been increasingly consumed, leading to an increase in global fruit production. However, fresh produce is susceptible to large losses during production and preservation. In the postharvest preservation stage, fruits undergo various technical treatments for maintaining their [...] Read more.
In the past few decades, fruits have been increasingly consumed, leading to an increase in global fruit production. However, fresh produce is susceptible to large losses during production and preservation. In the postharvest preservation stage, fruits undergo various technical treatments for maintaining their quality. A widely adopted technology is the application of edible coatings, which can be applied to a diverse range of fruits to regulate the exchange of moisture and gases between the fruit and its environment. In addition, edible coatings provide a significant benefit by allowing the integration of different active ingredients into the coating’s matrix, meaning that these substances will associate with and possibly be eaten together with the fruit. This would help improve the organoleptic and nutritional qualities of the fruit as well as the shelf life. This paper provides an overview of the available data on the typical components used in coating matrix, focusing on the effect of the material combinations and application techniques to fruit properties. The processors can use this knowledge in choosing a suitable coating material and concentration for various fresh and fresh-cut fruits. Additionally, this paper reviews recent developments and limitations in utilizing edible coatings for prolonging the shelf-life of fruits. Full article
(This article belongs to the Special Issue Food Drying and Storage Technologies)
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