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Nanomaterials and Nanotechnology in Food: Applicability, Functionality, and Safety—2nd Edition
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Nanomaterials and Nanotechnology in Food: Applicability, Functionality, and Safety—2nd Edition

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Engineering and Technology".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 4987

Special Issue Editors

Dr. Qinzhi Wang

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Guest Editor
College of Food Science and Engineering, Qingdao Agricultural University, Qingdao 266109, China
Interests: SERS; biosensors; nanomaterials; food analysis; food safety
Special Issues, Collections and Topics in MDPI journals
Dr. Ying Gu

E-Mail Website
Guest Editor
Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, China
Interests: food safety; sensing analysis; signal amplification; advanced functional materials; AI in food safety
Special Issues, Collections and Topics in MDPI journals
Dr. Wenxin Zhu

E-Mail Website
Guest Editor
College of Food Science and Engineering, Northwest A&F University, Yangling, China
Interests: nanomaterials and nanotechnology in food; Electrochemical technology in food
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Food safety is a main research hotspot in food science regarding human health and is currently a global public health concern. Contaminants in food, such as foodborne pathogenic micro-organisms, pesticides, veterinary drug residues, toxins, and illegal additives that are produced during food processing and preservation, threaten human health. Developing advanced techniques for the reliable detection and control of these food contaminants is thus very important for food safety.

The applications of nanomaterials and nanotechnology in food science and engineering have received increasing attention. Some typical applications include nanocatalyst-based electrochemical/colorimetric/fluorescent sensing platforms, nanocatalyst-based advanced oxidation processes, nanomaterial-embedded packaging films, nanomaterial-based active ingredient delivery platforms, nanozyme-based sensing platforms and sanitizers, nanomaterials for food sample pretreatment, and other novel electro-/photo-catalysis techniques in food science. Furthermore, training complex models based on artificial intelligence (AI) frameworks enables the prediction of intricate relationships and the execution of more complex tasks, which contributes to making decisions from complex or large datasets in food safety analysis.

Here, we cordially invite authors to contribute original research articles or review articles covering the most recent progress in the application of nanomaterials and nanotechnology in food, as well as food safety analytical methods based on traditional machine learning or deep learning approaches.

Dr. Qinzhi Wang
Dr. Ying Gu
Dr. Wenxin Zhu
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. Foods is an international peer-reviewed open access semimonthly 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 2900 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

  • nanomaterials
  • nanotechnology
  • nanocatalysis
  • foods
  • food nutrition
  • food micro-organisms
  • artificial intelligence

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Published Papers (3 papers)

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Research

15 pages, 6161 KiB  
Article
Screening of a Fraction with Higher Amyloid β Aggregation Inhibitory Activity from a Library Containing 210 Mushroom Extracts Using a Microliter-Scale High-Throughput Screening System with Quantum Dot Imaging
by Gegentuya Huanood, Mahadeva M. M. Swamy, Rina Sasaki, Keiya Shimamori, Masahiro Kuragano, Enkhmaa Enkhbat, Yoshiko Suga, Masaki Anetai, Kenji Monde and Kiyotaka Tokuraku
Foods 2024, 13(23), 3740; https://doi.org/10.3390/foods13233740 - 22 Nov 2024
Viewed by 1271
Abstract
Alzheimer’s disease (AD) is a highly prevalent neurodegenerative disease hallmarked by amyloid plaques and neurofibrillary tangles. Amyloid plaques are formed by the amyloid β (Aβ) aggregation, so substances that inhibit this aggregation are useful for preventing and treating AD. Mushrooms are widely used [...] Read more.
Alzheimer’s disease (AD) is a highly prevalent neurodegenerative disease hallmarked by amyloid plaques and neurofibrillary tangles. Amyloid plaques are formed by the amyloid β (Aβ) aggregation, so substances that inhibit this aggregation are useful for preventing and treating AD. Mushrooms are widely used medicinal fungi with high edible and nutritional value. Mushrooms have a variety of biologically active ingredients, and studies have shown that they have certain effects in anti-bacterial, anti-oxidation, anti-inflammatory, anti-tumor, and immune regulation. Previously, we developed a microliter-scale high-throughput screening (MSHTS) system using quantum dot (QD) nanoprobes to screen Aβ aggregation inhibitors. In this study, we appraised the Aβ aggregation inhibitory activity of 210 natural mushrooms from Hokkaido (Japan) and found 11 samples with high activity. We then selected Elfvingia applanata and Fuscoporia obliqua for extraction and purification as these samples were able to suppress Aβ-induced neurocytotoxicity and were readily available in large quantities. We found that the ethyl acetate (EtOAc) extract of E. applanata has high Aβ aggregation inhibitory activity, so we performed silica gel column chromatography fractionation and found that fraction 5 (f5) of the EtOAc extract displayed the highest Aβ aggregation inhibitory activity among all mushroom samples. The half-maximal effective concentration (EC50) value was 2.30 µg/mL, higher than the EC50 of 10.7 µg/mL for rosmarinic acid, a well-known Aβ aggregation inhibitor. This inhibitory activity decreased with further purification, suggesting that some compounds act synergistically. The f5 fraction also inhibited the deposition of Aβ aggregates on the cell surface of human neuroblastoma SH-SY5Y cells. Our expectation is that f5, with additional tests, may eventually prove to be an inhibitor for the prevention of AD. Full article
(This article belongs to the Special Issue Nanomaterials and Nanotechnology in Food: Applicability, Functionality, and Safety—2nd Edition)
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14 pages, 2059 KiB  
Article
Classification and Identification of Foodborne Bacteria in Beef by Utilising Surface-Enhanced Raman Spectroscopy Coupled with Chemometric Methods
by Huixin Zuo, Yingying Sun, Mingming Huang, Stephanie Marie Fowler, Jing Liu, Yimin Zhang and Yanwei Mao
Foods 2024, 13(22), 3688; https://doi.org/10.3390/foods13223688 - 19 Nov 2024
Viewed by 1063
Abstract
The detection and classification of foodborne pathogenic bacteria is crucial for food safety monitoring, consequently requiring rapid, accurate and sensitive methods. In this study, the surface-enhanced Raman spectroscopy (SERS) technique coupled with chemometrics methods was used to detect and classify six kinds of [...] Read more.
The detection and classification of foodborne pathogenic bacteria is crucial for food safety monitoring, consequently requiring rapid, accurate and sensitive methods. In this study, the surface-enhanced Raman spectroscopy (SERS) technique coupled with chemometrics methods was used to detect and classify six kinds of foodborne pathogenic bacteria, including Salmonella typhimurium (S. typhimurium), Escherichia coli (E. coli) O157:H7, Staphylococcus aureus (S. aureus), Listeria monocytogenes (L. monocytogenes), Listeria innocua (L. innocua), and Listeria welshimeri (L. welshimeri). First, silver nanoparticles (AgNPs) with different particle sizes were prepared as SERS-enhanced substrates by changing the concentration of sodium citrate, and the volume ratio of silver nanosol to bacterial solution was optimised to obtain the optimal SERS signal. Then, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to classify the SERS spectra of six bacteria at three classification levels (Gram type level, genus level and species level), and appropriate classification models were established. Finally, these models were validated on 540 spectra using linear discriminant analysis (LDA), achieving an average accuracy of 95.65%. Overall, it was concluded that the SERS technique combined with chemometrics methods could achieve the rapid detection and classification identification of foodborne pathogenic bacteria, providing an effective means for food safety monitoring. Full article
(This article belongs to the Special Issue Nanomaterials and Nanotechnology in Food: Applicability, Functionality, and Safety—2nd Edition)
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21 pages, 5959 KiB  
Article
Banana Peel Extract-Derived ZnO Nanopowder: Transforming Solar Water Purification for Safer Agri-Food Production
by Dušica Jovanović, Szabolcs Bognár, Vesna Despotović, Nina Finčur, Sandra Jakšić, Predrag Putnik, Cora Deák, Gábor Kozma, Branko Kordić and Daniela Šojić Merkulov
Foods 2024, 13(16), 2643; https://doi.org/10.3390/foods13162643 - 22 Aug 2024
Cited by 2 | Viewed by 1947
Abstract
Pure water scarcity is the most significant emerging challenge of the modern society. Various organics such as pesticides (clomazone, quinmerac), pharmaceuticals (ciprofloxacin, 17α-ethynilestradiol), and mycotoxins (deoxynivalenol) can be found in the aquatic environment. The aim of this study was to fabricate ZnO nanomaterial [...] Read more.
Pure water scarcity is the most significant emerging challenge of the modern society. Various organics such as pesticides (clomazone, quinmerac), pharmaceuticals (ciprofloxacin, 17α-ethynilestradiol), and mycotoxins (deoxynivalenol) can be found in the aquatic environment. The aim of this study was to fabricate ZnO nanomaterial on the basis of banana peel extract (ZnO/BPE) and investigate its efficiency in the photocatalytic degradation of selected organics under various experimental conditions. Newly synthesized ZnO/BPE nanomaterials were fully characterized by the XRD, FTIR, SEM-EPS, XPS, and BET techniques, which confirmed the successful formation of ZnO nanomaterials. The photocatalytic experiments showed that the optimal catalyst loading of ZnO/BPE was 0.5 mg/cm3, while the initial pH did not influence the degradation efficiency. The reusability of the ZnO/BPE nanomaterial was also tested, and minimal activity loss was found after three photocatalytic cycles. The photocatalytic efficiency of pure banana peel extract (BPE) was also studied, and the obtained data showed high removal of ciprofloxacin and 17α-ethynilestradiol. Finally, the influence of water from Danube River was also examined based on the degradation efficiency of selected pollutants. These results showed an enhanced removal of ciprofloxacin in water from the Danube River, while in the case of other pollutants, the treatment was less effective. Full article
(This article belongs to the Special Issue Nanomaterials and Nanotechnology in Food: Applicability, Functionality, and Safety—2nd Edition)
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