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Biosensors
Special Issues
Biosensing Strategies for Food Safety Applications
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Biosensing Strategies for Food Safety Applications

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Environmental Biosensors and Biosensing".

Deadline for manuscript submissions: 20 May 2025 | Viewed by 932

Special Issue Editor

Dr. Hongmei Cao

E-Mail Website
Guest Editor
School of Food Science and Engineering, Hainan University, Haikou 570228, China
Interests: electrochemical and colorimetric biosensing based on single-atom nanozyme for food safety detection; nucleic acid amplification integrated microfluidics chip for pathogen detection in food

Special Issue Information

Dear Colleagues,

In recent decades, the development of biosensors for food safety applications has been a rapidly evolving field, with ongoing research efforts focused on enhancing sensitivity, selectivity, and reliability. Advances in nanotechnology, biotechnology, and material science have enabled the design and fabrication of novel biosensors with improved performance characteristics. Additionally, the integration of biosensors with emerging technologies, such as smartphone-based platforms and Internet of Things (IoT) devices, has the potential to revolutionize the field of food safety testing.

This Special Issue aims to highlight the latest developments in biosensing strategies for food safety applications, showcasing cutting-edge research and innovations in the field. Contributions are invited on topics including, but not limited to, the following:

  • Novel biosensors for the detection of foodborne pathogens, such as immunosensors, aptasensors, microbe-based sensors, peptide-based sensors, optical sensors, etc.;
  • Biosensing technologies for the rapid detection of chemical contaminants in food, for example, microfluidic technology, lateral flow strips, SERS, electrochemiluminescence, bio-chips, etc.;
  • Integration of biosensors with emerging materials for enhanced food safety, containing nanozyme, metal nanoparticles, quantum dots, GO, etc.;
  • Biosensing approaches for monitoring food quality and authenticity, including testing antibodies, heavy metals, pesticides, veterinary drugs, etc.;
  • Field-deployable biosensors for on-site food safety testing, like smartphone-based or IoT-based biosensors.

We look forward to receiving insightful contributions to this Special Issue.

Dr. Hongmei Cao
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. Biosensors 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 2700 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

  • biosensors
  • food safety
  • pathogen
  • antibody
  • immunosensor
  • nanozyme
  • electrochemiluminescence

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

Published Papers (2 papers)

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Research

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23 pages, 4548 KiB  
Article
Intelligent Evaluation and Dynamic Prediction of Oysters Freshness with Electronic Nose Non-Destructive Monitoring and Machine Learning
by Baichuan Wang, Yueyue Li, Kang Liu, Guangfen Wei, Aixiang He, Weifu Kong and Xiaoshuan Zhang
Biosensors 2024, 14(10), 502; https://doi.org/10.3390/bios14100502 - 14 Oct 2024
Viewed by 285
Abstract
Physiological and environmental fluctuations in the oyster cold chain can lead to quality deterioration, highlighting the importance of monitoring and evaluating oyster freshness. In this study, an electronic nose was developed using ten partially selective metal oxide-based gas sensors for rapid freshness assessment. [...] Read more.
Physiological and environmental fluctuations in the oyster cold chain can lead to quality deterioration, highlighting the importance of monitoring and evaluating oyster freshness. In this study, an electronic nose was developed using ten partially selective metal oxide-based gas sensors for rapid freshness assessment. Simultaneous analyses, including GC-MS, TVBN, microorganism, texture, and sensory evaluations, were conducted to assess the quality status of oysters. Real-time electronic nose measurements were taken at various storage temperatures (4 °C, 12 °C, 20 °C, 28 °C) to thoroughly investigate quality changes under different storage conditions. Principal component analysis was utilized to reduce the 10-dimensional vectors to 3-dimensional vectors, enabling the clustering of samples into fresh, sub-fresh, and decayed categories. A GA-BP neural network model based on these three classes achieved a test data accuracy rate exceeding 93%. Expert input was solicited for performance analysis and optimization suggestions enhanced the efficiency and applicability of the established prediction system. The results demonstrate that combining an electronic nose with quality indices is an effective approach for diagnosing oyster spoilage and mitigating quality and safety risks in the oyster industry. Full article
(This article belongs to the Special Issue Biosensing Strategies for Food Safety Applications)

Review

Jump to: Research

24 pages, 8540 KiB  
Review
A Review of Advanced Sensor Technologies for Aquatic Products Freshness Assessment in Cold Chain Logistics
by Baichuan Wang, Kang Liu, Guangfen Wei, Aixiang He, Weifu Kong and Xiaoshuan Zhang
Biosensors 2024, 14(10), 468; https://doi.org/10.3390/bios14100468 - 30 Sep 2024
Viewed by 568
Abstract
The evaluation of the upkeep and freshness of aquatic products within the cold chain is crucial due to their perishable nature, which can significantly impact both quality and safety. Conventional methods for assessing freshness in the cold chain have inherent limitations regarding specificity [...] Read more.
The evaluation of the upkeep and freshness of aquatic products within the cold chain is crucial due to their perishable nature, which can significantly impact both quality and safety. Conventional methods for assessing freshness in the cold chain have inherent limitations regarding specificity and accuracy, often requiring substantial time and effort. Recently, advanced sensor technologies have been developed for freshness assessment, enabling real-time and non-invasive monitoring via the detection of volatile organic compounds, biochemical markers, and physical properties. The integration of sensor technologies into cold chain logistics enhances the ability to maintain the quality and safety of aquatic products. This review examines the advancements made in multifunctional sensor devices for the freshness assessment of aquatic products in cold chain logistics, as well as the application of pattern recognition algorithms for identification and classification. It begins by outlining the categories of freshness criteria, followed by an exploration of the development of four key sensor devices: electronic noses, electronic tongues, biosensors, and flexible sensors. Furthermore, the review discusses the implementation of advanced pattern recognition algorithms in sensor devices for freshness detection and evaluation. It highlights the current status and future potential of sensor technologies for aquatic products within the cold chain, while also addressing the significant challenges that remain to be overcome. Full article
(This article belongs to the Special Issue Biosensing Strategies for Food Safety Applications)
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