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Biosensors
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Advanced Biosensors for Food and Agriculture Safety
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Advanced Biosensors for Food and Agriculture Safety

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensor Materials".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 4997

Special Issue Editors

Dr. Zhaoyang Ding

E-Mail Website
Guest Editor
College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China
Interests: fluorescence wensors; MOFs; food safety; nanomaterials
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Huilin Liu

E-Mail Website
Guest Editor
School of Food and Health, Beijing Technology and Business University, Beijng 10000, China
Interests: food analysis; food biosensing; food safety rapid sensing; food safety control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ensuring the safety and quality of food and agricultural products is crucial for managing global challenges such as population growth, climate change, and complex supply chains. Contamination from pathogens, pesticides, toxins, and environmental pollutants poses significant risks to both public health and economic stability. In this regard, advanced biosensors are transformative, offering rapid, accurate, and portable solutions for real-time hazard detection in food and agriculture. Recent advancements in nanotechnology have further enhanced the sensitivity, specificity, and scalability of these sensors. This Special Issue, "Advanced Biosensors for Food and Agriculture Safety," explores the latest developments in biosensor design, application, and commercialization. It aims to cover the application of biosensors in detecting foodborne pathogens, pesticide residues, food additives, and environmental contaminants in agricultural products. It also seeks to highlight advancements in optical, electrochemical, and wearable biosensors that enable onsite detection, improving food safety, reducing reliance on traditional lab-based methods, and ensuring transparency in the food supply chain. Researchers are invited to submit original studies, reviews, and perspectives that address current challenges and future opportunities in using biosensing technologies to create safer and more sustainable food systems.

Dr. Zhaoyang Ding
Prof. Dr. Huilin Liu
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 250 words) can be sent to the Editorial Office for assessment.

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 2200 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
  • agricultural safety
  • pathogen detection
  • pesticide residues
  • food additives
  • nanotechnology
  • real-time analysis
  • food supply chain

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Published Papers (4 papers)

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Research

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15 pages, 3317 KB  
Article
Research on Optimizing Electronic Nose Sensor Arrays for Oyster Cold Chain Detection Based on Multi-Algorithm Collaborative Optimization
by Yirui Kong, Zhenhua Guo, Weifu Kong, Hongjuan Li, Xinrui Li, Xiaoshuan Zhang, Xinzhe Liu, Ruihan Wu and Baichuan Wang
Biosensors 2025, 15(12), 772; https://doi.org/10.3390/bios15120772 - 25 Nov 2025
Viewed by 674
Abstract
Real-time quality monitoring during oyster cold chain transportation is a critical component in ensuring food safety. Addressing the issues of high redundancy and insufficient environmental adaptability in existing electronic nose systems, this study proposes a multi-algorithm collaborative optimization strategy for sensor array optimization. [...] Read more.
Real-time quality monitoring during oyster cold chain transportation is a critical component in ensuring food safety. Addressing the issues of high redundancy and insufficient environmental adaptability in existing electronic nose systems, this study proposes a multi-algorithm collaborative optimization strategy for sensor array optimization. The system integrates ten gas sensors (TGS series, MQ series), employing Random Forest (RFA), Simulated Annealing (SA), and Genetic Quantum Particle Swarm Optimization (GA-QPSO) for sensor selection. KNN combined with K-means analysis validates the optimization outcomes. Under cold chain environments at 4 °C, 12 °C, 20 °C, and 28 °C, a multidimensional dataset was constructed by extracting global variables using feature correlation functions. Experiments demonstrate that the optimized sensor count decreases from 10 to 5–6 units while maintaining recognition accuracy above 95%, with redundancy decreased by over 40%. This multi-algorithm collaborative optimization effectively balances sensor array recognition precision, resource efficiency, and environmental adaptability, providing an intelligent, high-precision technical solution for oyster cold chain monitoring. Full article
(This article belongs to the Special Issue Advanced Biosensors for Food and Agriculture Safety)
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14 pages, 1284 KB  
Article
Non-Enzymatic Selective Detection of Histamine in Fishery Product Samples on Boron-Doped Diamond Electrodes
by Hiroshi Aoki, Risa Miyazaki and Yasuaki Einaga
Biosensors 2025, 15(8), 489; https://doi.org/10.3390/bios15080489 - 29 Jul 2025
Cited by 1 | Viewed by 1757
Abstract
Histamine sensing that uses enzymatic reactions is the most common form of testing due to its selectivity for histamine. However, enzymes are difficult to store for long periods of time, and the inactivation of enzymes decreases the reliability of the results. In this [...] Read more.
Histamine sensing that uses enzymatic reactions is the most common form of testing due to its selectivity for histamine. However, enzymes are difficult to store for long periods of time, and the inactivation of enzymes decreases the reliability of the results. In this study, we developed a novel, quick, and easily operated histamine sensing technique that takes advantage of the histamine redox reaction and does not require enzyme-based processes. Because the redox potential of histamine is relatively high, we used a boron-doped diamond (BDD) electrode that has a wide potential window. At pH 8.4, which is between the acidity constant of histamine and the isoelectric point of histidine, it was found that an oxygen-terminated BDD surface successfully detected histamine, both selectively and exclusively. Measurements of the sensor’s responses to extracts from fish meat samples that contained histamine at various concentrations revealed that the sensor responds linearly to the histamine concentration, thus allowing it to be used as a calibration curve. The sensor was used to measure histamine in another fish meat sample treated as an unknown sample, and the response was fitted to the calibration curve to perform an inverse estimation. When estimated in this way, the histamine concentration matched the certified value within the range of error. A more detailed examination showed that the sensor response was little affected by the histidine concentration in the sample. The detection limit was 20.9 ppm, and the linear response range was 0–150 ppm. This confirms that this sensing method can be used to measure standard histamine concentrations. Full article
(This article belongs to the Special Issue Advanced Biosensors for Food and Agriculture Safety)
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Review

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21 pages, 1282 KB  
Review
Biosensors for Stress Detection: A Systematic Review from Herbaceous to Woody Plants
by Raffaella Margherita Zampieri, Alessandro Bizzarri, Eleftherios Touloupakis, Serena Laschi, Ilaria Palchetti, Claudia Cocozza and Alessio Giovannelli
Biosensors 2026, 16(5), 242; https://doi.org/10.3390/bios16050242 - 25 Apr 2026
Viewed by 836
Abstract
Plants must constantly adapt to biotic and abiotic stressors, which the global climate change crisis has intensified. To monitor plant health and predict their ability to face these challenges, various target molecules, such as hormones, glucose, and reactive oxygen species, are used as [...] Read more.
Plants must constantly adapt to biotic and abiotic stressors, which the global climate change crisis has intensified. To monitor plant health and predict their ability to face these challenges, various target molecules, such as hormones, glucose, and reactive oxygen species, are used as proxies for their physiological status. This review provides a systematic assessment of the current state of biosensor technology, an innovative analytical approach designed for in situ, minimally invasive, and real-time monitoring. Using the PICO (Problem, Intervention, Comparison, and Outcome) strategy, relevant research papers were identified. The review highlights how biosensors can detect physiological responses to stress before visual symptoms manifest, offering a significant advantage over traditional, often destructive, laboratory techniques, like gas chromatography–mass spectrometer (GC-MS) or high-performance liquid chromatography (HPLC). These advancements aim to improve precision agriculture and forestry management by providing sustainable methods to assess resilience in changing environments. Finally, the challenges of translating research from model organisms to complex woody species and choosing the correct target are discussed, and future perspectives, including the integration of biosensors with Artificial Intelligence-driven predictive models for large-scale environmental monitoring, are outlined. Full article
(This article belongs to the Special Issue Advanced Biosensors for Food and Agriculture Safety)
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58 pages, 1400 KB  
Review
Biosensors of Wine Fermentation for Monitoring Chemical and Biochemical Interactions, Process Indicators and Migration of Compounds and Metabolites, Between Wine and Fermentation Vessels—A Critical Review
by Vasileios D. Prokopiou, Aikaterini Karampatea, Zoi S. Metaxa and Alexandros V. Tsoupras
Biosensors 2026, 16(3), 153; https://doi.org/10.3390/bios16030153 - 10 Mar 2026
Cited by 2 | Viewed by 1166
Abstract
Wine alcoholic fermentation occurs in a dynamic biochemical environment where interactions between the vessel and the product can cause inorganic and organic species to migrate into the fermenting must or wine. At low pH and with rising ethanol levels, fermentation tanks made of [...] Read more.
Wine alcoholic fermentation occurs in a dynamic biochemical environment where interactions between the vessel and the product can cause inorganic and organic species to migrate into the fermenting must or wine. At low pH and with rising ethanol levels, fermentation tanks made of stainless steel, concrete or cementitious materials, ceramics, or polymers exhibit material-specific behaviors that may promote the release of toxic trace elements or alter technologically important ions. These changes can affect yeast physiology, fermentation kinetics, and matrix stability, directly impacting wine safety and quality. They may also influence the evolution of key fermentation metabolites and phenolic constituents, thereby affecting process performance, color development, oxidative stability, and other quality-related attributes. This review synthesizes current evidence on migration mechanisms and examines how vessel composition shapes the chemical and microbiological profile of fermentation. It also critically evaluates biosensor technologies—covering both biorecognition elements and signal-transduction strategies—and assesses the transition from laboratory prototypes to in situ or at-line implementations capable of detecting both migration-related events and process-relevant compositional changes with operational value for HACCP-based control. Electrochemical, optical, bienzymatic, and nanozyme-enabled platforms are discussed in terms of selectivity, matrix compatibility, and long-term functional stability under polyphenol and protein interference, CO2 variability, fouling and biofouling, and calibration drift. Particular attention is given to analytes associated with vessel-derived migrants and to biosensor targets related to fermentation metabolites and phenolic indicators, which support dynamic process monitoring and quality-focused decision making. Considering regulatory compliance requirements across the EU, US, and Asia, we propose a practical pathway for integrating biosensors into HACCP monitoring by treating vessel–product interactions as critical control points, while laboratory reference methods remain essential for verification and compliance documentation. Full article
(This article belongs to the Special Issue Advanced Biosensors for Food and Agriculture Safety)
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