Biosensors for Food Safety & Quality Inspection

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

Deadline for manuscript submissions: closed (15 April 2022) | Viewed by 2791

Special Issue Editors


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Guest Editor
Brussels Photonics Team, Department of Applied Physics and Photonics, Vrije Universiteit Brussel, 1050 Brussels, Belgium
Interests: lab-on-a-chip; optical biosensors; biosensing technology; antibody; ring resonators; Mach-Zehnder interferometer; surface plasmon resonance; microfluidic; Raman spectroscopy; fluorescence; cell viability; waveguide; organ-on-a-chip

Special Issue Information

Dear Colleagues,

During the last two decades, optical biosensors, in particular label-free optical biosensors, have become one of the most attractive biosensing techniques thanks to a number of unique characteristics such as the use of light and the excellent bioanalytical performance. Their applications in different domains gain momentum and cover various disciplines such as food safety, environmental monitoring, health care, and biosecurity.

The goal of this Special Issue “Biosensors for Food Safety and Quality Inspection” is to bring together novel biosensing technologies and optical detection approaches for monitoring food safety and quality. Moreover, we encourage researchers to demonstrate new applications of optical biosensors in the food supply chain, from production, to cultivation, to consumption. A wide range of possible analytes that are present in food enable the development of various types of optical biosensors based on waveguides, fibers, photonic crystals, nanoparticles, and free-form optics, combined with chemical surface functionalization techniques and/or biological recognition elements. Furthermore, portable lab-on-a-chip devices working with optical detection principles make possible fast, economic inspection of food quality at different points of the food supply chain.

We kindly invite you to share your work, expertise, insights, and latest results with the biosensor-research community in the form of research articles and reviews for this Special Issue.

Dr. Tatevik Chalyan
Dr. Sara Tombelli
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. 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

  • Optical biosensor
  • Interferometers
  • Microring resonators
  • Spectroscopy
  • Fluorescence mycroscopy
  • Antibiotics
  • Funghi
  • Aptamers
  • Antibodies
  • Fiber gratings
  • Nanoparticles
  • Photonic crystals
  • Mycotoxins
  • Limit of detection
  • Food quality

Published Papers (1 paper)

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Research

15 pages, 7192 KiB  
Article
Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine Ageing
by Tatevik Chalyan, Indy Magnus, Maria Konstantaki, Stavros Pissadakis, Zacharias Diamantakis, Hugo Thienpont and Heidi Ottevaere
Biosensors 2022, 12(4), 227; https://doi.org/10.3390/bios12040227 - 09 Apr 2022
Cited by 1 | Viewed by 2073
Abstract
Due to its physical, chemical, and structural properties, oakwood is widely used in the production of barrels for wine ageing. When in contact with the wine, oak continuously releases aromatic compounds such as lignin, tannin, and cellulose to the liquid. Due to the [...] Read more.
Due to its physical, chemical, and structural properties, oakwood is widely used in the production of barrels for wine ageing. When in contact with the wine, oak continuously releases aromatic compounds such as lignin, tannin, and cellulose to the liquid. Due to the release process, oak loses its characteristic aromatic compounds in time; hence, the flavour that it gives to the enclosed wine decreases for repeated wine refills and a barrel replacement is required. Currently, the estimation of the maximum number of refills is empirical and its underestimation or overestimation can impose unnecessary costs and impair the quality of the wine. Therefore, there is a clear need to quantify the presence of the aforementioned aromatic compounds in an oak barrel prior to a refill. This work constitutes a study to examine noninvasive optical biosensing techniques for the characterization of an oak barrel used in wine ageing, towards the development of a model to unveil its lifespan without inducing structural damage. Spectroscopic diagnostic techniques, such as reflectance, fluorescence, and Raman scattering measurements are employed to assess the change in the chemical composition of the oakwood barrel (tannin and lignin presence) and its dependence on repeated refills. To our knowledge, this is the first time that we present a benchmarking study of oak barrel ageing characteristics through spectroscopic methods for the wine industry. The spectroscopic data are processed using standard chemometric techniques, such as Linear Discriminant Analysis and Partial Least Squares Discriminant Analysis. Results of a study of fresh, one-time-used, and two-times-used oak barrel samples demonstrate that reflectance spectroscopy can be a valuable tool for the characterization of oak barrels. Moreover, reflectance spectroscopy has demonstrated the most accurate classification performance. The highest accuracy has been obtained by a Partial Least Squares Discriminant Analysis model that has been able to classify all the oakwood samples from the barrels with >99% accuracy. These preliminary results pave a way for the application of cost-effective and non-invasive biosensing techniques based on reflectance spectroscopy for oak barrels assessment. Full article
(This article belongs to the Special Issue Biosensors for Food Safety & Quality Inspection)
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