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Sensors for Food Safety and Quality 2019-2020

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (22 January 2021) | Viewed by 39812

Special Issue Editor

Special Issue Information

Dear Colleagues,

Food safety and quality is a critical factor for the nutrition and health of citizens. Thus, it is one of the most important research and regulatory topics. It includes issues such as the origin and traceability of food, quality labels, genetically modified organisms, fraud detection, ingredients, additives, nutrition and health claims, use of pesticides and herbicides, detection of contaminants or pathogens, food-borne diseases, shelf life, packaging, handling and transport, food processing, etc. It covers every single step from the farm to the fork.

Sensors are key tools for the analysis, detection, and monitoring in all these topics. Almost any kind of sensors (biosensors, optical or electrochemical sensors, etc.) have been reported for the analysis or monitoring of food safety and quality. However, it is a complicated area with several factors implied, intercorrelated, and difficult to track and control. Recently, single sensors have benefited from new tendencies, such as the combination of sensors in arrays, artificial intelligence, Internet of Things, intelligent packaging, smartphones or nanomaterials.

This Special Issue is dedicated to publishing articles that describe novel sensors for any topic related with food safety and quality. The topic also includes new tools and approaches that enhance sensor systems and facilitate their application in real environments. Therefore, articles reporting recent advances and reviews in food quality and safety, as well as closely-related topics, are welcome.

Dr. Jose V Ros-Lis
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. Sensors 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 2600 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

  • Sensor
  • Microbes
  • Toxins
  • Spoilage
  • Indicator
  • Safety
  • Quality
  • Food
  • Artificial intelligence
  • Smartphone
  • Arrays

Published Papers (7 papers)

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Research

Jump to: Review

17 pages, 812 KiB  
Article
Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics
by Tsung-Hsin Wu, I-Chun Tung, Han-Chun Hsu, Chih-Chun Kuo, Jenn-How Chang, Suming Chen, Chao-Yin Tsai and Yung-Kun Chuang
Sensors 2020, 20(19), 5451; https://doi.org/10.3390/s20195451 - 23 Sep 2020
Cited by 11 | Viewed by 2960
Abstract
Partially fermented tea such as oolong tea is a popular drink worldwide. Preventing fraud in partially fermented tea has become imperative to protect producers and consumers from possible economic losses. Visible/near-infrared (VIS/NIR) spectroscopy integrated with stepwise multiple linear regression (SMLR) and support vector [...] Read more.
Partially fermented tea such as oolong tea is a popular drink worldwide. Preventing fraud in partially fermented tea has become imperative to protect producers and consumers from possible economic losses. Visible/near-infrared (VIS/NIR) spectroscopy integrated with stepwise multiple linear regression (SMLR) and support vector machine (SVM) methods were used for origin discrimination of partially fermented tea from Vietnam, China, and different production areas in Taiwan using the full visible NIR wavelength range (400–2498 nm). The SMLR and SVM models achieved satisfactory results. Models using data from chemical constituents’ specific wavelength ranges exhibited a high correlation with the spectra of teas, and the SMLR analyses improved discrimination of the types and origins when performing SVM analyses. The SVM models’ identification accuracies regarding different production areas in Taiwan were effectively enhanced using a combination of the data within specific wavelength ranges of several constituents. The accuracy rates were 100% for the discrimination of types, origins, and production areas of tea in the calibration and prediction sets using the optimal SVM models integrated with the specific wavelength ranges of the constituents in tea. NIR could be an effective tool for rapid, nondestructive, and accurate inspection of types, origins, and production areas of teas. Full article
(This article belongs to the Special Issue Sensors for Food Safety and Quality 2019-2020)
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15 pages, 2115 KiB  
Article
An Artificial Neural Network Assisted Dynamic Light Scattering Procedure for Assessing Living Cells Size in Suspension
by Dan Chicea
Sensors 2020, 20(12), 3425; https://doi.org/10.3390/s20123425 - 17 Jun 2020
Cited by 12 | Viewed by 2928
Abstract
Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still be brought in simplifying [...] Read more.
Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still be brought in simplifying the experimental setup and in employing an easier to use data processing procedure for the acquired time-series. A DLS time series processing procedure based on an artificial neural network is presented with details regarding the design, training procedure and error analysis, working over an extended particle size range. The procedure proved to be much faster regarding time-series processing and easier to use than fitting a function to the experimental data using a minimization algorithm. Results of monitoring the long-time variation of the size of the Saccharomyces cerevisiae during fermentation are presented, including the 10 h between dissolving from the solid form and the start of multiplication, as an application of the proposed procedure. The results indicate that the procedure can be used to identify the presence of bigger particles and to assess their size, in aqueous suspensions used in the food industry. Full article
(This article belongs to the Special Issue Sensors for Food Safety and Quality 2019-2020)
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15 pages, 2915 KiB  
Article
Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum
by Paweł Piotr Konieczka, María José Aliaño-González, Marta Ferreiro-González, Gerardo F. Barbero and Miguel Palma
Sensors 2020, 20(11), 3123; https://doi.org/10.3390/s20113123 - 31 May 2020
Cited by 26 | Viewed by 4803
Abstract
Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified [...] Read more.
Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches. Full article
(This article belongs to the Special Issue Sensors for Food Safety and Quality 2019-2020)
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11 pages, 3463 KiB  
Article
Screen-Printed Voltammetric Biosensors for the Determination of Copper in Wine
by Liliana Norocel and Gheorghe Gutt
Sensors 2019, 19(21), 4618; https://doi.org/10.3390/s19214618 - 24 Oct 2019
Cited by 7 | Viewed by 2875
Abstract
Certain heavy metals present in wine, including copper, can form insoluble salts and can induce additional casse, so their determination is important for its quality and stability. In this context, a new biosensor for quantification of copper ions with BSA protein (bovine serum [...] Read more.
Certain heavy metals present in wine, including copper, can form insoluble salts and can induce additional casse, so their determination is important for its quality and stability. In this context, a new biosensor for quantification of copper ions with BSA protein (bovine serum albumin) and using SPE electrodes (screen-printed electrodes) is proposed. The objective of this research was to develop a miniaturized, portable, and low-cost alternative to classical methods. A potentiostat, which displays the response in the form of a cyclic voltammogram, was used in order to carry out this method. Values measured for the performance characteristics of the new biosensor revealed a good sensitivity (21.01 μA mM−1cm−2), reproducibility (93.8%), and limit of detection (0.173 ppm), suggesting that it has a high degree of application in the analysis proposed by our research. The results obtained for wine samples were compared with the reference method, atomic absorption spectrometer (AAS), and it was indicated that the developed biosensor is efficient and can be used successfully in the analysis of copper in wine. For the 20 samples of red wine analyzed with AAS, the concentration range of copper was between 0.011 and 0.695 mg/L and with the developed biosensor it was between 0.037 and 0.658 mg/L. Similar results were obtained for the 20 samples of white wine, 0.121–0.765 mg/L (AAS) and 0.192–0.789 mg/L (developed biosensor), respectively. Full article
(This article belongs to the Special Issue Sensors for Food Safety and Quality 2019-2020)
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Review

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34 pages, 2570 KiB  
Review
Current Trends and Challenges for Rapid SMART Diagnostics at Point-of-Site Testing for Marine Toxins
by Michael Dillon, Maja A. Zaczek-Moczydlowska, Christine Edwards, Andrew D. Turner, Peter I. Miller, Heather Moore, April McKinney, Linda Lawton and Katrina Campbell
Sensors 2021, 21(7), 2499; https://doi.org/10.3390/s21072499 - 3 Apr 2021
Cited by 26 | Viewed by 5609
Abstract
In the past twenty years marine biotoxin analysis in routine regulatory monitoring has advanced significantly in Europe (EU) and other regions from the use of the mouse bioassay (MBA) towards the high-end analytical techniques such as high-performance liquid chromatography (HPLC) with tandem mass [...] Read more.
In the past twenty years marine biotoxin analysis in routine regulatory monitoring has advanced significantly in Europe (EU) and other regions from the use of the mouse bioassay (MBA) towards the high-end analytical techniques such as high-performance liquid chromatography (HPLC) with tandem mass spectrometry (MS). Previously, acceptance of these advanced methods, in progressing away from the MBA, was hindered by a lack of commercial certified analytical standards for method development and validation. This has now been addressed whereby the availability of a wide range of analytical standards from several companies in the EU, North America and Asia has enhanced the development and validation of methods to the required regulatory standards. However, the cost of the high-end analytical equipment, lengthy procedures and the need for qualified personnel to perform analysis can still be a challenge for routine monitoring laboratories. In developing regions, aquaculture production is increasing and alternative inexpensive Sensitive, Measurable, Accurate and Real-Time (SMART) rapid point-of-site testing (POST) methods suitable for novice end users that can be validated and internationally accepted remain an objective for both regulators and the industry. The range of commercial testing kits on the market for marine toxin analysis remains limited and even more so those meeting the requirements for use in regulatory control. Individual assays include enzyme-linked immunosorbent assays (ELISA) and lateral flow membrane-based immunoassays (LFIA) for EU-regulated toxins, such as okadaic acid (OA) and dinophysistoxins (DTXs), saxitoxin (STX) and its analogues and domoic acid (DA) in the form of three separate tests offering varying costs and benefits for the industry. It can be observed from the literature that not only are developments and improvements ongoing for these assays, but there are also novel assays being developed using upcoming state-of-the-art biosensor technology. This review focuses on both currently available methods and recent advances in innovative methods for marine biotoxin testing and the end-user practicalities that need to be observed. Furthermore, it highlights trends that are influencing assay developments such as multiplexing capabilities and rapid POST, indicating potential detection methods that will shape the future market. Full article
(This article belongs to the Special Issue Sensors for Food Safety and Quality 2019-2020)
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23 pages, 1285 KiB  
Review
Bio-Based Sensors for Smart Food Packaging—Current Applications and Future Trends
by Carolina Rodrigues, Victor Gomes Lauriano Souza, Isabel Coelhoso and Ana Luísa Fernando
Sensors 2021, 21(6), 2148; https://doi.org/10.3390/s21062148 - 18 Mar 2021
Cited by 75 | Viewed by 12937
Abstract
Intelligent food packaging is emerging as a novel technology, capable of monitoring the quality and safety of food during its shelf-life time. This technology makes use of indicators and sensors that are applied in the packaging and that detect changes in physiological variations [...] Read more.
Intelligent food packaging is emerging as a novel technology, capable of monitoring the quality and safety of food during its shelf-life time. This technology makes use of indicators and sensors that are applied in the packaging and that detect changes in physiological variations of the foodstuffs (due to microbial and chemical degradation). These indicators usually provide information, e.g., on the degree of freshness of the product packed, through a color change, which is easily identified, either by the food distributor and the consumer. However, most of the indicators that are currently used are non-renewable and non-biodegradable synthetic materials. Because there is an imperative need to improve food packaging sustainability, choice of sensors should also reflect this requirement. Therefore, this work aims to revise the latest information on bio-based sensors, based on compounds obtained from natural extracts, that can, in association with biopolymers, act as intelligent or smart food packaging. Its application into several perishable foods is summarized. It is clear that bioactive extracts, e.g., anthocyanins, obtained from a variety of sources, including by-products of the food industry, present a substantial potential to act as bio-sensors. Yet, there are still some limitations that need to be surpassed before this technology reaches a mature commercial stage. Full article
(This article belongs to the Special Issue Sensors for Food Safety and Quality 2019-2020)
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20 pages, 2601 KiB  
Review
Nano-Biosensing Platforms for Detection of Cow’s Milk Allergens: An Overview
by Monika Nehra, Mariagrazia Lettieri, Neeraj Dilbaghi, Sandeep Kumar and Giovanna Marrazza
Sensors 2020, 20(1), 32; https://doi.org/10.3390/s20010032 - 19 Dec 2019
Cited by 42 | Viewed by 5937
Abstract
Among prevalent food allergies, cow milk allergy (CMA) is most common and may persist throughout the life. The allergic individuals are exposed to a constant threat due to milk proteins’ presence in uncounted food products like yogurt, cheese, and bakery items. The problem [...] Read more.
Among prevalent food allergies, cow milk allergy (CMA) is most common and may persist throughout the life. The allergic individuals are exposed to a constant threat due to milk proteins’ presence in uncounted food products like yogurt, cheese, and bakery items. The problem can be more severe due to cross-reactivity of the milk allergens in the food products due to homologous milk proteins of diverse species. This problem can be overcome by proper and reliable food labeling in order to ensure the life quality of allergic persons. Therefore, highly sensitive and accurate analytical techniques should be developed to detect the food allergens. Here, significant research advances in biosensors (specifically immunosensors and aptasensors) are reviewed for detection of the milk allergens. Different allergic proteins of cow milk are described here along with the analytical standard methods for their detection. Additionally, the commercial status of biosensors is also discussed in comparison to conventional techniques like enzyme-linked immunosorbent assay (ELISA). The development of novel biosensing mechanisms/kits for milk allergens detection is imperative from the perspective of enforcement of labeling regulations and directives keeping in view the sensitive individuals. Full article
(This article belongs to the Special Issue Sensors for Food Safety and Quality 2019-2020)
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