Advanced Real-Time On-Site Sensing Technologies in Food and Environment Analysis

A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Analytical Methods, Instrumentation and Miniaturization".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 21428

Special Issue Editors

Department of Biosystems Engineering, Zhejiang University, Hangzhou 310058, China
Interests: nanocomposites; modified electrode; pattern recognition; intelligent flavor sensing system; food quality detection
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Guest Editor
College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou, China
Interests: gas sensors; data mining

Special Issue Information

Dear Colleagues,

Real-time detection devices and sensors are key in object detection with fast inference while maintaining simple operation and a base level of accuracy. The number of different types of sensors that focus on object detection quantitatively or qualitatively is continuously growing, although their applications in practical utilization are more limited. Compared to laboratory-scale devices, real-time on-site detection devices based on gas sensors, microwave sensors, or spectroscopy sensors are extremely attractive due to their low cost, easy operation, and simplified sample pretreatment.

This Special Issue will provide a forum for the latest research activities in the field of chemical/physical sensors, relevant data mining, and their application. Both review articles and original research papers are solicited in areas including, but not limited to, the following:

  • Gas sensors, microwave sensors, or spectroscopy sensors;
  • On-line analysis system design based on micro sensors or sensor arrays;
  • The application of sensors for food detection or environment monitoring;
  • Data mining for sensor signal feature extraction, data reduction, classification, prediction, etc.

Dr. Zhenbo Wei
Dr. Shanshan Qiu
Guest Editors

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Published Papers (10 papers)

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Research

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22 pages, 4886 KiB  
Article
Utilising Portable Laser-Induced Breakdown Spectroscopy for Quantitative Inorganic Water Testing
by Nils Schlatter, Bernd G. Lottermoser, Simon Illgner and Stefanie Schmidt
Chemosensors 2023, 11(9), 479; https://doi.org/10.3390/chemosensors11090479 - 1 Sep 2023
Cited by 1 | Viewed by 1260
Abstract
At present, the majority of water testing is carried out in the laboratory, and portable field methods for the quantification of elements in natural waters remain to be established. In contrast, portable instruments like portable X-ray fluorescence (pXRF) analysis and portable laser-induced breakdown [...] Read more.
At present, the majority of water testing is carried out in the laboratory, and portable field methods for the quantification of elements in natural waters remain to be established. In contrast, portable instruments like portable X-ray fluorescence (pXRF) analysis and portable laser-induced breakdown spectroscopy (pLIBS) have become routine analytical methods for the quantification of elements in solids. This study aims to show that pLIBS can also be used for chemical compositional measurements of natural waters. Bottled mineral waters were selected as sample materials. A surface-enhanced liquid-to-solid conversion technique was used to improve the detection limits and circumvent the physical limitations in liquid analysis. The results show that low to medium mineralised waters can be analysed quantitatively for their ions using the documented method. For more highly concentrated samples, typically above an electrical conductivity (EC) of 1000 µS/cm, further adjustment is required in the form of self-absorption correction. However, water with a conductivity up to this limit can be analysed for the main cations (Li+, Na+, Mg2+, K+, Ca2+, and Sr2+) as well as the main anions (SO42− and Cl) using the documented method. This study demonstrates that there is significant potential for developing field-based pLIBS as a tool for quantitative water analysis. Full article
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11 pages, 2320 KiB  
Article
Application of an Electronic Nose Technology for the Prediction of Chemical Process Contaminants in Roasted Almonds
by Marta Mesías, Juan Diego Barea-Ramos, Jesús Lozano, Francisco J. Morales and Daniel Martín-Vertedor
Chemosensors 2023, 11(5), 287; https://doi.org/10.3390/chemosensors11050287 - 11 May 2023
Cited by 3 | Viewed by 1319
Abstract
The purpose of this study was to investigate the use of an experimental electronic nose (E-nose) as a predictive tool for detecting the formation of chemical process contaminants in roasted almonds. Whole and ground almonds were subjected to different thermal treatments, and the [...] Read more.
The purpose of this study was to investigate the use of an experimental electronic nose (E-nose) as a predictive tool for detecting the formation of chemical process contaminants in roasted almonds. Whole and ground almonds were subjected to different thermal treatments, and the levels of acrylamide, hydroxymethylfurfural (HMF) and furfural were analysed. Subsequently, the aromas were detected by using the electronic device. Roasted almonds were classified as positive or negative sensory attributes by a tasting panel. Positive aromas were related to the intensity of the almond odour and the roasted aroma, whereas negative ones were linked to a burnt smell resulting from high-intensity thermal treatments. The electronic signals obtained by the E-nose were correlated with the content of acrylamide, HMF, and furfural (RCV2 > 0.83; RP2 > 0.76 in whole roasted almonds; RCV2  > 0.88; RP 2 > 0.95 in ground roasted almonds). This suggest that the E-nose can predict the presence of these contaminants in roasted almonds. In conclusion, the E-nose may be a useful device to evaluate the quality of roasted foods based on their sensory characteristics but also their safety in terms of the content of harmful compounds, making it a useful predictive chemometric tool for assessing the formation of contaminants during almond processing. Full article
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12 pages, 4529 KiB  
Article
A Paper-Chip-Based Phage Biosensor Combined with a Smartphone Platform for the Quick and On-Site Analysis of E. coli O157:H7 in Foods
by Chaiyong Wu, Dengfeng Li, Qianli Jiang and Ning Gan
Chemosensors 2023, 11(2), 151; https://doi.org/10.3390/chemosensors11020151 - 20 Feb 2023
Cited by 2 | Viewed by 1837
Abstract
The rapid and specific point-of-care (POC) analysis of virulent pathogenic strains plays a key role in ensuring food quality and safety. In this work, a paper-based fluorescent phage biosensor was developed for the detection of the virulent E. coli O157:H7 strain (as the [...] Read more.
The rapid and specific point-of-care (POC) analysis of virulent pathogenic strains plays a key role in ensuring food quality and safety. In this work, a paper-based fluorescent phage biosensor was developed for the detection of the virulent E. coli O157:H7 strain (as the mode of virulent pathogens) in food samples. Firstly, phages that can specifically combine with E. coli O157:H7 (E. coli) were stained with SYTO-13 dye to prepare a novel fluorescent probe (phage@SYTO). Simultaneously, a micro-porous membrane filter with a pore size of 0.45 μm was employed as a paper chip so as to retain the E. coli-phage@SYTO complex (>1.2 μm) on its surface. The phage@SYTO (200 nm in size) was able to pass through the pores of the chip, and the complex could be retained on the paper chip using the free phage@SYTO probes. The E. coli-phage@SYTO could emit a visual fluorescent signal (excited at 365 nm; emitted at 520 nm) onto the chip, which could be detected by a smartphone to reflect the concentration of E. coli. Under optimized conditions, the detection limit was as low as 50 CFU/mL (S/N = 3) and exhibited a wide linear range from 102 to 106 CFU/mL. The sensor has potential application value for the quick and specific POCT detection of virulent E. coli in foods. Full article
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15 pages, 4044 KiB  
Article
Detection of Low-Level Adulteration of Hungarian Honey Using near Infrared Spectroscopy
by Zsanett Bodor, Mariem Majadi, Csilla Benedek, John-Lewis Zinia Zaukuu, Márta Veresné Bálint, Éva Csajbókné Csobod and Zoltan Kovacs
Chemosensors 2023, 11(2), 89; https://doi.org/10.3390/chemosensors11020089 - 24 Jan 2023
Cited by 4 | Viewed by 2271
Abstract
Honey adulteration is a worldwide problem; however, its detection is a challenge for researchers and authorities. There are numerous ways of honey counterfeiting; amongst them, direct adulteration is one of the most common methods. Correlative techniques, such as near-infrared spectroscopy (NIRS), are useful [...] Read more.
Honey adulteration is a worldwide problem; however, its detection is a challenge for researchers and authorities. There are numerous ways of honey counterfeiting; amongst them, direct adulteration is one of the most common methods. Correlative techniques, such as near-infrared spectroscopy (NIRS), are useful tools in the detection of honey adulteration; however, this method has not been applied to Hungarian honeys. The aim of this research was to investigate the performance of NIRS for the detection of sugar syrup addition to Hungarian honeys at lower concentration levels (<10% w/w). Acacia, rape, forest, sunflower, and linden honeys were mixed with high-fructose-content sugar syrup, rice syrup, or self-made glucose fructose syrup in 3%, 5%, and 10% w/w. NIRS analysis was performed in the spectral range of 950–1650 nm. Principal component analysis was coupled with linear discriminant analysis and partial least square regression models were built for the classification and prediction of adulteration levels, respectively. Our results showed that the performance of NIRS highly depends on both type of syrup and honey. PCA-LDA models provided the 100% correct classification of control in the case of all the models, while PLSR results could predict the added sugar syrup content in the case of rice and F40 syrup models, obtaining >2.2 RPDCV value. Full article
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16 pages, 4448 KiB  
Article
Monitoring of MSW Incinerator Leachate Using Electronic Nose Combined with Manifold Learning and Ensemble Methods
by Zhongyuan Zhang, Shanshan Qiu, Jie Zhou and Jingang Huang
Chemosensors 2022, 10(12), 506; https://doi.org/10.3390/chemosensors10120506 - 30 Nov 2022
Cited by 1 | Viewed by 1447
Abstract
Waste incineration is regarded as an ideal method for municipal solid waste disposal (MSW), with the advantages of waste-to-energy, lower secondary pollution, and greenhouse gas emission mitigation. For incineration leachate, the information from the headspace gas that varies at different processing processes and [...] Read more.
Waste incineration is regarded as an ideal method for municipal solid waste disposal (MSW), with the advantages of waste-to-energy, lower secondary pollution, and greenhouse gas emission mitigation. For incineration leachate, the information from the headspace gas that varies at different processing processes and might be useful for chemical analysis, is ignored. The study applied a novel electronic nose (EN) to mine the information from leachate headspace gas. By combining manifold learnings (principal component analysis (PCA) and isometric feature mapping (ISOMAP), and uniform manifold approximation and projection (UMAP) and ensemble techniques (light gradient boosting machine (lightGBM) and extreme gradient boosting (XGBT)), EN based on the UMAP-XGBT model had the best classification performance with a 99.95% accuracy rate in the training set and a 95.83% accuracy rate in the testing set. The UMAP-XGBT model showed the best prediction ability for leachate chemical parameters (pH, chemical oxygen demand, biochemical oxygen demand, ammonia, and total phosphorus), with R2 higher than 0.99 both in the training and testing sets. This is the first study of the EN application for leachate monitoring, offering an easier and quicker detection method than traditional instrumental measurements for the enforcement and implementation of effective monitoring programs. Full article
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12 pages, 1688 KiB  
Article
Design and Optimization of Electronic Nose Sensor Array for Real-Time and Rapid Detection of Vehicle Exhaust Pollutants
by Jin Tong, Chengxin Song, Tianjian Tong, Xuanjie Zong, Zhaoyang Liu, Songyang Wang, Lidong Tan, Yinwu Li and Zhiyong Chang
Chemosensors 2022, 10(12), 496; https://doi.org/10.3390/chemosensors10120496 - 22 Nov 2022
Cited by 3 | Viewed by 1255
Abstract
Traditional vehicle exhaust pollutant detection methods, such as bench test and remote sensing detection, have problems such as large volume, high cost, complex process, long waiting time, etc. In this paper, according to the main components of vehicle exhaust pollutants, an electronic nose [...] Read more.
Traditional vehicle exhaust pollutant detection methods, such as bench test and remote sensing detection, have problems such as large volume, high cost, complex process, long waiting time, etc. In this paper, according to the main components of vehicle exhaust pollutants, an electronic nose with 12 gas sensors was designed independently for real-time and rapid detection of vehicle exhaust pollutants. In order to verify that the designed electronic nose based on machine learning classification method can accurately identify the exhaust pollutants from different engines or different concentration levels from the same engine. After feature extraction of the collected data, Random Forest (RF) was used as the classifier, and the average classification accuracy reached 99.92%. This result proved that the designed electronic nose combined with RF method can accurately and sensitively judge the concentration level of vehicle exhaust pollutants.. Then, in order to enable the electronic nose to be vehicle-mounted and to achieve real-time and rapid detection of vehicle exhaust pollutants. We used Recursive Feature Elimination with Cross Validation (RFECV), Random Forest Feature Selector (RFFS) and Principal Component Analysis (PCA) to optimize the sensor array. The results showed that these methods can effectively simplify the sensor array while ensuring the RF classifier’s classification recognition rate. After using RFECV and RFFS to optimize the sensor array, the RF classifier’s classification recognition rate of the optimized sensor arrays for vehicle exhaust pollutants reached 99.77% and 99.44%, respectively. The numbers of sensors in the optimized sensor arrays were six and eight respectively, which achieved the miniaturization and low-cost of the electronic nose. With the limitation of six sensors, RFECV is the best sensor array optimization method among the three methods. Full article
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16 pages, 9647 KiB  
Article
Real-Time Measurement of Moisture Content of Paddy Rice Based on Microstrip Microwave Sensor Assisted by Machine Learning Strategies
by Jin Liu, Shanshan Qiu and Zhenbo Wei
Chemosensors 2022, 10(10), 376; https://doi.org/10.3390/chemosensors10100376 - 20 Sep 2022
Cited by 6 | Viewed by 2507
Abstract
Moisture content is extremely imoprtant to the processes of storage, packaging, and transportation of grains. In this study, a portable moisture measuring device was developed based on microwave microstrip sensors. The device is composed of three parts: a microwave circuit module, a real-time [...] Read more.
Moisture content is extremely imoprtant to the processes of storage, packaging, and transportation of grains. In this study, a portable moisture measuring device was developed based on microwave microstrip sensors. The device is composed of three parts: a microwave circuit module, a real-time measurement module, and software to display the results. This work proposes an improvement measure by optimizing the thickness of paddy rice samples (8–13 cm) and adding the ambient temperatures and the moisture contents (13.66–27.02% w.b.) at a 3.00 GHz frequency. A random forest, decision tree, k-nearest neighbor, and support vector machine were applied to predict the moisture content in the paddy rice. Microwave characteristics, phase shift, and temperature compensation were selected as the input variables to the prediction models, which have achieved high accuracy. Among those prediction models, the random forest model yielded the best performance with highest accuracy and stability (R2 = 0.99, RMSE = 0.28, MAE = 0.26). The device showed a relatively stable performance (the maximum average absolute error was 0.55%, the minimum absolute error was 0.17%, the mean standard deviation was 0.18%, the maximum standard deviation was 0.41%, and the minimum standard deviation was 0.08%) within the moisture content range of 13–30%. The instrument has the advantages of real-time, simple structure, convenient operation, low cost, and portability. This work is expected to provide an important reference for the real-time in situ measurement of agricultural products, and to be of great significance for the development of intelligent agricultural equipment. Full article
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10 pages, 2129 KiB  
Article
A Microphysiometric System Based on LAPS for Real-Time Monitoring of Microbial Metabolism
by Nan Jiang, Tao Liang, Chunlian Qin, Qunchen Yuan, Mengxue Liu, Liujing Zhuang and Ping Wang
Chemosensors 2022, 10(5), 177; https://doi.org/10.3390/chemosensors10050177 - 6 May 2022
Cited by 4 | Viewed by 2078
Abstract
Macronutrients (carbohydrates, fat and protein) are the cornerstones of daily diet, among which carbohydrates provide energy for the muscles and central nervous system during movement and exercise. The breakdown of carbohydrates starts in the oral cavity, where they are primarily hydrolyzed to glucose [...] Read more.
Macronutrients (carbohydrates, fat and protein) are the cornerstones of daily diet, among which carbohydrates provide energy for the muscles and central nervous system during movement and exercise. The breakdown of carbohydrates starts in the oral cavity, where they are primarily hydrolyzed to glucose and then metabolized to organic acids. The end products may have an impact on the oral microenvironment, so it is necessary to monitor the process of microbial metabolism and to measure the pH change. Although a pH meter has been widely used, it is limited by its sensitivity. We then introduce a light addressable potentiometric sensor (LAPS), which has been used in extracellular acidification detection of living cells with the advantages of being objective, quantitative and highly sensitive. However, it is difficult to use in monitoring bacterial metabolism because bacteria cannot be immobilization on the LAPS chip as easily as living cells. Therefore, a microphysiometric system integrated with Transwell insert and microfluidic LAPS chip was designed and constructed to solve this problem. The decrease in pH caused by glucose fermentation in Lactobacillus rhamnosus was successfully measured by this device. This proves the feasibility of the system for metabolism detection of non-adhere targets such as microorganisms and even 3D cells and organoids. Full article
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17 pages, 3418 KiB  
Article
Tetracycline Antibiotics: Elucidating the Electrochemical Fingerprint and Oxidation Pathway
by Rocío Cánovas, Nick Sleegers, Alexander L.N. van Nuijs and Karolien De Wael
Chemosensors 2021, 9(7), 187; https://doi.org/10.3390/chemosensors9070187 - 20 Jul 2021
Cited by 16 | Viewed by 3991
Abstract
Herein, a complete study of the electrochemical behavior of the most commonly used tetracycline antibiotics (TCs) on unmodified carbon screen-printed electrodes (SPEs) is presented. In addition, the oxidation pathway of TCs on SPE is elucidated, for the first time, with liquid chromatography-quadrupole time-of-flight [...] Read more.
Herein, a complete study of the electrochemical behavior of the most commonly used tetracycline antibiotics (TCs) on unmodified carbon screen-printed electrodes (SPEs) is presented. In addition, the oxidation pathway of TCs on SPE is elucidated, for the first time, with liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Square wave voltammetry (SWV) was used to study the electrochemical fingerprint (EF) of the antibiotics shaping the different oxidation processes of the TCs in a pH range from 2 to 12. Their characteristic structure and subsequent EF offer the possibility of distinguishing this class of antibiotics from other types. Under the optimized parameters, calibration curves of tetracycline (TET), doxycycline (DOXY), oxytetracycline (OXY), and chlortetracycline (CHL) in a Britton Robinson buffer solution (pH 9) exhibited a linear range between 5 and 100 µM with excellent reproducibilities (RSDTET = 3.01%, RSDDOXY = 3.29%, RSDOXY = 9.78% and RSDCHL = 6.88% at 10 µM, N = 3) and limits of detection (LOD) of LODTET = 4.15 µM, LODDOXY = 2.14 µM, LODOXY = 3.07 µM and LODCHL = 4.15 µM. Furthermore, binary, tertiary, and complex mixtures of all TCs were analyzed with SWV to investigate the corresponding EF. A dual pH screening (pH 4 and pH 9), together with the use of a custom-made Matlab script for data treatment, allowed for the successful confirmation of a single presence of TCs in the unknown samples. Overall, this work presents a straightforward study of the electrochemical behavior of TCs in SPE, allowing for the future on-site identification of residues of tetracycline antibiotics in real samples. Full article
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Review

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32 pages, 5627 KiB  
Review
Optical Immunosensors for Bacteria Detection in Food Matrices
by Dimitra Kourti, Michailia Angelopoulou, Panagiota Petrou and Sotirios Kakabakos
Chemosensors 2023, 11(8), 430; https://doi.org/10.3390/chemosensors11080430 - 3 Aug 2023
Cited by 3 | Viewed by 2959
Abstract
Optical immunosensors are one of the most popular categories of immunosensors with applications in many fields including diagnostics and environmental and food analysis. The latter field is of particular interest not only for scientists but also for regulatory authorities and the public since [...] Read more.
Optical immunosensors are one of the most popular categories of immunosensors with applications in many fields including diagnostics and environmental and food analysis. The latter field is of particular interest not only for scientists but also for regulatory authorities and the public since food is essential for life but can also be the source of many health problems. In this context, the current review aims to provide an overview of the different types of optical immunosensors focusing on their application for the determination of pathogenic bacteria in food samples. The optical immunosensors discussed include sensors based on evanescent wave transduction principles including surface plasmon resonance (SPR), fiber-optic-, interferometric-, grating-coupler-, and ring-resonator-based sensors, as well as reflectometric, photoluminescence, and immunosensors based on surface-enhanced Raman scattering (SERS). Thus, after a short description of each transduction technique, its implementation for the immunochemical determination of bacteria is discussed. Finally, a short commentary about the future trends in optical immunosensors for food safety applications is provided. Full article
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