Detection Of Food Contaminants Research Articles

Detection of food harmful substances based on electrochemical biosensors

Food safety is related to everyone's health and life, so it is crucial to establish appropriate food systems and infrastructure, and develop efficient instruments for detecting food contaminants. Nowadays, many advanced detection technologies have emerged, playing a huge role in food safety testing, such as chromatographic analysis, spectral analysis, and electrochemical analysis. Among them, electrochemical biosensors have the advantages of superior selectivity, high sensitivity, convenient operation, low cost, and fast response, which are expected to develop into portable instruments for on-site rapid detection. Significant progress has been made in the electrochemical detection of food contaminants through the combination of nanotechnology and intelligent technology in recent years. This research summarizes the advancement of electrochemical biosensing technology for the detection of pesticides, heavy metals, illegal additives and mycotoxin by discussing the analytes, electrode materials, modification techniques, methods and detection limits for electrochemistry. Finally, the future development trends of the technology are discussed.

Phage T4-based colorimetric sensing material and its application to develop a time-dependent bacteria sensing platform for long-term detection of food contamination

Herein, we have developed a new type of bacteria-sensing platform for the naked-eye detection of Escherichia coli (E. coli) via a one-spot sample injection process. The platform comprised chlorophenol red-β-d-galactopyranoside (CPRG), isopropyl β-d-thiogalactopyranoside (IPTG), bacteriophages and two carbohydrates namely, maltodextrin and trehalose. CRPG and IPTG detected the β-galactosidase released from the bacteria and enhance its productivity, respectively. Bacteriophages were used as bioreceptors, and two carbohydrates protected phages during thermal process enabling long-term use of the platform. The developed material was characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy to determine the presence of the phages in the microcapsules. The detection property of the sensing material was examined using different strains of E. coli. Cold water-soluble guar gum was used as the stable gel matrix to increase the reactivity of platform toward samples stored at low temperature. The final prototype was tested using food samples containing different E. coli strains to demonstrate its food applicability with long-term use. This approach may provide an efficient and feasible phage-based sensing platform for the detection of bacterial contamination in food samples.

Improving the detection accuracy of the dual SERS aptasensor system with uncontrollable SERS “hot spot” using machine learning tools

BackgroundSimultaneous detection of food contaminants is crucial in addressing the collective health hazards arising from the presence of multiple contaminants. However, traditional multi-competitive surface-enhanced Raman scattering (SERS) aptasensors face difficulties in achieving simultaneous accurate detection of multiple target substances due to the uncontrollable SERS “hot spots”. In this study, using chloramphenicol (CAP) and estradiol (E2) as two target substances, we introduced a novel approach that combines machine learning methods with a dual SERS aptasensor, enabling simultaneous high-sensitivity and accurate detection of both target substances. ResultsThe strategy effectively minimizes the interference from characteristic Raman peaks commonly encountered in traditional multi-competitive SERS aptasensors. For this sensing system, the Au@4-MBA@Ag nanoparticles modified with sulfhydryl (SH)-CAP aptamer and Au@DTNB@Ag NPs modified with sulfhydryl (SH)-E2 aptamer were used as signal probes. Additionally, Fe3O4@Au nanoflowers integrated with SH-CAP aptamer complementary DNA and SH-E2 aptamer complementary DNA were used as capture probes, respectively. When compared to linear regression random forest, and support vector regression (SVR) models, the proposed artificial neural network (ANN) model exhibited superior precision, demonstrating R2 values of 0.963, 0.976, 0.991, and 0.970 for the training set, test set, validation set, and entire dataset, respectively. Validation with ten spectral groups reported an average error of 244 μg L−1. SignificanceThe essence of our study lies in its capacity to address a persistent challenge encountered by traditional multiple competitive SERS aptasensors – the interference generated by uncontrollable SERS “hot spots” that hinders simultaneous quantification. The accuracy of the predictive model for simultaneous detection of two target substances was significantly improved using machine learning tools. This innovative technique offers promising avenues for the accurate and high-sensitive simultaneous detection of multiple food and environmental contaminants.

Ensuring food safety: Microfluidic‐based approaches for the detection of food contaminants

AbstractDetecting foodborne contamination is a critical challenge in ensuring food safety and preventing human suffering and economic losses. Contaminated food, comprising biological agents (e.g. bacteria, viruses and fungi) and chemicals (e.g. toxins, allergens, antibiotics and heavy metals), poses significant risks to public health. Microfluidic technology has emerged as a transformative solution, revolutionizing the detection of contaminants with precise and efficient methodologies. By manipulating minute volumes of fluid on miniaturized systems, microfluidics enables the creation of portable chips for biosensing applications. Advancements from early glass and silicon devices to modern polymers and cellulose‐based chips have significantly enhanced microfluidic technology, offering adaptability, flexibility, cost‐effectiveness and biocompatibility. Microfluidic systems integrate seamlessly with various biosensing reactions, facilitating nucleic acid amplification, target analyte recognition and accurate signal readouts. As research progresses, microfluidic technology is poised to play a pivotal role in addressing evolving challenges in the detection of foodborne contaminants. In this short review, we delve into various manufacturing materials for state‐of‐the‐art microfluidic devices, including inorganics, elastomers, thermoplastics and paper. Additionally, we examine several applications where microfluidic technology offers unique advantages in the detection of food contaminants, including bacteria, viruses, fungi, allergens and more. This review underscores the significant advancement of microfluidic technology and its pivotal role in advancing the detection and mitigation of foodborne contaminants.

Bacteriophage-assisted lysis and eluted genomic DNA-based detection of pathogenic bacterial contamination in food

Foodborne diseases represent a significant global health concern, with a substantial number of illnesses and fatalities reported annually owing to the consumption of contaminated food. Current methods for identifying foodborne pathogens cannot effectively distinguish live from dead bacteria or efficiently detect multiple targets. Therefore, we developed a selective detection method for three pathogenic bacteria in food samples that leverages bacteriophage-assisted live-cell lysis and exposed genomic DNA amplification. The antimicrobial activity and host specificity of these three bacteriophages were employed to confirm the target bacteria selectivity. Bacterial DNA purification using bacteriophage-assisted lysis demonstrated the superior activity of the selected phages in extracting DNA from Escherichia coli O157:H7 and Salmonella Typhimurium. The results from reactions involving the three strains, including Bacillus cereus, highlighted that a 1 h incubation period yielded the most efficient DNA extraction and purification. The polymerase chain reaction (PCR) products obtained were comparable in terms of concentration and purity with those generated using bacterial DNA prepared using a commercial kit. In the practical food sample application experiment, bacterial strains were successfully recovered and concentrated using a polyethersulfone filter, resulting in a concentration factor >3 for all samples. Furthermore, the concentration of purified bacterial DNA from contaminated kimchi cabbage exceeded 10 ng/μL. Notably, we could detect E. coli O157:H7, S. Typhimurium, and B. cereus spiked at 103 colony-forming units/mL using multiplex PCR. This innovative bacteriophage-based approach holds substantial promise for the selective and practical detection of live foodborne pathogens, thereby significantly advancing food safety standards.

Eco-innovative electrochemical sensing for precise detection of vanillin and sulfadiazine additives in confectioneries

The continuous emergence of food additives and contaminants in edibles, especially confectioneries, demands advanced detection methods to ensure public health and safety. Vanillin (VAL) and sulfadiazine (SD) are of paramount concern due to their extensive application in various products. While VAL is favored for its flavoring attributes, SD, a common antibiotic, can inadvertently contaminate food items. For accurate and swift detection of these compounds, we introduced an innovative electrochemical sensor using cobalt oxide nanostructures. Notably, synthesizing these nanostructures through a green approach using glucose and starch is a significant advancement, offering both environmental benefits and enhanced material properties. The novelty of the material lies in its eco-friendly synthesis route and superior electrocatalytic performance. Preliminary results indicate a promising limit of detection (LOD) VAL= 0.003 µM & SD= 0.0055 µM and a broad linear range 0.02–209 µM emphasizing its potential for real-world food quality monitoring. This work, therefore, provides a crucial intersection of sustainable material synthesis and effective food contaminant detection, heralding a new era in food safety evaluation.

Recent Advances of DNA-Templated Metal Nanoclusters for Food Safety Detection: From Synthesis, Applications, Challenges, and Beyond.

Food safety concerns have become a significant threat to human health and well-being, catching global attention in recent years. As a result, it is imperative to research conceptually novel biosensing and effective techniques for food matrices detection. Currently, DNA-templated metal nanoclusters (DNA-MNCs) are considered as one of the most promising nanomaterials due to their excellent properties in biosensing. While DNA-MNCs have garnered increasing interest, the reviews of design strategies, applications, and futuristic prospects for biosensing have been hardly found especially in food safety. The synthesis of DNA-MNCs and their use as biosensing materials in food contamination detection, including pathogenic bacteria, toxins, heavy metals, residues of pesticides, and others were comprehensively reviewed. In addition, we summarize the properties of DNA-MNCs briefly and discuss the challenges and future trends. The application of DNA-MNCs powered biosensing has been demonstrated and actively studied, which is a promising paradigm for food safety testing that can supplement or even replace current existing methods. Despite the challenges of difficulty regulating accurately, poor stability, low quantum yield, and difficult commercial transformation, the application prospects of DNA-MNCs biosensors are promising. This review aims to provide insights and directions for the future development of DNA-MNCs based food detection technology.

Development of a Sensitive and Specific Quantitative RT-qPCR Method for the Detection of Hepatitis E Virus Genotype 3 in Porcine Liver and Foodstuff

As an international and zoonotic cause of hepatitis, hepatitis E virus (HEV) poses a significant risk to public health. However, the frequency of occurrence and the degree of contamination of food of animal origin require further research. The aim of this study was to develop and validate a highly sensitive quantitative RT-qPCR assay for the detection and quantification of HEV contamination in porcine liver and food. The focus was on genotype 3, which is most common as a food contaminant in developed countries and Europe. The selected assay has its target sequence in the open reading frame 1 (ORF1) of the HEV genome and showed good results in inclusivity testing, especially for HEV genotype 3. The developed assay seems to show high efficiency and a low intercept when compared to other assays, while having a comparable limit of detection (LOD). In addition, a standard curve was generated using artificially spiked liver to provide more accurate quantitative results for contamination assessment and tracking in this matrix. Application of the assay to test 67 pig livers from different origins resulted in a positivity rate of 7.5%, which is consistent with the results of numerous other prevalence studies. Quantitative detection of the viral genome in the food chain, particularly in pig livers, is essential for understanding the presence and evolution of HEV contamination and thus ensures consumer safety.

Ti3C2Tx MXene-Based Fluorescent Aptasensor for Detection of Dimethoate Pesticide.

Dimethoate contaminants in food pose a threat to human health. Rapid and sensitive trace detection methods are required to keep food safe. In this study, a novel fluorescent aptasensor was developed for the sensitive detection of dimethoate based on carbon quantum dots labeled with double-stranded DNA (CQDs-apt-cDNA) and Ti3C2Tx flakes. Under optimal conditions, the aptasensor showed a good linear range of 1 × 10-9 to 5 × 10-5 M for dimethoate with a coefficient of determination (R2) of 0.996. Besides, a low detection limit of 2.18 × 10-10 M was obtained. The aptasensor showed high selectivity in interference samples and good reproducibility with an RSD of 3.06% (<5%) for dimethoate detection. Furthermore, the proposed aptasensor was applied to the detection of dimethoate in apple juice and tap water with satisfactory recoveries from 96.2 to 104.4%. Because of these benefits, this aptasensor has the potential and promise for detecting food contaminants in the food industry.

Bimetallic nanozyme–bioenzyme hybrid material-mediated ultrasensitive and automatic immunoassay for the detection of aflatoxin B1 in food

Aflatoxin B1 (AFB1) is one of the most prevalent and dangerous biotoxin in crops and feedstuff, which poses a great threat to human health and also cause significant financial losses. Therefore, there is an urgent need to develop an effective method for AFB1 detection. In this work, we developed an automatic reaction equipment and nanozyme-enhanced immunosorbent assay (Auto-NEISA) for sensitive and accurate detection of AFB1 by combining the highly effective signal probes with a self-designed automated immunoreactive equipment. Wherein, polystyrene (PS) nanoparticles were used as signal carriers for loading a massive in situ-synthesized platinum and palladium bimetallic nanozyme, which could enrich horseradish peroxidase-labeled goat anti-mouse antibody (HRP-Ab2) on the nanozyme surface to form a bimetallic nanozyme–bioenzyme hybrid material for multiple signal amplification. The entire reaction could be automatically completed by the self-developed immunoreactive equipment. The Auto-NEISA method realized the sensitive detection of AFB1 with a wide linear detection range of 10–104 pg/mL, at a low limit of detection (LOD) of 5.52 pg/mL. The LOD was 65-fold lower than that of the enzyme-linked immunosorbent assay (ELISA). Additionally, Auto-NEISA was successfully applied to detect AFB1 in real food samples, demonstrating that it has considerable potential for detecting food contaminants with high accuracy and efficiency.

Detection of food contaminants: A review of established rapid analytical techniques and their applications and limitations

AbstractFood contaminants have consistently posed a serious threat to human health and have caused various food safety problems. The most common techniques currently used for the detection of food contaminants, include instrumental and immunoassay methods; however, these traditional methods have shown some limitations when applied to the analysis of food contaminants. Therefore, in recent years, more and more researchers have been devoted to the development of rapid, reliable, sensitive, and suitable detection techniques for the detection of food contaminants in food matrices. In this review, we first classify the analytical methods proposed in recent years into colorimetric methods, fluorescence methods, photoelectrochemical methods, electrochemical methods, nucleic acid amplification methods, and other methods, and illustrate their detection principles. In addition, the paper highlights the strategies and recent research advances for each method through typical application examples. Finally, the future perspectives of these analytical methods are presented. We hope that this review will provide researchers with valuable insights to guide the sensitive detection of food contaminants.

Application progress of covalent organic frameworks (COFs) materials in the detection of food contaminants

Application progress of covalent organic frameworks (COFs) materials in the detection of food contaminants

Target-triggered dual signal amplification based on HCR-enhanced nanozyme activity for the sensitive visual detection of Escherichia coli.

The detection of foodborne pathogens is crucial for food hygiene regulation and disease diagnosis. Colorimetry has become one of the main analytical methods in studying foodborne pathogens due to its advantages of visualization, low cost, simple operation, and no complex instrument. However, the low sensitivity limits its applications in early identification and on-site detection for trace analytes. In order to overcome such a limitation, herein we propose a joint strategy featuring dual signal amplification based on the hybridization chain reaction (HCR) and DNA-enhanced peroxidase-like activity of gold nanoparticles (AuNPs) for the sensitive visual detection of Escherichia coli. Target bacteria bound specifically to the aptamer domain in the capture hairpin probe, exposing the trigger domain for HCR and forming the extended double-stranded DNA (dsDNA) structures. The peroxidase-like catalytic capacity of AuNPs can be enhanced significantly by dsDNAs with the sticky ends of dsDNAs being adsorbed on AuNPs and the rigidity of dsDNAs causing the spatial regulation of AuNP concentration. The intensity of the enhancement was linearly related to the number of target bacteria. With the above strategy, the detection limit of our colorimetric method for Escherichia coli was down to 28 CFU mL-1 within a short analytical time (50 min). This study provides a new perspective for the sensitive and visual detection of early bacterial contamination in foods.

Europium nanospheres based ultrasensitive fluorescence immunosensor for aflatoxin B1 determination in feed

In this work, a new competitive immunosensor for aflatoxin B1 (AFB1) detection was developed using europium (Eu) fluorescent nanospheres and magnetic beads. Firstly, Eu nanospheres were synthesized through two steps including carboxylated polystyrene nanospheres and Eu-doped polystyrene nanospheres preparation. Then Eu nanospheres were covalently tagged to anti-AFB1 monoclonal antibody (anti-AFB1 mAb) through an EDC coupling method. Carboxylated Fe3O4 magnetic beads were conjugated to AFB1-BSA through EDC/NHS crosslinking to obtain AFB1-BSA-Fe3O4. In the absence of AFB1, Eu-anti-AFB1 mAb were incubated with AFB1-BSA-Fe3O4 to form Eu-anti-AFB1 mAb-AFB1-BSA-Fe3O4 in PBS buffer. However, in the presence of AFB1, the competitive interaction of AFB1 and AFB1-BSA-Fe3O4 to bind with Eu-anti-AFB1 mAb occurred. With the increasing concentration of AFB1, less Eu-anti-AFB1 mAb-AFB1-BSA-Fe3O4 formed. So the fluorescence intensity of Eu-anti-AFB1 mAb-AFB1-BSA-Fe3O4 was gradually decreased after magnetic separation. The degree of fluorescence decrease was linear with respect to the logarithm of AFB1 concentration in the range of 0.01–2 ng/mL in both buffer solution and feed samples and the detection limit was 0.003 ng/mL. What's more, the immunosensor showed excellent specificity for AFB1 without being interfered by other mycotoxins. In consideration of the excellent performance of this immunosensor, we can speculate that the proposed method could be widely used in detecting food contaminants.

Recent Studies and Applications of Hydrogel-Based Biosensors in Food Safety.

Food safety has increasingly become a human health issue that concerns all countries in the world. Some substances in food that can pose a significant threat to human health include, but are not limited to, pesticides, biotoxins, antibiotics, pathogenic bacteria, food quality indicators, heavy metals, and illegal additives. The traditional methods of food contaminant detection have practical limitations or analytical defects, restricting their on-site application. Hydrogels with the merits of a large surface area, highly porous structure, good shape-adaptability, excellent biocompatibility, and mechanical stability have been widely studied in the field of food safety sensing. The classification, response mechanism, and recent application of hydrogel-based biosensors in food safety are reviewed in this paper. Furthermore, the challenges and future trends of hydrogel biosensors are also discussed.

Gold nanoparticles as colorimetric probes in food analysis: Progress and challenges.

The rapid, sensitive and reliable food safety control is urgently needed due to the harmful effects of the food contaminants on human health. Colorimetric approach has exhibited promising potential for the detection of food contaminants due to their easy preparation, rapid detection, high sensitivity, and naked-eye sensing. In recent years, AuNPs-based colorimetric probes have been extensively explored for food analysis. The present article reviews the development of AuNPs-based colorimetric probes for colorimetric sensing and their applications in food analysis. It generally summarizes the properties of AuNPs and introduces the preparation and functionalization methods of AuNPs. An overview of the colorimetric sensing mechanisms of AuNPs-based probes and their applications in analysis of food contaminants are also provided. Although AuNPs-based colorimetric probes show many advantages in detection of food contaminants, challenges remain in terms of complexity of food matrices, multiple analytes detection in a single go, and testing conditions interference.

Research progress of the combination of COFs materials with food safety detection.

Covalent organic frameworks (COFs) have received lots of attention due to their multiple advantages such as high specific surface area, controlled pore size, and excellent stability. When detecting food contaminants, the matrix effect brought by complex food samples can significantly affect the accuracy of the results. How to attenuate matrix effect has always been a major challenge. Utilizing the advantages of COFs and applying them to detect food contaminants is currently a key research direction. The aim of this work is to provide a systematic summary of sample pretreatment techniques and detection techniques combined with COFs, which include almost all current techniques combined with COFs. In addition, the principles of combining COFs with different techniques are explained. Finally, the research foci and development direction of COFs in food contaminant detection are discussed. This is an important reference for the future development of food safety and the design of COFs.

Fe-N-C single-atom nanozyme-linked immunosorbent assay for quantitative detection of aflatoxin B1

Aflatoxin B1 (AFB1) is a prominent food contaminant known for its high toxicity. Rapid, low-cost, and sensitive detection of AFB1 is an urgent demand for food safety risk control. In the traditional enzyme-linked immunosorbent assay (ELISA) method for AFB1 detection, horseradish peroxide (HRP) is high-cost and possesses poor environmental stability. In this study, a direct competitive single-atom nanozymes (SAzymes) -linked immunosorbent assay was developed based on Fe-N-C SAzymes. The proposed methods exhibited excellent sensitivity, rapid detection, fabrication, and low cost. Under the optimal conditions, the limit of detection of the new assay was 3.3 pg mL−1, with a quantitative relationship between 0.0084 and 0.358 ng mL−1. In addition, the developed method presented good recoveries in spiked samples, ranging from 84.50% and 103.75%, with coefficients of variation below 10%. Furthermore, the developed detection method showed good consistency (R2 = 0.9852) with the reference method, liquid chromatography/mass spectrometry (LC-MS/MS). To our knowledge, this is the first report about single-atom nanozymes-based ELISA for AFB1 determination. This work provides a feasible strategy for the rapid and sensitive detection of food contaminants using SAzymes.

Nanosensors: A smart remedy for early detection of clenbuterol contamination in food.

Veterinary drugs which are primarily meant for livestock treatment have now been categorised under potential food contaminant due to its unregulated usage and abuse. Their over usage by animal workers lead to production of contaminated animal-based food products which contain veterinary drug residues. These drugs are also misused as growth promoters to enhance the muscle to fat ratio in human body. This review highlights the misuse of such a veterinary drug; Clenbuterol. In this review, we have comprehensively discussed the usage of nanosensors to detect clenbuterol in food samples. Colorimetric, fluorescent, electrochemical, SERS and electrochemiluminescence are major categories of nanosensors that have been utilized for this purpose. The mechanism through which these nanosensors detect clenbuterol have been discussed in detail. The limit of detection and recovery percentage values of each nanosensor have been compared. This review will impart significant information on various nanosensors for clenbuterol detection in real samples.

Fluorescence determination of 3-MCPD by combining amino silica nanoparticles with fluorescein isothiocyanate

Using amino silica modified with fluorescein isothiocyanate (FITC), a quick fluorescence analysis technique is used for the detection of 3-monochloropropane-1,2-diol (3-MCPD). At 100 °C and pH 8.5, FITC-modified amino silica exhibits the lowest fluorescence intensity in the presence of 3-MCPD. This can predominantly be explained mostly explained by 3-MCPD’s capacity to occupy the amino group that FITC normally binds to. The fluorescence intensity of FITC-modified amino silica was greatly quenched by 3-MCPD’s reaction with the amino group under alkaline conditions, and the fluorescence intensity is different at different reaction times, reaction pH, and reaction temperature. The effects of various 3-MCPD concentrations on the optical characteristics of FITC-modified amino silica were also investigated. Fluorescence analysis is used to obtain a linear range from 0.025 to 1.0 mg/L for 3-MCPD detection under optimal experimental conditions, with a detection limit of 0.025 mg/L and a correlation coefficient of 0.9915. The quantity of 3-MCPD in soy sauce was measured under ideal conditions. Using the optimized conditions, the contents of 3-MCPD in soy sauce were determined. These results suggest that this method is sensitive to 3-MCPD and may have a substantial application in the rapid detection of food contaminants particularly, where the quality and safety of food products are of paramount concern.