Nanomaterials-based aptasensors for rapid detection and early warning of key food contaminants: A review.

The frequent occurrence of food safety incidents has aroused public concern about food safety and key contaminants. Foodborne pathogen contamination, pesticide residues, heavy metal residues, and other food safety problems will significantly impact human health. Therefore, developing efficient and sensitive detection method to ensure food safety early warning is paramount. The aptamer-based sensor (aptasensor) is a novel analytical tool with strong targeting, high sensitivity, low cost, etc. It has been extensively utilized in the pharmaceutical industry, biomedicine, environmental engineering, food safety detection, and in other diverse fields. This work reviewed the latest research progress of aptasensors for food analysis and detection, mainly introducing their application in detecting various key food contaminants. Subsequently, the sensing mechanism and performance of aptasensors are discussed. Finally, the review will examine the challenges and opportunities related to aptasensors for detecting major contaminants in food, and advance implementation of aptasensors in food safety and detection.

Smartphone-assisted colorimetric biosensor for the rapid visual detection of natural antioxidants in food samples.

Quantitative monitoring of the concentrations of epigallocatechin gallate (EGCG) and cysteine (Cys) is of great significance for promoting human health. In this study, iron/aluminum bimetallic MOF material MIL-53 (Fe, Al) was rapidly prepared under room temperature using a co-precipitation method, followed by investigating the peroxidase-like (POD-like) activity of MIL-53(Fe, Al) using 3,3',5,5'-tetramethylbenzidine (TMB) as a chromogenic substrate. The results showed that the Michaelis -Menten constants of TMB and H2O2 as substrates were 0.167 mM and 0.108 mM, respectively. A colorimetric sensing platform for detecting EGCG and Cys was developed and successfully applied for analysis and quantitative detection using a smartphone. The linear detection range for EGCG was 15∼80 µM (R2=0.994) and for Cys was 7∼95 µM (R2=0.998). The limits of detection (LOD) were 0.719 µM and 0.363 µM for EGCG and Cys, respectively. This work provides a new and cost-effective approach for the real-time analysis of catechins and amino acids.

Recent advances in electrochemical approaches for detection of nitrite in food samples.

Nitrite is a common ingredient in the industry and agriculture; it is everywhere, like water, food, and surroundings. Recently, several approaches have been developed to measure the nitrite levels. So, this review was presented as a summary of many approaches utilized to detect the nitrite. Furthermore, the types of information that may be acquired using these methodologies, including optic and electrical signals, were discussed. In electrical signal methods, electrochemical sensors are usually developed using different materials, including carbon, polymers, oxides, and hydroxides. At the same time, optic signals receiving techniques involve utilizing fluorescence chromatography, absorption, and spectrometry instruments. Furthermore, these methodologies' benefits, drawbacks, and restrictions are examined. Lastly, due to the efficiency and fast means of electrochemical detectors, it was suggested that they can be used for detecting nitrite in food safety. Futuristic advancements in the techniques used for nitrite determination are subsequently outlined.

Thylakoid-based green preparation of porous microneedles for antibiotic residues detection in food samples.

BACKGROUND: Antibiotic residues in food chain have raised concerns regarding their toxicity and involvement in antimicrobial resistance. However, most existing antibiotic biosensors are primarily applicable to liquid food samples. Given the complex matrix characteristics of foods, there is an urgent need for the development of effective antibiotic detection platforms that exhibit high universality and flexibility. Porous microneedles (PMN) are microdevice structures with needle-like shapes and microscale pores throughout their composition, which facilitate rapid sampling. Consequently, the integration of PMN with biosensors holds significant promise for the detection of antibiotic residues in complex food samples. RESULTS: In this study, hydrogel-forming PMN are fabricated by leveraging the oxygen-production capacity of thylakoid to generate bubbles and form porous structures. These PMN are then integrated with a fluorescence aptasensor for the quantification of the antibiotic netilmicin. The aptasensor consists of a netilmicin (NET) aptamer with stem loop and hairpin structure, which facilitated the binding of SYBR Green I to produce a fluorescent signal. In the presence of NET, the complete binding between NET and the aptamer results in a reduction of fluorescence intensity, thereby generating a detectable signal change for the detection of NET. Utilizing capillary action accelerate fluid extraction (2.9 times faster than nonporous microneedles) and a large specific surface area (5.1072 m2/g) conducive to aptasensor adsorb, the PMN achieve efficient capture and quantification of antibiotic with limits of detection and quantitation of 5.99 nM and 19.8 nM, respectively. SIGNIFICANCE: Porous microneedles with tunable porosity and desirable mechanical properties are successfully fabricated. The integration of PMN with aptasensor enable the efficient detection of netilmicin in fish, milk and river water samples, demonstrating high recovery rates. The PMN represent potential tools for the convenient and rapid detection of antibiotic residues within complex food matrices, thereby enhancing food safety monitoring.

Reproducible, Accurate, and Sensitive Food Toxin On-Site Detection with Carbon Nanotube Transistor Biosensors.

Field-effect transistor (FET) biosensors based on nanomaterials are promising in the areas of food safety and early disease diagnosis due to their ultrahigh sensitivity and rapid response. However, most academically developed FET biosensors lack real-world reproducibility and comprehensive methodological validation to meet the standards of regulatory bodies. Here, highly uniform and well-packaged semiconducting carbon nanotube (CNT) FET biosensor chips were developed and assessed for the plug-and-play sensing for the rapid and highly sensitive detection of aflatoxin B1 (AFB1) in real food samples to meet international standards. In order to meet the requirements for reproducibility and stability, a scalable residual-free passivation and packaging process was developed for CNT FET biosensors. Portable detection systems were then constructed for on-site detection. The resulting packaged chips were functionalized with nucleic aptamers to enable highly selective detection of AFB1 in food samples with a detection limit (LOD) of 0.55 fg/mL (standard) for AFB1 and cross-reactivity coefficients to interferences as low as 1.8 × 10-7 in simulated solutions. Utilizing the portable detection system, on-site real food detection was achieved with a rapid response time less than 60 s, and LOD of 0.25 pg/kg (standard) in complex corn sample matrices. Single-blind tests demonstrated the ability of the chips to detect AFB1-positive food with 100% accuracy, using a set of 30 peanut samples. Validation experiments confirmed that the detection range, stability, and repeatability met international standards. This study showcased the accuracy, reliability, and potential practical applications of CNT FET biosensor chips in areas such as food safety and rapid biomedical testing.

Development of a simple and rapid dipstick paper-based test strip for colorimetric determination of nitrate and nitrite in water and foodstuffs.

A rapid user-friendly paper-based test strip using zinc microparticles in conjugation with Griess reagent was developed for nitrite and nitrate detection. Test strips were fabricated using a simple and fast method of step-by-step immersion into reagents so that each strip contained a single detection pad for nitrite detection and another separate pad for nitrate detection. To reduce nitrate to nitrite, zinc microparticles suspended in ethanolic solution of polyvinylpyrrolidone (PVP) were uniformly immobilized on the paper strips that were previously impregnated in the Griess reagent and dried. The Griess reagent components were optimized to reach the highest color intensity. The optimized test strip was able to determine both nitrite and nitrate with respective detection limits of 0.43 and 9.43 mg/kg and a detection time of 60 s. The performance of the new test strips was evaluated for the simultaneous colorimetric detection of nitrite and nitrate in water and different food samples.

C-GCS@ZIF-F/PL based electrochemical sensor for rapid and ultra-sensitive detection of rutin in foods.

Herein, a stable and ultra-sensitive rutin electrochemical sensor was successfully developed. This sensor based on glassy carbon electrode (GCE) modified with C-GCS@ZIF-F/PL nanocomposite, which was made of thermally carbonized glucose (GCS) doped with flower-like ZIF (ZIF-F) and pencil lead (PL). The electrochemical response of rutin was considerably significant at C-GCS@ZIF-F/PL/GCE, demonstrating favorable conductivity and electrocatalytic properties for detection of rutin. Under optimal conditions, the linear range is 0.1-100 µM, with a low detection limit (LOD) of 0.0054 µM. It also exhibits excellent stability, reproducibility, as well as selectivity over common interfering ions such as Na+, uric acid, quercetin and riboflavin, etc. Meanwhile, the practical utility of developed sensor was evaluated in food samples including honey, orange, and buckwheat tea, achieving satisfactory recovery rates ranging from 98.2% to 101.7%. This paper introduces a novel technique for the detection of rutin in foods.

Advanced chemically modified electrodes and platforms in food analysis and monitoring.

Electrochemical sensors and electroanalytical techniques become emerging as effective and low-cost tools for rapid assessment of special parameters of the food quality. Chemically modified electrodes are developed to change properties and behaviour, particularly sensitivity and selectivity, of conventional electroanalytical sensors. Within this comprehensive review, novel trends in chemical modifiers material structure, electrodes construction and flow analysis platforms are described and evaluated. Numerous recent application examples for the detection of food specific analytes are presented in a form of table to stimulate further development in both, the basic research and commercial field.

Cost-effective fully 3D-printed on-drop electrochemical sensor based on carbon black/polylactic acid: a comparative study with screen-printed sensors in food analysis.

3D-printing technology allows scientist to fabricate easily electrochemical sensors. Until now, these sensors were designed employing a large amount of material, which increases the cost and decreases manufacturing throughput. In this work, a low-cost 3D-printed on-drop electrochemical sensor (3D-PES) was fully manufactured by fused filament fabrication, minimizing the number of printing layers. Carbon black/polylactic acid filament was employed, and the design and several printing parameters were optimized to yield the maximum electroanalytical performance using the minimal amount of material. Print speed and extrusion width showed a critical influence on the electroanalytical performance of 3D-PES. Under optimized conditions, the fabrication procedure offered excellent reproducibility (RSD 1.3% in working electrode diameter), speed (< 3 min/unit), and costs (< 0.01 $ in material cost). The 3D-PES was successfully applied to the determination of phloridzin in apple juice. The analytical performance of 3D-PES was compared with an equivalent commercial on-drop screen-printed electrode, yielding similar precision and accuracy but lower sensitivity. However, 3D-PES provides interesting features such as recyclability, biodegradability, low-cost, and the possibility of being manufactured near the point of need, some of which meets several demands of Green Chemistry. This cost-effective printing approach is a green and promising alternative for manufacturing disposable and portable electroanalytical devices, opening new possibilities not only in on-site food analysis but also in point-of-care testing.

A sensitive enzyme-free electrochemical sensor based on ZnWO4@co-MNPC@MIP for specific recognition and determination of chloramphenicol in milk sample.

We have carefully built a new chloramphenicol (CAP) electrochemical sensor, which takes the zinc tungstate @ cobalt magnetic nanoporous carbon @ molecularly imprinted polymer (ZnWO4@Co-MNPC@MIP) as the core. First, we successfully prepared Co-MNPC nanomaterials using an efficient one-step hydrothermal method and a direct carbonization method. Next, we recombined ZnWO4 with Co-MNPC and synthesized the completely new ZnWO4@Co-MNPC complex by using the hydrothermal method. To further improve its performance, we combined ZnWO4@Co-MNPC with a molecular imprinted polymer and coated a molecular imprinted (MIP) shell on the surface of ZnWO4@Co-MNPC by precipitation polymerization. This shell not only gives the sensor a new performance but also gives it a stronger peak current, resulting in a more accurate detection of CAP. Under optimal conditions, the ZnWO4@Co-MNPC@MIP (MMIP) electrode has a stronger CAP detection peak current than the one-component electrode, with a fairly wide linear range: 0.007-200 µM and 200-1400 µM. Even more surprisingly, the detection limit is as low as 0.0027 µM, which allows the sensor to maintain excellent selectivity and stability in the face of various interferences, making it an excellent electrochemically modified electrode. Compared to magnetic non-molecular imprint sensors (MNIPs), MMIP sensors have higher detection efficiency. After practical application, we found that the ZnWO4@Co-MNPC@MIP modified electrode was satisfactory in milk samples.

A nanosilica-coated thread-based analytical device for nitrate and nitrite detection in food samples.

A new microfluidic thread-based analytical device (µTAD) for nitrate and nitrite determination in food samples was developed. The cotton thread substrate was coated with nanosilica to increase its hydrophilicity and stability, and polylactic acid was applied to one end of the nanosilica-coated thread to constrain the fluid flow along the thread in one direction. Quantification of nitrate and nitrite was based on the modified Griess reaction, using sulfanilamide and N-(1-naphthyl) ethylenediamine as chromogenic reagents, and utilizing a distance-based detection technique. Linear responses were observed in a range of 4-25 mg L-1 (R2 = 0.9991) for nitrite and a range of 8-50 mg L-1 (R2 = 0.9989) for nitrate. The limits of detection for nitrite and nitrate were 1.5 and 3.1 mg L-1, respectively. The detection time was 5 min for nitrite analysis, and 7 min for nitrate analysis. The new method demonstrated good precision, accuracy, selectivity, and stability. The performance of the proposed µTAD for nitrite and nitrate determination in real food samples was comparable to that of the conventional UV-Vis spectrophotometric method. The proposed µTAD could serve as a simple, low-cost, and portable method for nitrite and nitrate detection in food samples.

A portable europium complex-loaded fluorescent test paper combined with smartphone analysis for the on-site and visual detection of mancozeb in food samples.

The on-site detection of mancozeb in food samples holds immense value for food safety. A red-fluorescent europium complex (Eu-PYDC-Phen) has been prepared and employed as a fluorescence probe for mancozeb detection. The optimized probe suspension exhibits excellent detection performances, including a wide linear range (0-0.24 mM), low detection limit (65 nM), rapid response (2 mins) and high selectivity. Moreover, a portable detection platform was carefully designed, integrating the Eu-PYDC-Phen-based fluorescent test strips with smartphone color recognition software. This innovative platform enables visual and on-site detection of mancozeb in tomato, apple, and lettuce, achieving satisfactory recovery rates (90.34 to 106.50%). Furthermore, the integration of machine learning techniques based on hierarchical clustering algorithm has the potential to further improve the prediction and decision-making efficiency in mancozeb detection. This work provides an economical, convenient, and reliable strategy for on-site detection of pesticide in agricultural products, thereby making a meaningful contribution to food safety.

Cu2(OH)3NO3 nanozyme sensor array for the discrimination of multiple sulfides in food.

In the food industry, sulfides are commonly used as preservatives and flavor regulators. However, long-term excessive intake of sulfides can lead to serious health problems. Therefore, developing efficient sulfide detection methods is particularly important. Here, we have effectively synthesized a novel bifunctional copper hydroxide nitrate (Cu2(OH)3NO3) nanozyme with outstanding peroxidase-like and laccase-like behaviors in basic deep eutectic solvents (DES). Because the various types of sulfides have diverse regulatory effects on the two catalytic behaviors of Cu2(OH)3NO3, a two channel nanozyme sensor array based on the peroxidase-like and laccase-like behaviors of Cu2(OH)3NO3 was constructed and successfully used for the identification of six kinds of sulfides (Na2S, Na2S2O3, Na2SO3, Na2SO4, NaHSO3, and Na2S2O8). Remarkably, the sensor array has achieved successful discrimination among six sulfides present in wine, egg, and milk samples. Finally, the sensor array has successfully distinguished and differentiated three actual samples (wine, egg, and milk). This study is of great significance in promoting the efficient construction of array units and improving the effective identification of sulfides in complex food samples.

Handheld methanol detector for beverage analysis: interlaboratory validation.

Methanol is a toxic alcohol contained in alcoholic beverages as a natural byproduct of fermentation or added intentionally to counterfeits to increase profit. To ensure consumer safety, many countries and the EU have established strict legislation limits for methanol content. Methanol concentration is mostly detected by laboratory instrumentation since mobile devices for routine on-site testing of beverages in distilleries, at border stations or even at home are not available. Here, we validated a handheld methanol detector for beverage analysis in an ISO 5725 interlaboratory trial: a total of 119 measurements were performed by 17 independent participants (distilleries, universities, authorities, and competence centers) from six countries on samples with relevant methanol concentrations (0.1, 1.5 vol%). The detector was based on a microporous separation filter and a nanostructured gas sensor allowing on-site measurement of methanol down to 0.01 vol% (in the liquid) within only 2 min by laymen. The detector showed excellent repeatability (<5.4%), reproducibility (<9.5%) and small bias (<0.012 vol%). Additional measurements on various methanol-spiked alcoholic beverages (whisky, rum, gin, vodka, tequila, port, sherry, liqueur) indicated that the detector is not interfered by environmental temperature and spirit composition, featuring excellent linearity (R2 > 0.99) down to methanol concentrations of 0.01 vol%. This device has been recently commercialized (Alivion Spark M-20) with comparable accuracy to the gold-standard gas chromatography and can be readily applied for final product inspection, intake control of raw materials or to identify toxic counterfeit products.

Recent advances and trends in innovative biosensor-based devices for heavy metal ion detection in food.

Low-cost, reliable, and efficient biosensors are crucial in detecting residual heavy metal ions (HMIs) in food products. At present, based on distance-induced localized surface plasmon resonance of noble metal nanoparticles, enzyme-mimetic reaction of nanozymes, and chelation reaction of metal chelators, the constructed optical sensors have attracted wide attention in HMIs detection. Besides, based on the enrichment and signal amplification strategy of nanomaterials on HMIs and the construction of electrochemical aptamer sensing platforms, the developed electrochemical biosensors have overcome the plague of low sensitivity, poor selectivity, and the inability of multiplexed detection in the optical strategy. Moreover, along with an in-depth discussion of these different types of biosensors, a detailed overview of the design and application of innovative devices based on these sensing principles was provided, including microfluidic systems, hydrogel-based platforms, and test strip technologies. Finally, the challenges that hinder commercial application have also been mentioned. Overall, this review aims to establish a theoretical foundation for developing accurate and reliable sensing technologies and devices for HMIs, thereby promoting the widespread application of biosensors in the detection of HMIs in food.

Machine learning powered CN-coordinated cobalt nanoparticles embedded cellulosic nanofibers to assess meat quality via clenbuterol monitoring.

The World Anti-Doping Agency (WADA) has prohibited the use of clenbuterol (CLN) because it induces anabolic muscle growth while potentially causing adverse effects such as palpitations, anxiety, and muscle tremors. Thus, it is vital to assess meat quality because, athletes might have positive test for CLN even after consuming very low quantity of CLN contaminated meat. Numerous materials applied for CLN monitoring faced potential challenges like sluggish ion transport, non-uniform ion/molecule movement, and inadequate electrode surface binding. To overcome these shortcomings, herein we engineered bimetallic zeolitic imidazole framework (BM-ZIF) derived N-doped porous carbon embedded Co nanoparticles (CN-CoNPs), dispersed on conductive cellulose acetate-polyaniline (CP) electrospun nanofibers for sensitive electrochemical monitoring of CLN. Interestingly, the smartly designed CN-CoNPs wrapped CP (CN-CoNPs-CP) electrospun nanofibers offers rapid diffusion of CLN molecules to the sensing interface through amine and imine groups of CP, thus minimizing the inhomogeneous ion transportation and inadequate electrode surface binding. Additionally, to synchronize experiments, machine learning (ML) algorithms were applied to optimize, predict, and validate voltametric current responses. The ML-trained sensor demonstrated high selectivity, even amidst interfering substances, with notable sensitivity (4.7527 µA/µM/cm2), a broad linear range (0.002-8 µM), and a low limit of detection (1.14 nM). Furthermore, the electrode exhibited robust stability, retaining 98.07% of its initial current over a 12-h period. This ML-powered sensing approach was successfully employed to evaluate meat quality in terms of CLN level. To the best of our knowledge, this is the first study of using ML powered system for electrochemical sensing of CLN.

A smartphone-based sensor for detection of iron and potassium in food and beverage samples.

A novel approach for simultaneous detection of iron and potassium via a smartphone-based potentiometric method is proposed in this study. The screen printed electrodes were modified with carbon black nanomaterial and ion selective membrane including zinc (II) phtalocyanine as the ionophore. The developed Fe3+-selective electrode and K+-selective electrode exhibited detection limits of 1.0 × 10-6 M and 1.0 × 10-5 M for Fe3+ and K+ ions, respectively. The electrodes were used to simultaneously detect Fe3+ and K+ ions in apple juice, skim milk, soybean and coconut water samples with recovery values between 90%-100.5%, and validated against inductively coupled plasma-optical emission spectrometry. Due to the advantageous characteristics of the sensors and the portability of Near Field Communication potentiometer supported with a smartphone application, the proposed method offers sensitive and selective detection of iron and potassium ions in food and beverage samples at the point of need.

An electrochemical aptasensor for zearalenone detection based on the Co3O4/MoS2/Au nanocomposites and hybrid chain reaction.

An electrochemical aptasensor was used for the fast and sensitive detection of zearalenone (ZEN) based on the combination of Co3O4/MoS2/Au nanocomposites and the hybrid chain reaction (HCR). The glassy carbon electrode was coated with Co3O4/MoS2/Au nanomaterials to immobilize the ZEN-cDNA that had been bound with ZEN-Apt by the principle of base complementary pairing. In the absence of ZEN, the HCR could not be triggered because the ZEN-cDNA could not be exposed. After ZEN was added to the surface of the electrode, a complex structure was produced on the modified electrode by the combination of ZEN and ZEN-Apt. Therefore, the ZEN-cDNA can raise the HCR to produce the long-strand dsDNA structure. Due to the formation of dsDNA, the methylene blue (MB) could be inserted into the superstructure of branched DNA and the peak currents of the MB redox signal dramatically increased. So the concentration of ZEN could be detected by the change of signal intensity. Under optimized conditions, the developed electrochemical biosensing strategy showed an outstanding linear detection range of 1.0×10-10 mol/L to 1.0×10-6 mol/L, a low detection limit (LOD) of 8.5×10-11 mol/L with desirable selectivity and stability. Therefore, the fabricated platform possessed a great application potential in fields of food safety, medical detection, and drug analysis.

Portable sensing methods based on carbon dots for food analysis.

Food analysis is significantly important in monitoring food quality and safety for human health. Traditional methods for food detection mainly rely on benchtop instruments and require a certain amount of analysis time, which promotes the development of portable sensors. Portable sensing methods own many advantages over traditional techniques such as flexibility and accessibility in diverse environments, real-time monitoring, cost-effectiveness, and rapid deployment. This review focuses on the portable approaches based on carbon dots (CDs) for food analysis. CDs are zero-dimensional carbon-based material with a size of less than 10 nm. In the manner of sensing, CDs exhibit rich functional groups, low biotoxicity, good biocompatibility, and excellent optical properties. Furthermore, there are many methods for the synthesis of CDs using various precursor materials. The incorporation of CDs into food science and engineering for enhancing food safety control and risk assessment shows promising prospects.

Integrated molybdenum single atom array sensors with multichannels for nitrite detection in foods.

Nitrite (NO2-) is present in a variety of foods, but the excessive intake of NO2- can indirectly lead to carcinogenic, teratogenic, mutagenicity and other risks to the human body. Therefore, the detection of NO2- is crucial for maintaining human health. In this study, an integrated array sensor for NO2- detection is developed based on molybdenum single atom material (IMSMo-SAC) using high-resolution electrohydrodynamic (EHD) printing technology. The sensor comprises three components: a printed electrode array, multichannels designed on polydimethylsiloxane (PDMS) and an electronic signal process device with bluetooth. By utilizing Mo-SAC to facilitate electron transfer during the redox reaction, rapid and efficient detection of NO2- can be achieved. The sensor has a wide linear range of 0.1 µM-107.8 mM, a low detection limit of 33 nM and a high sensitivity of 0.637 mA-1mM-1 cm-2. Furthermore, employing this portable array sensor allows simultaneously measurements of NO2- concentrations in six different foods samples with acceptable recovery rates. This array sensor holds great potential for detecting of small molecules in various fields.