Signal-enhanced SERS-sensors of CAR-PLS and GA-PLS coupled AgNPs for ochratoxin A and aflatoxin B1 detection

Nanosilver-mediated enzyme-free electrochemical immunosensor with enhanced stability for aflatoxin B1 detection in food safety

The development and research of electrochemical immunoassays have attracted considerable attention. However, traditional electrochemical immunoassays inevitably require the participation of biological enzymes, which suffer from high cost, poor stability, inconvenient storage and easy inactivation. Herein, we constructed a bio-enzyme-free electrochemical immunoassay system specifically for the detection of aflatoxin B1 (AFB1). This method was based on the traditional antigen-antibody immune recognition system utilizing the nanosilver particles (NSPs) as signal markers to replace conventional natural enzymes. Subsequently, the labeled NSPs were transferred to silver ions in the presence of nitric acid. The concentration of silver ions was determined using anodic stripping voltammetry (ASV), which correlates closely to the concentration of the target. The current intensity measured by the bio-enzyme-free electrochemical sensor exhibited a negative correlation with the concentration of AFB1. Under optimized conditions, the electrochemical sensor was used to detect AFB1 in the dynamic concentration range of 0.01-100 ng mL-1, and the limit of detection was 0.4882 pg mL-1. The spiked recovery range of AFB1 in corn starch was determined to be between 100.98% and 109.42%, while the relative standard deviation (RSD) range was found to be from 0.34% to 3.82%. These results indicate that the electrochemical immunosensor without biological enzyme labeling has reliable accuracy, and the sensor has a broad application prospect in AFB1 detection.

Label-free localized surface plasmon resonance (LSPR) biosensor, based on Au-Ag NPs embedded in TiO2 matrix, for detection of Ochratoxin-A (OTA) in wine

Ochratoxin-A (OTA) is a widespread foodstuff contaminant with potential carcinogenic effects. Innovative sensing technologies that allow on-site and sensitive food screening can have a significant impact on food and environment safety. A novel and quantitative label-free LSPR-based biosensor was specifically designed for OTA detection, employing a portable LSPR spectroscopy sensing system for efficient on-site and cost-effective analysis. This biosensor is comprised of monoclonal anti-OTA antibodies immobilized on the surface of sputtered Au-Ag nanoparticles embedded in a TiO2 matrix. Under optimized conditions, the LSPR-based biosensor demonstrated a linear dynamic response from 0.05 to 2 ng mL-1, with an estimated limit of detection at 7 pg mL-1, using 55 μL of sample, outperforming commercial ELISA technique in relevant bioanalytical parameters. Sensitivity in OTA detection is crucial because it ensures the accurate identification of low concentrations, which is essential for preventing health risks associated to cumulative ingestion of contaminated food products. The robustness and feasibility of the presented LSPR-based biosensing was tested using spiked white wine, exhibiting a satisfactory recovery of 93 %-113 %, confirming its efficacy in a complex matrix.

A Review of Current Developments in Functionalized Mesoporous Silica Nanoparticles: From Synthesis to Biosensing Applications

Functionalized mesoporous silica nanoparticles (MSNs) have been widely investigated in the fields of nanotechnology and material science, owing to their high surface area, diverse structure, controllable cavity, high biocompatibility, and ease of surface modification. In the past few years, great efforts have been devoted to preparing functionalized MSNs for biosensing applications with satisfactory performance. The functional structure and composition in the synthesis of MSNs play important roles in high biosensing performance. With the development of material science, diverse functional units have been rationally incorporated into mesoporous structures, which endow MSNs with design flexibility and multifunctionality. Here, an overview of the recent developments of MSNs as nanocarriers is provided, including the methodologies for the preparation of MSNs and the nanostructures and physicochemical properties of MSNs, as well as the latest trends of MSNs and their use in biosensing. Finally, the prospects and challenges of MSNs are presented.

Label-free and highly sensitive detection of aflatoxin B1 by Ag IANPs via surface-enhanced Raman spectroscopy

Aflatoxin B1 (AFB1), a pernicious constituent of the aflatoxin family, predominantly contaminates cereals, oils, and their derivatives. Acknowledged as a Class I carcinogen by the World Health Organization (WHO), the expeditious and quantitative discernment of AFB1 remains imperative. This investigation delineates that aluminum ions can precipitate the coalescence of iodine-modified silver nanoparticles, thereby engendering hot spots conducive for label-free AFB1 identification via Surface-Enhanced Raman Spectroscopy (SERS). This methodology manifests a remarkable limit of detection (LOD) at 0.47 fg/mL, surpassing the sensitivity thresholds of conventional survey techniques. Moreover, this method has good anti-interference ability, with a relative error of less than 10% and a relative standard deviation of less than 6% in quantitative results. Collectively, these findings illuminate the substantial application potential and viability of this approach in the quantitative analysis of AFB1, underpinning a significant advancement in food safety diagnostics.

SERS Performance Factor: A Convenient Parameter for the Enhancement Evaluation of SERS Substrates

Surface-enhanced Raman spectroscopy (SERS), with molecular fingerprint information and single-molecule sensitivity, has been widely used for qualitative and quantitative analysis in various fields. Plenty of nanostructured plasmonic materials have been fabricated to achieve high SERS activity. Currently, great difficulty lies in evaluating the SERS performance among substrates, making it difficult to standardize. Addressing this problem, this work proposed the SERS performance factor (S P F = Δ I S E R S Δ C S E R S / Δ I R a m a n Δ C R a m a n ) as a practically operational parameter to evaluate the sensitivity of SERS substrates. Experimentally, SPF can be obtained by taking the ratio of the slopes (i.e., the sensitivity) for concentration-dependent SERS and normal Raman measurements in the linear range of the intensity response under identical experimental conditions. Theoretically, SPF quantitatively describes the overall contribution to the SERS performance, (i.e., the electromagnetic (EM) enhancement of the SERS substrate and the interfacial interaction between the probe and substrate). The use of SPF as the criterion for evaluating the SERS performance was validated on Au nanoparticles in colloidal and solid states, where the tendency of SPF is consistent with that of the sensitivity of the probe molecules. Derived from the typically used surface enhancement factor EF in which accurate parameters are hardly achievable and different from concentration-dependent analytical enhancement factor AEF, SPF distinguishes itself with a simpler calculation and thereby offers a convenient and reliable protocol for the evaluation of the performance of different SERS substrates, which is very important to the practical application of SERS.

Farm to fork applications: how vibrational spectroscopy can be used along the whole value chain?

Vibrational spectroscopy is a nondestructive analysis technique that depends on the periodic variations in dipole moments and polarizabilities resulting from the molecular vibrations of molecules/atoms. These methods have important advantages over conventional analytical techniques, including (a) their simplicity in terms of implementation and operation, (b) their adaptability to on-line and on-farm applications, (c) making measurement in a few minutes, and (d) the absence of dangerous solvents throughout sample preparation or measurement. Food safety is a concept that requires the assurance that food is free from any physical, chemical, or biological hazards at all stages, from farm to fork. Continuous monitoring should be provided in order to guarantee the safety of the food. Regarding their advantages, vibrational spectroscopic methods, such as Fourier-transform infrared (FTIR), near-infrared (NIR), and Raman spectroscopy, are considered reliable and rapid techniques to track food safety- and food authenticity-related issues throughout the food chain. Furthermore, coupling spectral data with chemometric approaches also enables the discrimination of samples with different kinds of food safety-related hazards. This review deals with the recent application of vibrational spectroscopic techniques to monitor various hazards related to various foods, including crops, fruits, vegetables, milk, dairy products, meat, seafood, and poultry, throughout harvesting, transportation, processing, distribution, and storage.

Simultaneous detection of multiple mycotoxins in agricultural products: Recent advances in optical and electrochemical sensing methods

Mycotoxin contamination poses serious threats to human and animal health. Food and environmental systems are often simultaneously contaminated with multiple mycotoxins, a problem that is further exacerbated by the synergistic toxicological effects of these co-occurring mycotoxins. Consequently, the development of rapid detection methods capable of simultaneously identifying multiple mycotoxins in agricultural products is essential to prevent their entry into the food chain. Compared to standard detection methods, optical and electrochemical (EC) sensing methods have distinct advantages for the rapid detection of mycotoxins. This review comprehensively summarizes the latest advancements in the field of simultaneous detection of multiple mycotoxins using optical and EC sensing methods over the last 6 years (2018-2024). First, the review introduces the classification and relevant principles of optical and EC sensing methods. Thereafter, it emphasizes innovative simultaneous detection strategies within these approaches. Finally, it discusses current challenges and offers a reference for further research. Currently, the main challenge lies in the mutual interference among targets, making the development of an interference-free detection platform essential. Furthermore, the ongoing development of integrated technology is expected to aid regulatory authorities in improving the quality of agricultural products for field applications.

Quantitative SERS sensor for mycotoxins with extraction and identification function

The development of new sensors for on-site food toxin monitoring that combine extraction, analytes distinction and detection is important in resource-limited environments. Surface-enhanced Raman scattering (SERS)-based signal readout features fast response and high sensitivity, making it a powerful method for detecting mycotoxins. In this work, a SERS-based assay for the detection of multiple mycotoxins is presented that combines extraction and subsequent detection, achieving an analytically relevant detection limit (∼ 1 ng/mL), which is also tested in corn samples. This sensor consists of a magnetic-core and mycotoxin-absorbing polydopamine-shell, with SERS-active Au nanoparticles on the outer surface. The assay can concentrate multiple mycotoxins, which are identified through multiclass partite least squares analysis based on their SERS spectra. We developed a strategy for the analysis of multiple mycotoxins with minimal sample pretreatment, enabling in situ analytical extraction and subsequent detection, displaying the potential to rapidly identify lethal mycotoxin contamination on site.

Cascade Amplifying Electrochemical Bioanalysis for Zearalenone Detection in Agricultural Products: Utilizing a Glucose-Fenton-HQ System on Bimetallic-ZIF@CNP Nanocomposites

The integration of advanced materials and signaling cascade strategies is a promising and highly relevant topic for enhancing the performance of bioanalysis. In this study, a three-stage cascade amplification electrochemical bioanalysis (TCAE-bioanalysis) was developed and evaluated for the detection of zearalenone (ZEN). This method couples immunoreaction with a glucose-Fenton-hydroquinone (HQ) system on bimetallic-ZIF (B-ZIF)@CNP nanocomposites. The B-ZIF@CNP-modified gold electrode (AuE) was prepared, offering high conductivity and an excellent reaction interface. The immunoreaction introduced glucose oxidase (GOx) into the glucose-Fenton-HQ system, generating an abundant electron signal. The method achieved an ultrasensitive limit of detection (LOD) as low as 0.87 pg/mL, with an IC50 value of 30.8 pg/mL, representing a 229-fold enhancement in sensitivity compared to ELISA using the same monoclonal antibody (McAb). The specificity, reliability, and practicality of this approach were thoroughly demonstrated for agricultural product samples. Additionally, the TCAE-bioanalysis offers several advantages, including simplified preparation for advanced B-ZIF@CNP, a convenient detection system, and the use of common and environmentally friendly reagents. This study presents a comprehensive approach to improving electrochemical bioanalysis and may also expand the application of signaling cascades and environmentally friendly techniques in other biosensing or diagnostic contexts.

Enzyme- and label-free cascade isothermal amplification aptasensor for the ultrasensitive detection of ochratoxin A

BACKGROUND

Ultrasensitive detection is crucial for the early warning and intervention of risk factors, ultimately benefiting the environment and human health. Low levels of ochratoxin A (OTA) present a hidden yet significant threat, and rapid detection via high-performing biosensors is therefore essential.

RESULTS

A cascade isothermal amplification aptasensor (CIA-aptasensor) was designed for OTA detection. On the surface of a magnetic bead probe, the OTA level was converted into positively correlated trigger cDNA through its competitive binding with OTA-Apt. The released trigger cDNA activated catalytic hairpin assembly followed by coupling with a hybridization chain reaction to achieve CIA. After adding graphene oxide and SYBR Green I, the background interference was eliminated to specifically obtain OTA-related fluorescence. The ultrasensitive limit of detection was 0.22 pg mL-1, an improvement of 1368-fold over conventional enzyme-linked aptamer sorbent assay by the same OTA-Apt, demonstrating satisfactory reliability and practicability. Thus, the CIA-aptasensor provides an enzyme- and label-free simplified homogeneous system with minimal background interference using isothermal conditions.

SIGNIFICANCE

This study provides a polymerase chain reaction-like approach for enhancing the sensitivity and performance of a biosensor, which could be extended for the application of CIA and label-free signaling strategy to other risk factors.

Exo I-based cyclic digestion coupled with synergistic enhancement strategy for integrating dual-mode optical aptasensor platform

The improvement of dual-mode techniques was of particular interest to researchers, which might enhance the detection performance and applicability. Here, a dual-mode optical aptasensor (DO-aptasensor) platform based on exonuclease I (Exo I) cyclic digestion and synergistic enhancement strategy had proposed for zearalenone (ZEN). Following the preparation of dumbbell-shaped signal probe, the Exo I-based cyclic digestion amplification performed, and then the synergistic enhancement effect carried out to achieve the Poly-HRP-based colorimetry and FAM-SGI-based fluorescence. The efficient homogeneous system realized through the magnetic separation, while the signal interference further eliminated by the graphene oxide (GO). The LOD values were as low as 0.067 ng mL-1 for colorimetry mode and 0.009 ng mL-1 for fluorescence mode, which reduced 23-fold and 172-fold than ELASA by same ZEN-Apt. This promising platform gave rise to a dual-mode optical readout, improved sensitivity and positively correlated detection. Meanwhile, the DO-aptasensor also exhibited the acceptable specificity, desirable reliability and excellent practicability. This novel avenue of aptasensor platform hold great potential for dual-mode optical monitoring of other targets, which can further expand the application scope of Exo I-based signal amplification and synergistic enhancement effect.

Plasmonic colorimetry and G-quadruplex fluorescence-based aptasensor: A dual-mode, protein-free and label-free detection for OTA

G-quadruplexes (G4) have received significant attention in the field of aptasensors owing to their unique physicochemical characteristics. A dual-mode, protein-free and label-free aptamer sensor based on plasmonic colorimetry and G4 fluorescence (PC@GF-aptasensor) was proposed for ochratoxin A (OTA). Colorimetry mode was achieved through the surface plasmon resonance (SPR) effect, which related to the OTA-Apt-based G4-OTA. The fluorescence mode was reflected by the insertion of thioflavin T (ThT) into G4-OTA. The OTA could be interpreted via three readouts: (1) naked eye (LOD of 2.0 ng mL-1), (2) smartphone (LOD of 1.65 ng mL-1), and (3) spectrofluorometer (LOD of 0.93 ng mL-1). The PC@GF-aptasensor exhibited several advantages, such as a standardised recognition group, simplified operation, low background signal, and practicality. The proposed PC@GF-aptasensor integrated SPR-based multicolour interpretation and ThT-inserted fluorescence reflection to obtain a dual-mode optical biosensor, which may provide valuable insights for the development of other targets with G4-based aptamers.

Navigating the development of silver nanoparticles based food analysis through the power of artificial intelligence

In the ongoing pursuit of enhancing food safety and quality through advanced technologies, silver nanoparticles (AgNPs) stand out for their antimicrobial properties. Despite being overshadowed by other nanoparticles in food sensing applications, AgNPs possess inherent qualities that make them effective tools for rapid and selective contaminant detection in food matrices. This review aims to reinvigorate the interest in AgNPs in the food industry, emphasizing their sensing mechanism and the transformative potential of integrating them with artificial intelligence (AI) for enhanced food safety monitoring. It discusses key AI tools and principles in the food industry, demonstrating their positive impact on food analytical chemistry. The interplay between AI and biosensors offers many advantages and adaptability to dynamic analytical challenges, significantly improving food safety monitoring and potentially redefining the landscape of food safety and quality assurance.

Detection of Anthocyanins in Potatoes Using Micro-Hyperspectral Images Based on Convolutional Neural Networks

The color potato has the function of both a food and vegetable. The color potato not only contains various amino acids and trace elements needed by the human body but also contains anthocyanins. Anthocyanins have many functions, such as antioxidation, inflammation inhibition, vision improvement, and cancer prevention, so colored potatoes are deeply loved by consumers and have good market prospects. However, at present, the detection of anthocyanin content in color potatoes mainly depends on chemical methods, which are time-consuming and laborious, so it is necessary to study a fast and accurate detection method. In this study, microscopic hyperspectral equipment was used to collect the spectral information of the outer skin and inner skin of potatoes. The original spectrum, pretreatment spectrum, and characteristic spectrum variables of the outer skin and inner skin were predicted by the convolution neural network (CNN) algorithm and partial least squares regression (PLS) algorithm, respectively, and the performance of the model was evaluated by the prediction set correlation coefficient (Rp), prediction set root mean square error (RMSEP), correction set correlation coefficient (Rc), correction set root mean square error (RMSEC), and residual prediction deviation (RPD). The results revealed that the inner skin Raw + CNN model constructed under raw spectral data is optimal with Rc = 0.9508, RMSEC = 0.0374%, Rp = 0.9461, RMSEP = 0.2361% and RPD = 4.4933. The inner skin Savitzky-Golay (SG) + Detrend (DET) + CNN model constructed from pre-processed spectral data is optimal with Rc = 0.9499, RMSEC = 0.0359%, Rp = 0.9439, RMSEP = 0.2384%, RPD = 4.6516. The inner skin DET + competitive adaptive reweighted sampling (CARS) +CNN model constructed from the feature-based spectral data was optimal with Rc = 0.9527, RMSEC = 0.0708%, Rp = 0.9457, RMSEP = 0.2711%, and RPD = 4.1623. It can be seen that the Rp, RMSEP, Rc, RMSEC, and RPD values for modeling the spectral information of the inner skin were higher than those of the outer skin under the three different spectral data. The prediction accuracy of the model built by the CNN algorithm was better than the conventional algorithm PLS, the application of the CNN algorithm in inner skin can achieve accurate prediction of anthocyanin content in potato.

Recent advances in nanomaterial-based optical biosensors for food safety applications: Ochratoxin-A detection, as case study

Global population growth tremendously impacts the global food industry, endangering food safety and quality. Mycotoxins, particularly Ochratoxin-A (OTA), emerge as a food chain production threat, since it is produced by fungus that contaminates different food species and products. Beyond this, OTA exhibits a possible human toxicological risk that can lead to carcinogenic and neurological diseases. A selective, sensitive, and reliable OTA biodetection approach is essential to ensure food safety. Current detection approaches rely on accurate and time-consuming laboratory techniques performed at the end of the food production process, or lateral-flow technologies that are rapid and on-site, but do not provide quantitative and precise OTA concentration measurements. Nanoengineered optical biosensors arise as an avant-garde solution, providing high sensing performance, and a fast and accurate OTA biodetection screening, which is attractive for the industrial market. This review core presents and discusses the recent advancements in optical OTA biosensing, considering engineered nanomaterials, optical transduction principle and biorecognition methodologies. Finally, the major challenges and future trends are discussed, and current patented OTA optical biosensors are emphasized for a particular promising detection method.

Advancing Mycotoxin Detection in Food and Feed: Novel Insights from Surface-Enhanced Raman Spectroscopy (SERS)

The implementation of low-cost and rapid technologies for the on-site detection of mycotoxin-contaminated crops is a promising solution to address the growing concerns of the agri-food industry. Recently, there have been significant developments in surface-enhanced Raman spectroscopy (SERS) for the direct detection of mycotoxins in food and feed. This review provides an overview of the most recent advancements in the utilization of SERS through the successful fabrication of novel nanostructured materials. Various bottom-up and top-down approaches have demonstrated their potential in improving sensitivity, while many applications exploit the immobilization of recognition elements and molecular imprinted polymers (MIPs) to enhance specificity and reproducibility in complex matrices. Therefore, the design and fabrication of nanomaterials is of utmost importance and are presented herein. This paper uncovers that limited studies establish detection limits or conduct validation using naturally contaminated samples. One decade on, SERS is still lacking significant progress and there is a disconnect between the technology, the European regulatory limits, and the intended end-user. Ongoing challenges and potential solutions are discussed including nanofabrication, molecular binders, and data analytics. Recommendations to assay design, portability, and substrate stability are made to help improve the potential and feasibility of SERS for future on-site agri-food applications.

Magnetic nanoparticle-based immunosensors and aptasensors for mycotoxin detection in foodstuffs: An update

Mycotoxin contamination of food crops is a global challenge due to their unpredictable occurrence and severe adverse health effects on humans. Therefore, it is of great importance to develop effective tools to prevent the accumulation of mycotoxins through the food chain. The use of magnetic nanoparticle (MNP)-assisted biosensors for detecting mycotoxin in complex foodstuffs has garnered great interest due to the significantly enhanced sensitivity and accuracy. Within such a context, this review includes the fundamentals and recent advances (2020-2023) in the area of mycotoxin monitoring in food matrices using MNP-based aptasensors and immunosensors. In this review, we start by providing a comprehensive introduction to the design of immunosensors (natural antibody or nanobody, random or site-oriented immobilization) and aptasensors (techniques for aptamer selection, characterization, and truncation). Meanwhile, special attention is paid to the multifunctionalities of MNPs (recoverable adsorbent, versatile carrier, and signal indicator) in preparing mycotoxin-specific biosensors. Further, the contribution of MNPs to the multiplexing determination of various mycotoxins is summarized. Finally, challenges and future perspectives for the practical applications of MNP-assisted biosensors are also discussed. The progress and updates of MNP-based biosensors shown in this review are expected to offer readers valuable insights about the design of MNP-based tools for the effective detection of mycotoxins in practical applications.

Advances in surface-enhanced Raman spectroscopy-based sensors for detection of various biomarkers

Surface enhanced Raman spectroscopy (SERS) allows the ultrasensitive detection of analytes present in traces or even single molecule levels by the generation of electromagnetic fields. It is a powerful vibrational spectroscopic method that is capable to detect traces of chemical and biological analytes. SERS technique is involved in the extremely sophisticated studies of molecules with high specificity and sensitivity. In the vicinity of nanomaterials decorated surfaces, SERS can monitor extremely low concentrations of analytes in a non-destructive manner with narrow line widths. This review article is focused on some recently developed SERS-based sensors for distinct types of analytes like disease-related biomarkers, organic and inorganic molecules, various toxins, dyes, pesticides, bacteria as well as single molecules. This study aims to enlighten the arising sensing approaches based on the SERS technique. Apart from this, some basics of the SERS technique like their mechanism, detection strategy, and involvement of some specific nanomaterials are also highlighted herein. Finally, the study concluded with some discussion of applications of SERS in various fields like food and environmental analysis.

Construction of a SERS platform for sensitive detection of aflatoxin B1 based on CRISPR strategy

Aflatoxin B1, a pathogen in the aflatoxin family, has attracted much attention due to the harmfulness in production and life. However, the common methods like high performance liquid chromatography used for detection of AFB1 have deficiency in complicated pretreatment processes, and the purification effect is not ideal. Herein, a SERS platform based on CRISPR strategy was designed for sensitive detection of AFB1. By synthesizing core-shell nanoparticles embedded with Raman silent region dye molecules, Prussian blue (PB), the detection of the sensor reduced background interference and the SERS signal was calibrated. At the same time, the high-efficiency reverse cleavage activity of cas12a was used to convert non-nucleic acid targets into nucleic acid, so as to achieve the effect of sensitive detection of AFB1 with a detection limit of 3.55  pg/mL. This study provides a new thought for SERS detection of non-nucleic acid targets in the future.

Label-free detection of trace level zearalenone in corn oil by surface-enhanced Raman spectroscopy (SERS) coupled with deep learning models

Surface-enhanced Raman spectroscopy (SERS) and deep learning models were adopted for detecting zearalenone (ZEN) in corn oil. First, gold nanorods were synthesized as a SERS substrate. Second, the collected SERS spectra were augmented to improve the generalization ability of regression models. Third, five regression models, including partial least squares regression (PLSR), random forest regression (RFR), Gaussian progress regression (GPR), one-dimensional convolutional neural networks (1D CNN), and two-dimensional convolutional neural networks (2D CNN), were developed. The results showed that 1D CNN and 2D CNN models possessed the best prediction performance, i.e., determination of prediction set (R_P²) = 0.9863 and 0.9872, root mean squared error of prediction set (RMSEP) = 0.2267 and 0.2341, ratio of performance to deviation (RPD) = 6.548 and 6.827, limit of detection (LOD) = 6.81 × 10^-4 and 7.24 × 10^-4 μg/mL. Therefore, the proposed method offers an ultrasensitive and effective strategy for detecting ZEN in corn oil.

Aflatoxin detection technologies: recent advances and future prospects

Aflatoxins have posed serious threat to food safety and human health. Therefore, it is important to detect aflatoxins in samples rapidly and accurately. In this review, various technologies to detect aflatoxins in food are discussed, including conventional ones such as thin-layer chromatography (TLC), high performance liquid chromatography (HPLC), enzyme linked immunosorbent assay (ELISA), colloidal gold immunochromatographic assay (GICA), radioimmunoassay (RIA), fluorescence spectroscopy (FS), as well as emerging ones (e.g., biosensors, molecular imprinting technology, surface plasmon resonance). Critical challenges of these technologies include high cost, complex processing procedures and long processing time, low stability, low repeatability, low accuracy, poor portability, and so on. Critical discussion is provided on the trade-off relationship between detection speed and detection accuracy, as well as the application scenario and sustainability of different technologies. Especially, the prospect of combining different technologies is discussed. Future research is necessary to develop more convenient, more accurate, faster, and cost-effective technologies to detect aflatoxins.

A rapid aroma quantification method: Colorimetric sensor-coupled multidimensional spectroscopy applied to black tea aroma

Aroma affects the quality of black tea, and the rapid evaluation of aroma quality is the key to realize the intelligent processing of black tea. A simple colorimetric sensor array coupled with a hyperspectral system was proposed for the rapid quantitative detection of key volatile organic compounds (VOCs) in black tea. Feature variables were screened based on competitive adaptive reweighted sampling (CARS). Furthermore, the performance of the models for VOCs quantitative prediction was compared. For the quantitative prediction of linalool, benzeneacetaldehyde, hexanal, methyl salicylate, and geraniol, the CARS-least-squares support vector machine model's correlation coefficients were 0.89, 0.95, 0.88, 0.80, and 0.78, respectively. The interaction mechanism of array dyes with VOCs was based on density flooding theory. The optimized highest occupied molecular orbital levels, lowest unoccupied molecular orbital energy levels, dipole moments, and intermolecular distances were determined to be strongly correlated with interactions between array dyes and VOCs.

Recent Advances in Biomolecular Detection Based on Aptamers and Nanoparticles

The fast, accurate detection of biomolecules, ranging from nucleic acids and small molecules to proteins and cellular secretions, plays an essential role in various biomedical applications. These include disease diagnostics and prognostics, environmental monitoring, public health, and food safety. Aptamer recognition (DNA or RNA) has gained extensive attention for biomolecular detection due to its high selectivity, affinity, reproducibility, and robustness. Concurrently, biosensing with nanoparticles has been widely used for its high carrier capacity, stability and feasibility of incorporating optical and catalytic activity, and enhanced diffusivity. Biosensors based on aptamers and nanoparticles utilize the combination of their advantages and have become a promising technology for detecting of a wide variety of biomolecules with high sensitivity, reliability, specificity, and detection speed. Via various sensing mechanisms, target biomolecules have been quantified in terms of optical (e.g., colorimetric and fluorometric), magnetic, and electrical signals. In this review, we summarize the recent advances in and compare different aptamer-nanoparticle-based biosensors by nanoparticle types and detection mechanisms. We also share our views on the highlights and challenges of the different nanoparticle-aptamer-based biosensors.

Recent advances in simultaneous detection strategies for multi-mycotoxins in foods

Mycotoxin contamination has become a challenge in the field of food safety testing, given the increasing emphasis on food safety in recent years. Mycotoxins are widely distributed, in heavily polluted areas. Food contamination with these toxins is difficult to prevent and control. Mycotoxins, as are small-molecule toxic metabolites produced by several species belonging to the genera Aspergillus, Fusarium, and Penicillium growing in food. They are considered teratogenic, carcinogenic, and mutagenic to humans and animals. Food systems are often simultaneously contaminated with multiple mycotoxins. Due to the additive or synergistic toxicological effects caused by the co-existence of multiple mycotoxins, their individual detection requires reliable, accurate, and high-throughput techniques. Currently available, methods for the detection of multiple mycotoxins are mainly based on chromatography, spectroscopy (colorimetry, fluorescence, and surface-enhanced Raman scattering), and electrochemistry. This review provides a comprehensive overview of advances in the multiple detection methods of mycotoxins during the recent 5 years. The principles and features of these techniques are described. The practical applications and challenges associated with assays for multiple detection methods of mycotoxins are summarized. The potential for future development and application is discussed in an effort, to provide standards of references for further research.

Dispersive micro solid phase extraction based ionic liquid functionalized ZnO nanoflowers couple with chromatographic methods for rapid determination of aflatoxins in wheat and peanut samples

Aflatoxins (AFs) contaminate agricultural products in a wide range of ways during their harvesting, storage and transport. Therefore, the detection of AFs has certain practical significance. Herein, a dispersive micro solid phase extraction (D-µSPE) technology was constructed based on 1-hexyl-3-methylimidazolium hexafluorophosphate ([HMIM][PF₆]) fabricated ZnO nanoflowers for AFs extraction from food matrix before HPLC procedure. The key parameters affecting the extraction efficiency were studied. Under optimal experimental conditions, the method showed excellent linearity with high correlation coefficients (≥0.994). LOD and LOQ were 0.034 and 0.114 μg/kg for AFB1, 0.024 and 0.082 μg/kg for AFB2, 0.067 and 0.226 μg/kg for AFG1 and 0.025 and 0.084 μg/kg for AFG2. The recovery of actual samples spiked with analytes (at 5, 15 and 20 μg/kg) were from 93.8 to 105.1%. Overall, an accurate AFs analysis method was developed and could be applied to the determination of AFs in various food and agricultural products.

Application of Analytical Technologies in the Discrimination and Authentication of Herbs from Fritillaria: A Review

Medicinal plants of Fritillaria are widely distributed in numerous countries around the world and possess excellent antitussive and expectorant effects. In particular, Fritillariae Bulbus (FB) as a precious traditional medicine has thousands of years of medical history in China. Herbs of Fritillaria have a high market value and demand while limited by harsh growing circumstances and scarce wild resources. As a consequence, fraudulent behaviors are regularly engaged by the unscrupulous merchants in an attempt to reap greater profits. It is of an urgent need to evaluate the quality of Fritillaria herbs and their products using various analytical instruments and techniques. This review has scrutinized approximately 160 articles from 1995 to 2022 published on the investigation of Fritillaria herbs and related herbal products. The botanical classification of genus Fritillaria, types of counterfeits, technologies applied for differentiating Fritillaria species were comprehensively summarized and discussed in the current review. Molecular and chromatographic identification were the dominant technologies in the authentication of Fritillaria herbs. Additionally, we brought some potential and promising technologies and analytical strategies into attention, which are worthy attempting in the future researches. This review could conduce to excellent reference value for further investigations of the authenticity assessment of Fritillaria species.

Intelligent evaluation of free amino acid and crude protein content in raw peanut seed kernels using NIR spectroscopy paired with multivariable calibration

Given the nutritional importance of peanuts, this study examined the free amino acid (FAA) and crude protein (CP) content in raw peanut seeds. Near-infrared spectroscopy (NIRS) was employed in combination with variable selection algorithms after successful reference data analysis using colorimetric and Kjeldahl methods. Ensuing the application of partial least squares (PLS) as a full spectral model, the genetic algorithm (GA), bootstrapping soft shrinkage (BOSS), uninformative variable elimination (UVE), and random frog (RF) models were tested and assessed. A comparison of correlation coefficients of prediction (R_p), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD) was performed to appraise the performance of the built models. Using RF-PLS, an unsurpassed outcome was achieved for FAA (R_p = 0.937, RPD = 3.38) and CP (R_p = 0.9261, RPD = 3.66). These findings demonstrated that NIR in combination with RF-PLS could be utilized for quantitative, rapid, and nondestructive prediction of FAA and CP in raw peanut seed samples.

A Narrative Review of Recent Advances in Rapid Assessment of Anthocyanins in Agricultural and Food Products

Anthocyanins (ACNs) are plant polyphenols that have received increased attention recently mainly due to their potential health benefits and applications as functional food ingredients. This has also created an interest in the development and validation of several non-destructive techniques of ACN assessments in several food samples. Non-destructive and conventional techniques play an important role in the assessment of ACNs in agricultural and food products. Although conventional methods appear to be more accurate and specific in their analysis, they are also associated with higher costs, the destruction of samples, time-consuming, and require specialized laboratory equipment. In this review article, we present the latest findings relating to the use of several spectroscopic techniques (fluorescence, Raman, Nuclear magnetic resonance spectroscopy, Fourier-transform infrared spectroscopy, and near-infrared spectroscopy), hyperspectral imaging, chemometric-based machine learning, and artificial intelligence applications for assessing the ACN content in agricultural and food products. Furthermore, we also propose technical and future advancements of the established techniques with the need for further developments and technique amalgamations.

Rapid monitoring of black tea fermentation quality based on a solution-phase sensor array combined with UV-visible spectroscopy

Rapid monitoring of fermentation quality has been the key to realizing the intelligent processing of black tea. In our study, mixing ratios, sensing array components and reaction times were optimized before an optimal solution phase colorimetric sensor array was constructed. The characteristic spectral information of the array was obtained by UV-visible spectroscopy and subsequently combined with machine learning algorithms to construct a black tea fermentation quality evaluation model. The competitive adaptive reweighting algorithms (CARS)-support vector machine model discriminated the black tea fermentation degree with 100% accuracy. For quantification of catechins and four theaflavins (TF, TFDG, TF-3-G, and TF-3'-G), the correlation coefficients of the CARS least square support vector machine model prediction set were 0.91, 0.86, 0.76, 0.72 and 0.79, respectively. The results obtained within 2 min enabled accurate monitoring of the fermentation quality of black tea, which provides a new method and idea for intelligent black tea processing.

Application of Nanomaterials for Coping with Mycotoxin Contamination in Food Safety: From Detection to Control

Mycotoxins, which are toxic secondary metabolites produced by fungi, are harmful to humans. Mycotoxin-induced contamination has drawn attention worldwide. Consequently, the development of reliable and sensitive detection methods and high-efficiency control strategies for mycotoxins is important to safeguard food industry safety and public health. With the rapid development of nanotechnology, many novel nanomaterials that provide tremendous opportunities for greatly improving the detection and control performance of mycotoxins because of their unique properties have emerged. This review comprehensively summarizes recent trends in the application of nanomaterials for detecting mycotoxins (fluorescence, colorimetric, surface-enhanced Raman scattering, electrochemical, and point-of-care testing) and controlling mycotoxins (inhibition of fungal growth, mycotoxin absorption, and degradation). These detection methods possess the advantages of high sensitivity and selectivity, operational simplicity, and rapidity. With research attention on the control of mycotoxins and the gradual excavation of the properties of nanomaterials, nanomaterials are also employed for the inhibition of fungal growth, mycotoxin absorption, and mycotoxin degradation, and impressive controlling effects are obtained. This review is expected to provide the readers insight into this state-of-the-art area and a reference to design nanomaterials-based schemes for the detection and control of mycotoxins.

Pumpkin extract and fermented whey individually and in combination alleviated AFB1- and OTA-induced alterations on neuronal differentiation invitro

Food and feed are daily exposed to mycotoxin contamination which effects may be counteracted by functional compounds like carotenoids and fermented whey. Among mycotoxins, the most toxic and studied are aflatoxin B1 (AFB1) and ochratoxin A (OTA), which neurotoxicity is not well reported. Therefore, SH-SY5Y human neuroblastoma cells ongoing differentiation were exposed during 7 days to digested bread extracts contained pumpkin and fermented whey, individually and in combination, along with AFB1 and OTA and their combination, in order to evaluate their presumed effects on neuronal differentiation. The immunofluorescence analysis of βIII-tubulin and dopamine markers pointed to OTA as the most damaging treatment for cell differentiation. Cell cycle analysis reported the highest significant differences for OTA-contained bread compared to the control in phase G₀/G₁. Lastly, RNA extraction was performed and gene expression was analyzed by qPCR. The selected genes were related to neuronal differentiation and cell cycle. The addition of functional ingredients in breads not only enhancing the expression of neuronal markers, but also induced an overall improvement of gene expression compromised by mycotoxins activity. These data confirm that in vitro neuronal differentiation may be impaired by AFB1 and OTA-exposure, which could be modulated by bioactive compounds naturally found in diet.

SERS-based Au@Ag NPs Solid-phase substrate combined with chemometrics for rapid discrimination of multiple foodborne pathogens

In this study, a surface enhanced Raman scattering (SERS) sensor based on Au@Ag NPs solid-phase substrate combined with chemometrics was constructed for the discrimination of three pathogenic bacteria (Staphylococcus aureus, Escherichia coli and Listeria monocytogenes). The Au@Ag NPs were synthesized and self-assembled on filter paper using the dip-coating method. The good absorbency of the filter paper immobilized the bacteria on the substrate, increased the interaction between the bacteria and the substrate, and enhanced the SERS signal of the bacteria. The main peaks of the bacterial spectra were close to each other, but the relative intensities of the vibrational peaks were significantly different, and each strain exhibited unique Raman peaks. The combination of partial least squared discriminant analysis (PLS-DA) method with bacterial SERS allowed the effective identification of the three bacteria. Moreover, the method was applied for the quantitative detection of Staphylococcus aureus with a minimum detection concentration of 10⁴ cfu/mL.

Label-free ratiometric homogeneous electrochemical aptasensor based on hybridization chain reaction for facile and rapid detection of aflatoxin B1 in cereal crops

Aflatoxin B1 (AFB1) contamination has raised global concerns in agricultural and food industry; thus, sensitive, accurate and rapid AFB1 sensors are essential in many circumstances. Herein, we developed a label-free and immobilization-free ratiometric homogeneous electrochemical aptasensor based on hybridization chain reaction (HCR) for facile and rapid determination of AFB1. Methylene blue (MB) and ferrocene (Fc) were used as label-free probes to produce a response signal (I_MB) and a reference signal (I_Fc) in solution phase, respectively. The ratio of I_MB/I_Fc was used as a yardstick to quantify AFB1. HCR was exploited to enlarge the intensity of I_MB as well as ratiometric signal. By combining label-free homogeneous assay and ratiometric strategy, the resulting aptasensor offered sensitive, rapid, and reliable determinations of AFB1 with a detection limit of 38.8 pg mL^-1. The aptasensor was then used to determine AFB1 in cereal samples with comparable reliability as HPLC-MS.

Sensitive surface-enhanced Raman spectroscopy (SERS) determination of nitrofurazone by β-cyclodextrin-protected AuNPs/γ-Al2O3 nanoparticles

A novel surface-enhanced Raman spectroscopy (SERS) method for the determination of nitrofurazone was developed using AuNPs/γ-Al₂O₃ nanoparticles protected by β-cyclodextrin (β-CD) as substrate prepared in our lab. The optimum experimental conditions were obtained from single factor procedure and response surface modeling. A linear relationship (I_SERS = 508.96c + 31987.87, c: nmol L^-1, R² = 0.996) between SERS intensity and the concentration of nitrofurazone in the range of 3.3 - 667.0 nmol L^-1 was established, the limit of detection (LOD) was found at nmol L^-1 level (0.37 nmol L^-1 by 3S₀/S). The selectivity for the method was studied by the influences of foreign substances on the determination. The recoveries and RSD (n = 5) for the six meat samples were 95.1 % - 104.5% and 2.4 % - 4.8% respectively, which suggesting that the new SERS method was successfully to detecting nitrofurazone.

In vitro and in vivo evaluation of AFB1 and OTA-toxicity through immunofluorescence and flow cytometry techniques: A systematic review

Due to the globalization, mycotoxins have been considered a major risk to human health being the main contaminants of foodstuffs. Among them, AFB1 and OTA are the most toxic and studied. Therefore, the goal of this review is to deepen the knowledge about the toxicological effects that AFB1 and OTA can induce on human health by using flow cytometry and immunofluorescence techniques in vitro and in vivo models. The examination of the selected reports shows that the majority of them are focused on immunotoxicity while the rest are concerned about nephrotoxicity, hepatotoxicity, gastrointestinal toxicity, neurotoxicity, embryotoxicity, reproductive system, breast, esophageal and lung toxicity. In relation to immunofluorescence analysis, biological processes related to AFB1- and OTA-toxicity were evaluated such as inflammation, neuronal differentiation, DNA damage, oxidative stress and cell death. In flow cytometry analysis, a wide range of assays have been performed across the reviewed studies being apoptosis assay, cell cycle analysis and intracellular ROS measurement the most employed. Although, the toxic effects of AFB1 and OTA have been reported, further research is needed to clarify AFB1 and OTA-mechanism of action on human health.

Rapid detection of chlorpyrifos residue in rice using surface-enhanced Raman scattering coupled with chemometric algorithm

Due to the continuous development and progress of society and more and more attention to the quality and safety of food, rapid testing of pesticides in food is of great significance. In this paper, surface-enhanced Raman spectroscopy (SERS) and chemometric algorithms were employed collectively to quantify chlorpyrifos (CP) residues in rice samples. The SERS spectra from different concentrations (0.01-1000 μg/mL) of CP were collected using AgNPs-deposited-ZnO nanoflower (NFs)-like nanoparticles (Ag@ZnO NFs) SERS sensor. Four quantitative chemometric models for CP were comparatively studied, and the competitive adaptive reweighted sampling-partial least squares model achieved the best prediction and practical applicability for predicting CP levels with a limit of detection of 0.01 µg/mL. The results of the student's t-test showed no significant difference between this method and high-performance liquid chromatography (HPLC), and good relative standard deviation (RSD) indicated that this method could be used for the detection of CP in rice.

Development of a label free electrochemical sensor based on a sensitive monoclonal antibody for the detection of tiamulin

Based on a murine monoclonal antibody (mAb) against tiamulin (TML), an electrochemical immunosensor was proposed using silver-graphene oxide (Ag-GO) nanocomposites and gold nanocomposites (AuNPs) to detect tiamulin (TML). Due to the synergetic properties of Ag-GO nanocomposites and AuNPs, the conductivity of the immunosensor was significantly enhanced. On account of the specific mAb and conductive nanocomposites, the proposed electrochemical immunosensor exhibited a low LOD of 0.003 ng mL^-1 for the detection of TML in a wide linear range of 0.01 to 1000 ng mL^-1. In addition, the immunosensor did not involve additional redox species. Furthermore, the efficient and simple electrochemical immunosensor was employed to detect TML in real samples with high accuracy, suggesting a potential detection platform for other veterinary antibiotics in animal derived foods.

SERS Sensors Based on Aptamer-Gated Mesoporous Silica Nanoparticles for Quantitative Detection of Staphylococcus aureus with Signal Molecular Release

This work describes a simple and novel biosensor for the quantitative determination of Staphylococcus aureus (S. aureus) based on target-induced release of signal molecules from aptamer-gated aminated mesoporous silica nanoparticles (MSNs) coupled with surface-enhanced Raman scattering (SERS) technology. MSNs were synthesized and then modified with amino groups by (3-aminopropyl) triethoxysilane to make them positively charged. Next, signal molecules (4-aminothiophenol, 4-ATP) were loaded into the pores of MSNs. Then, negatively charged aptamers of S. aureus were assembled on the surface of MSNs through electrostatic interactions. Upon the addition of S. aureus, the assembled aptamers were specifically bound to the bacteria. Consequently, the "gates" were opened, resulting in the release of 4-ATP from the pores of MSNs. The released molecules were measured by a Raman spectrometer, and the intensity of 4-ATP at 1071 cm^-1 was linearly related to the S. aureus concentration. A silver nanoflower silica core-shell structure (Ag NFs@SiO₂) was prepared and it served as a SERS substrate. Under optimized experimental conditions, a good linear relationship (y = 2107.93 + 1536.30x, R² = 0.9956) in the range from 4.7 × 10 to 4.7 × 10⁸ cfu/mL was observed with a limit of detection of 17 cfu/mL. The method was successfully applied for the analysis of S. aureus in fish samples and the recovery rate was 91.3-109%.