Bimetallic core shelled nanoparticles (Au@AgNPs) for rapid detection of thiram and dicyandiamide contaminants in liquid milk using SERS

Rapid and ultrasensitive detection of thiram and carbaryl pesticide residues in fruit juices using SERS coupled with the chemometrics technique

A gold nanogap substrate was used to measure the thiram and carbaryl residues in various fruit juices using surface-enhanced Raman scattering (SERS). The gold nanogap substrates can detect carbaryl and thiram with limits of detection of 0.13 ppb (0.13 μgkg-1) and 0.22 ppb (0.22 μgkg-1). Raw SERS data were first preprocessed to reduce noise and undesirable effects and, were later used for model creation, implementing classification, and regression analysis techniques. The partial least-squares regression models achieved the highest prediction correlation coefficient (R2) of 0.99 and the lowest root mean square of prediction value below 0.62 ppb for both pesticide-infected juice samples. Furthermore, to differentiate between juice samples contaminated by both pesticides and control (pesticide-free), logistic-regression classification models were produced and achieved the highest classification accuracies of 100% and 99% for contaminated juice containing thiram and 100% accurate results for contaminated juice containing carbaryl. This indicates that the gold nanogap surface has significant potential for achieving high sensitivity in detecting trace contaminants in food samples.

Developing a magnetic SERS nanosensor utilizing aminated Fe-Based MOF for ultrasensitive trace detection of organophosphorus pesticides in apple juice

The unreasonable use of organophosphorus pesticides leads to excessive pesticide residues in food, seriously threatening public health, and the potential of surface-enhanced Raman spectroscopy (SERS) technology, incorporating a metal-organic framework, is substantial for the rapid detection of trace pesticide residues. Here, a novel Fe3O4@NH2-MIL-101(Fe)@Ag (FNMA) SERS nanosensor was developed. Results indicated that the FNMA had a high enhancement factor of 1.53 × 108, a low limit of detection (LOD) of 4.55 × 10-12 M, and a relative standard deviation of 7.73 % for 4-nitrothiophenol, demonstrating its good SERS sensitivity and uniformity, and also possessed good storage stability for one month. In quantifying fenthion and methyl parathion in standard solutions and apple juice in the range of 0.05/0.02-20 mg/L, it showed LODs of 3.02 × 10-3 mg/L and 1.43 × 10-3 mg/L, and 0.0407 and 0.0075 mg/L, respectively, demonstrating potentials in ultrasensitive trace detection of pesticides in food.

MOF-derived multi-"hotspot" 3D Au/MOF-808 (Zr) nanostructures as SERS substrates for the ultrasensitive determination of thiram

A convenient self-assembly method is proposed for synthesis of 3D Au/MOF-808 (Zr) composite nanostructures with a cerium metal-organic framework loaded with gold nanoparticles. We combine adsorption properties of MOF materials with surface plasmon resonance of noble metals to construct hotspot-dense 3D Au/MOF-808 (Zr) SERS substrates, by using a two-step method of solvothermal and reduction reactions. The results show that optimal SERS substrates are obtained from a volume ratio of gold nanoparticles to MOF-808 (Zr) solution of 4:1 and a self-assembly time of 2 h. Rhodamine 6G (R6G) is used as a molecular probe to characterize and analyze SERS properties of substrates of 3D Au/MOF-808 (Zr) prepared under the optimal process conditions, where the substrates are capable to detect R6G concentrations down to 10-10 M with a relative standard deviation of 8.81%. Finally, we applied the SERS substrates of 3D Au/MOF-808 (Zr) to the detection of pesticide thiram, and establish a quantitative determination method. 3D Au/MOF-808 (Zr) provides a sensitive detection of thiram in lake water by SERS with a detection limit of 1.49 × 10-9 M. Application tests show that a SERS enhancement factor of the MOF-based SERS substrates for the detection of thiram can be significantly increased to 5.91 × 105. Thus, the above results indicate that such substrate has high sensitivity, good adsorption, homogeneity, and reproducibility, which can be extended for sensitive detection of pesticide residues in food and environment.

Self-assembled C-Ag hybrid nanoparticle on nanoporous GaN enabled ultra-high enhancement factor SERS sensor for sensitive thiram detection

Considering pesticide residues cause significant harm to public health and the environment, developing a simple, sensitive, and reliable approach to pesticide residue detection to address this issue is necessary. In this study, an ultrasensitive and reliable surface-enhanced Raman scattering (SERS) sensor was developed using cetylpyridinium chloride as a protecting and reducing agent for the in situ synthesis and self-assembly of C-Ag nanoparticles on nanoporous GaN for the quantitative detection of thiram. A systematic investigation of the performance of the SERS sensor revealed that the SERS sensor delivered a limit of detection (LOD) of 10-14 M and an enhancement factor of up to 1.80 × 1011 with reasonable uniformity and reproducibility, with the stability of the SERS sensor demonstrated via long-term storage for up to 22 weeks in air. The enhancement mechanism of the SERS sensor was verified using a finite-difference time-domain simulation. The SERS sensor successfully detected thiram in real samples with an LOD of 10-10 M. Hence, this study provides an effective platform for monitoring food safety and the environment.

Predicting wheat gluten concentrations in potato starch using GPR and SVM models built by terahertz time-domain spectroscopy

The purpose of this study was for the first time to explore the feasibility of terahertz (THz) spectral imaging for the detection of gluten contents in food samples. Based on the obtained 80 THz spectrum data, Gaussian process regression (GPR) and support vector machine (SVM) models were established to predict wheat gluten concentrations in 40 potato starch mixture samples. The prediction performances of GPR and SVM obtained were R2 = 0.859 and RMSE = 0.070, and R2 = 0.715 and RMSE = 0.101 in the gluten concentration range of 1.3%-100%, respectively, showing that the linear SVM algorithm had better prediction performance. The results indicated that THz spectral imaging combined with GPR could be used to predict the gluten content in food samples. It is thus hoped that this research should provide a novel technique for gluten content detection to ensure gluten-free food samples.

A SERS-based immune-nanoprobe for ultrasensitive detection of glycinin via a lateral flow assay

Glycinin is one of the most nutritious ingredients in soybean, but it is also an allergen that can cause allergic reactions in humans and animals, and even endanger life in severe cases. Therefore, it is imperative to develop a rapid and ultrasensitive detection method for glycinin. In order to achieve this goal, this experiment combined surface-enhanced Raman spectroscopy (SERS) technology with an economical, simple, fast and easy-to-carry immunochromatographic test strip, and successfully constructed an efficient sandwich immunochromatographic test strip. The immunoprobe of the test strip was covalently coupled by gold nanostars (AuNSs), Raman molecule 4-aminothiophenol (4-PATP) and rabbit polyclonal antibody. In this experiment, a gold nanostar immunochromatographic test strip for detecting glycinin was established. The detection limit of the test strip was 0.23 ng / mL, the recovery rate was 91.5-96.6 %, and the coefficient of variation was 1.61-6.15 %. In addition, the test strip had no cross reaction with whey protein, wheat protein, peanut protein, sesame protein and β-conglycinin, indicating that the detection method had good specificity and the ability to avoid false positive results. Hence, this experiment successfully prepared a rapid and sensitive test strip for glycinin.

Developments in food neonicotinoids detection: novel recognition strategies, advanced chemical sensing techniques, and recent applications

Neonicotinoid insecticides (NEOs) are a new class of neurotoxic pesticides primarily used for pest control on fruits and vegetables, cereals, and other crops after organophosphorus pesticides (OPPs), carbamate pesticides (CBPs), and pyrethroid pesticides. However, chronic abuse and illegal use have led to the contamination of food and water sources as well as damage to ecological and environmental systems. Long-term exposure to NEOs may pose potential risks to animals (especially bees) and even human health. Consequently, it is necessary to develop effective, robust, and rapid methods for NEOs detection. Specific recognition-based chemical sensing has been regarded as one of the most promising detection tools for NEOs due to their excellent selectivity, sensitivity, and robust interference resistance. In this review, we introduce the novel recognition strategies-enabled chemical sensing in food neonicotinoids detection in the past years (2017-2023). The properties and advantages of molecular imprinting recognition (MIR), host-guest recognition (HGR), electron-catalyzed recognition (ECR), immune recognition (IR), aptamer recognition (AR), and enzyme inhibition recognition (EIR) in the development of NEOs sensing platforms are discussed in detail. Recent applications of chemical sensing platforms in various food products, including fruits and vegetables, cereals, teas, honey, aquatic products, and others are highlighted. In addition, the future trends of applying chemical sensing with specific recognition strategies for NEOs analysis are discussed.

Cu2+-assisted sensing of fungicide Thiram in food, soil, and plant samples and the ratiometric detection of Hg2+ in living cells by a low cytotoxic and red emissive fluorescent sensor

Metal ions and pesticides are extensively used in many industries and agriculture. However, they cause significant environmental pollution and various adverse health effects. Therefore, the development of sensitive and selective techniques to detect them is necessary for human health and the ecosystem. In this paper, we report a novel red-emitting fluorescence probe with a large Stokes shift (∼220 nm) based on rhodamine and isophorone units. The probe shows a ratiometric fluorescence response toward Hg²⁺ ions; however, Cu²⁺ ions quench the red fluorescence signal. The decomposition of the probe-Cu²⁺ complex allows detection of Thiram followed by recovery of the red fluorescence signal of the probe. In addition, the probe shows a good linear response to Hg²⁺, Cu²⁺, and Thiram, with detection limits of 122.0 nM, 29.0 nM, and 72.0 nM, respectively. The practical applicability of the probe has been successfully tested in real samples. Moreover, smartphone detection and light-responsive capsule fabrication have been established, for easy and quick detection. The probe possesses very low cytotoxicity and allows visualization of Hg²⁺ and Cu²⁺ ions in HeLa cells. Therefore, the present probe is expected to be an effective tool assisting in easy, quick, and reliable detection of Thiram, Hg²⁺, and Cu²⁺ ions.

Flexible 3D Substrate of Ag Nanoparticle-Loaded Carbon Aerogels with Outstanding Surface-Enhanced Raman Scattering Performance

Surface-enhanced Raman scattering (SERS), an ultra-sensitive and non-destructive analytic technique, has attracted wide attention from the scientific community. Despite its rapid development, limited hotspots on the SERS substrates have restricted their potential in practical applications. Herein, we developed a facile method to fabricate a flexible three-dimensional (3D) SERS substrate composed of silver nanoparticles (Ag NPs)-loaded carbon aerogels (CAs). Such a flexible Ag NPs/CAs substrate exhibited numerous hotspots, which can facilely be adjusted not only by tuning the density of Ag NPs but also by controlling the bending degree of the flexible substrate. In addition, the influence of hotspots on the local electric field enhancement was investigated by theoretical calculations. Moreover, the 3D network structure of the CAs with a large specific surface area and strong adsorption ability can improve the capture of target molecules. Consequently, the optimal Ag NPs/CAs substrate has a low detection limit of 10^-12 M for rhodamine 6G molecules as well as good repeatability. Furthermore, based on the good performance of SERS detection of the Ag NPs/CAs substrate, it can also be practically used for the detection of thiram molecules on the surface of cherry tomatoes. Such a flexible 3D Ag NPs/CAs substrate has great potential for practical environmental monitoring applications.

Bimetallic metal-organic frameworks-based ratiometric fluorescence sensor for the quantitative detection of thiram in fruits samples

The identification of residual thiram (Tr) in foods is vital in view of its harmful effects on human health. Herein, a ratiometric fluorescence sensor (I₄₃₅/I₅₉₀) based on rhodamine B/NH₂-MIL-53(Al_0.75Fe_0.25) was constructed for the detection of Tr. Interestingly, the probe RhB/NH₂-MIL-53(Bim) assisted by Cu²⁺ could rapidly and sensitively recognize Tr with a low detection limit of 0.11 μg/mL in 10 min. The fluorescence sensing mechanism was investigated using fluorescence spectra, UV-Vis absorption spectra, the fluorescence lifetime and quantum yield. The results showed that the excellent sensing performance was attributed to fluorescence resonance energy transfer, electrostatic interaction, and photoinduced electron transfer. In addition, the practical application of this platform showed acceptable relative recoveries for Tr (84.03-107.81 %), and precisions were also achieved (relative standard deviation ≤ 8.69 %, n = 3). These results show that the presented herein can be applied to monitor the Tr content in real fruit samples.

Rapid qualitative detection of titanium dioxide adulteration in persimmon icing using portable Raman spectrometer and Machine learning

Persimmon icing is the white crystalline powder that adheres to the surface of persimmon cakes when the sugar in the persimmon spills over during processing, which is considered the essence of persimmon. Titanium dioxide is a food additive that is commonly added to the surface of persimmon cakes to impersonate high-quality persimmon cakes. However, excessive titanium dioxide can be harmful to humans, so a quick method is needed to identify persimmon cakes as adulterated. Raman spectroscopy with distinctive advantages of water-insensitivity, real-time, field-deployable, label-free, and fingerprinting-identification has been rapidly developed and used in food quality assurance and safety monitoring. In this study, we investigated Raman spectroscopy integrated with machine learning to assess titanium dioxide adulteration in dried persimmon icing. The adaptive iterative reweighting partial least squares (air-PLS) algorithm as an effective algorithm was used to remove fluorescent background signals in raw Raman spectroscopy. Principal components analysis (PCA) was employed to analyze the spectral data and determine the class memberships, and results showed that 99.9% of information could be explained by PC-1 and PC-2. Compared with extreme learning machine (ELM), support vector machine (SVM), back propagation artificial neural network (BP-ANN), and random forest (RF) models, one-dimensional stack auto encoder convolutional neural network (1D-SAE-CNN) could provide the highest detection accuracy of 0.9825, precision of 0.9824, recall of 0.9825, and f1-score of 0.9824. This study shows that Raman spectroscopy coupled with 1D-SAE-CNN is a promising method to detect titanium dioxide adulteration in persimmon icing.

Thiram-induced hyperglycemia causes tibial dyschondroplasia by triggering aberrant ECM remodeling via the gut-pancreas axis in broiler chickens

Pesticide thiram is widely used in agriculture and has been demonstrated to cause tibial dyschondroplasia (TD) in birds. However, the underlying mechanism remains unclear. This work used multi-omics analysis to evaluate the molecular pathways of TD in broilers that were exposed to low level of thiram. Integrative analysis of transcriptomic, proteomic, and metabolomic revealed thiram activity in enhancing pathological ECM remodeling via attenuating the glycolysis pathway and activating the hexosamine and glucuronic acid pathways. Intriguingly, we found hyperglycemia as a crucial factor for ECM overproduction, which resulted in the development of TD. We further demonstrated that high glucose levels are caused by islet secretion dysfunction in thiram-treated broilers. A combination of factors, including lipid disorder, low-grade inflammation, and gut flora disturbance, might contribute to the dysregulation of insulin secretion. The current work revealed the underlying toxicological mechanisms of thiram-induced tibial dyschondroplasia through blood glucose disorder via the gut-pancreas axis in chickens for the first time, which makes it easier to figure out the health risks of pesticides for worldwide policy decisions.

Combining thin-film microextraction and surface enhanced Raman spectroscopy to sensitively detect thiram based on 3D silver nanonetworks

By coupling thin-film microextraction (TFME) with surface enhanced Raman scattering (SERS), a facile method was developed for the determination of thiram in the complex matrix (orange juice or grape peel). The substrate of TFME was made by self-assembling silver sol on the silicon wafer to form a three-dimensional (3D) silver nanonetwork structure, without adding any template, which was used for TFME and SERS detection, respectively. The substrate exhibits high reproducibility with a relative standard deviation of about 7.32 % in spot and spot SERS intensity. The SERS signal intensity at a shift of 1384 cm^-1 and the thiram concentration showed good linearity in the range of 0.01-5 µg/L and the linear correlation coefficient was 0.9912. The detection limit for thiram was found to be 0.01 µg/L. The TFME-SERS method was applied for the determination of thiram in fruit juice and the results were obtained very well. Therefore, this method is expected to play a role in the detection of trace pollutants.

Enhancement of Magnetic Surface-Enhanced Raman Scattering Detection by Tailoring Fe3O4@Au Nanorod Shell Thickness and Its Application in the On-site Detection of Antibiotics in Water

Surface-enhanced Raman scattering (SERS) has become a promising method for the detection of contaminants or biomolecules in aqueous media. The low interference of water, the unique spectral fingerprint, and the development of portable and handheld equipment for in situ measurements underpin its predominance among other spectroscopic techniques. Among the SERS nanoparticle substrates, those composed of plasmonic and magnetic components are prominent examples of versatility and efficiency. These substrates harness the ability to capture the target analyte, concentrate it, and generate unique hotspots for superior enhancement. Here, we have evaluated the use of gold-coated magnetite nanorods as a novel multifunctional magnetic-plasmonic SERS substrate. The nanostructures were synthesized starting from core-satellite structures. A series of variants with different degrees of Au coatings were then prepared by seed-mediated growth of gold, from core-satellite structures to core-shell with partial and complete shells. All of them were tested, using a portable Raman instrument, with the model molecule 4-mercaptobenzoic acid in colloidal suspension and after magnetic separation. Experimental results were compared with the boundary element method to establish the mechanism of Raman enhancement. The results show a quick magnetic separation of the nanoparticles and excellent Raman enhancement for all the nanoparticles both in dispersion and magnetically concentrated with limits of detection up to the nM range (∼50 nM) and a quantitative calibration curve. The nanostructures were then tested for the sensing of the antibiotic ciprofloxacin, highly relevant in preventing antibiotic contaminants in water reservoirs and drug monitoring, showing that ciprofloxacin can be detected using a portable Raman instrument at a concentration as low as 100 nM in a few minutes, which makes it highly relevant in practical point-of-care devices and in situ use.

Au nanoparticles decorated covalent organic framework composite for SERS analyses of malachite green and thiram residues in foods

A three-dimensional (3D) surface-enhanced Raman scattering (SERS) substrate composed of gold nanoparticles (AuNPs) self-assembled covalent organic frameworks (COFs) was fabricated via the electrostatic interaction between positively charged COFs and negatively charged AuNPs, which exhibited excellent SERS performance and were successfully applied for the analyses of malachite green (MG) residue in different seafood products as well as thiram residue in several kinds of fruit juice. The raspberry-like structure SERS substrate has a larger surface area that can provide more adsorption sites in testing and improve the efficiency of sample enrichment. By using this developed SERS substrate, the detection linearity ranges are 1.0 × 10^-9 mol·L^-1-1.0 × 10^-6 mol·L^-1 for MG and 5.0 × 10^-8 mol·L^-1-1.0 × 10^-5 mol·L^-1 for thiram (R² ≥ 0.995). The detection limits are 6.2 × 10^-10 mol·L^-1 for MG and 1.7 × 10^-8 mol·L^-1 for thiram, respectively. The COF-AuNPs substrate was actually applied for analysis of MG in seafood products and thiram in different fruit juice, with the recoveries in the ranges of 94.67-108.99 % for MG and 95.00-107.58 % for thiram, and both of the relative standard deviation (RSD) are no more than 5.88 %. This work indicates that the developed COF-AuNPs substrate is promising for SERS analyses and detections of residues in foods.

Surface-enhanced Raman spectroscopy combined with stable isotope probing to assess the metabolic activity of Escherichia coli cells in chicken carcass wash water

Rapid evaluation of the metabolic activity of microorganisms is crucial in the assessment of the disinfection ability of various antimicrobial agents in the food industry. In this study, surface-enhanced Raman spectroscopy combined with isotope probing was employed for the analysis of the disinfection of single bacterial cells in the chicken carcass wash water. The Raman signals from single Escherichia coli O157:H7 cells were enhanced by in situ synthesis of silver nanoparticles. The ΔCD of the cells grown in presence of 0.5% hydrogen peroxide and 50 ppm chlorine was 5.86 ± 1.86% and 5.1 ± 2.3%, respectively, which showed significant reduction compared with cells grown in the absence of disinfecting agents (19.86 ± 2.51%) after 2 h of incubation. The study proved that the proposed method had the potential to assess the metabolic activity of microorganisms in other food products and optimize the disinfection process.

Trends in Application of SERS Substrates beyond Ag and Au, and Their Role in Bioanalysis

This article compares the applications of traditional gold and silver-based SERS substrates and less conventional (Pd/Pt, Cu, Al, Si-based) SERS substrates, focusing on sensing, biosensing, and clinical analysis. In recent decades plethora of new biosensing and clinical SERS applications have fueled the search for more cost-effective, scalable, and stable substrates since traditional gold and silver-based substrates are quite expensive, prone to corrosion, contamination and non-specific binding, particularly by S-containing compounds. Following that, we briefly described our experimental experience with Si and Al-based SERS substrates and systematically analyzed the literature on SERS on substrate materials such as Pd/Pt, Cu, Al, and Si. We tabulated and discussed figures of merit such as enhancement factor (EF) and limit of detection (LOD) from analytical applications of these substrates. The results of the comparison showed that Pd/Pt substrates are not practical due to their high cost; Cu-based substrates are less stable and produce lower signal enhancement. Si and Al-based substrates showed promising results, particularly in combination with gold and silver nanostructures since they could produce comparable EFs and LODs as conventional substrates. In addition, their stability and relatively low cost make them viable alternatives for gold and silver-based substrates. Finally, this review highlighted and compared the clinical performance of non-traditional SERS substrates and traditional gold and silver SERS substrates. We discovered that if we take the average sensitivity, specificity, and accuracy of clinical SERS assays reported in the literature, those parameters, particularly accuracy (93-94%), are similar for SERS bioassays on AgNP@Al, Si-based, Au-based, and Ag-based substrates. We hope that this review will encourage research into SERS biosensing on aluminum, silicon, and some other substrates. These Al and Si based substrates may respond efficiently to the major challenges to the SERS practical application. For instance, they may be not only less expensive, e.g., Al foil, but also in some cases more selective and sometimes more reproducible, when compared to gold-only or silver-only based SERS substrates. Overall, it may result in a greater diversity of applicable SERS substrates, allowing for better optimization and selection of the SERS substrate for a specific sensing/biosensing or clinical application.

Determination of 5-Hydroxymethylfurfural (5-HMF) in milk products by surface-enhanced Raman spectroscopy and its simulation analysis

5-Hydroxymethylfurfural (5-HMF) is a useful indicator of thermal damage degree and freshness of milk. It is of great importance to develop simple, rapid and accurate analytical methods for the sensitive detection of 5-HMF in milk and milk-based products. In this work, surface-enhance Raman spectroscopy (SERS) was used for rapid determination of 5-HMF in processed cheese by colloidal Au nanoparticles (AuNPs) substrate synthesized by the classical solvothermal reduction method. Density functional theory (DFT) calculations were carried out to determine the vibration assignments of 5-HMF and the surface enhancement effect of AuNPs substrate. The results found that a good linear response on the AuNPs substrate for 5-HMF in the concentration range of 0.1-75 mM was established with the detection limit of 75 μM (S/N = 3). Furthermore, the present method could be applied to the determination of 5-HMF in a cheese real sample which revealed its promising application in food safety and analysis.

Core-shell Au-Ag nanoparticles as colorimetric sensing probes for highly selective detection of a dopamine neurotransmitter under different pH conditions

Dopamine (DA) is a vital biomarker for the early diagnosis of dopaminergic dysfunction; therefore, it is important to establish a direct and selective detection tool for DA neurotransmitters. This work reports facilely synthesized Au-Ag core-shell nanoparticles (Au@Ag NPs) as colorimetric sensing probes for highly selective detection of the DA neurotransmitter. Our sensing strategy is based on DA-mediated aggregation of the Au@Ag NPs, which can show a distinct color transition from yellow to greenish grey. With the increase of pH from 6 to 10, the response time of colorimetric transition was significantly reduced by a factor of 10 and the limit of detection (LOD) for DA by a spectroscopic device was estimated to be 0.08 μM. Notably, optimized sensing probes of Au@Ag NPs at pH 10 demonstrated an excellent selectivity to DA against various interfering components (including catecholamines (norepinephrine and epinephrine), lysine, glutamic acid, glucose, or metal ions). Our sensing system also exhibited the reliable detection of DA in spiked human serum with the relative standard deviation lower than 4.0%, suggesting its possible application to the direct detection of DA in biological fluids.

Recent Progress on Techniques in the Detection of Aflatoxin B1 in Edible Oil: A Mini Review

Contamination of agricultural products and foods by aflatoxin B1 (AFB1) is becoming a serious global problem, and the presence of AFB1 in edible oil is frequent and has become inevitable, especially in underdeveloped countries and regions. As AFB1 results from a possible degradation of aflatoxins and the interaction of the resulting toxic compound with food components, it could cause chronic disease or severe cancers, increasing morbidity and mortality. Therefore, rapid and reliable detection methods are essential for checking AFB1 occurrence in foodstuffs to ensure food safety. Recently, new biosensor technologies have become a research hotspot due to their characteristics of speed and accuracy. This review describes various technologies such as chromatographic and spectroscopic techniques, ELISA techniques, and biosensing techniques, along with their advantages and weaknesses, for AFB1 control in edible oil and provides new insight into AFB1 detection for future work. Although compared with other technologies, biosensor technology involves the cross integration of multiple technologies, such as spectral technology and new nano materials, and has great potential, some challenges regarding their stability, cost, etc., need further studies.

Multiplex Sensing Based on Plasmonic Optics of Noble Metallic Nanostructures

Since the colorimetric method has the characteristics of being simple and low cost, the fluorescence spectrum has the characteristics of a strong signal, and Surface-enhanced Raman scattering (SERS) detection has the characteristics of high sensitivity and strong specificity, people usually use these three methods for detection, but the detection of a single sample takes more time. If multiple samples can be tested at the same time, the detection efficiency and sensitivity can be improved, and the selectivity and reliability will be greatly improved. Multiplex sensing also provides a new direction for researchers. To fully understand the research of multiplex sensing based on the plasmonic optics of noble metal nanostructures, this review summarizes all the results previously reported in this field. It also discusses the principles of various detection methods and the biochemical application of multiple detections and finally summarizes the challenges and prospects.

Analyzing macromolecular composition of E. Coli O157:H7 using Raman-stable isotope probing

Metabolic dynamics of bacterial cells is needed for understanding the correlation between changes in environmental conditions and cell metabolic activity. In this study, Raman spectroscopy combined with deuterium labelling was used to analyze the metabolic activity of a single Escherichia coli O157:H7 cell. The incorporation of deuterium from heavy water into cellular biomolecules resulted in the formation of carbon-deuterium (CD) peaks in the Raman spectra, indicating the cell metabolic activity. The broad vibrational peaks corresponding to CD and CH peaks encompassed different specific shifts of macromolecules such as protein, lipids, and nucleic acid. The utilization of tryptophan and oleic acid by the cell as the sole carbon source led to changes in cell lipid composition, as indicated by new peaks in the second derivative spectra. Thus, the proposed method could semi-quantitatively determine total metabolic activity, macromolecule specific identification, and lipid and protein metabolism in a single cell.

Smartphone-Based Techniques Using Carbon Dot Nanomaterials for Food Safety Analysis

The development of portable and efficient nanoprobes to realize the quantitative/qualitative onsite determination of food pollutants is of immense importance for safeguarding human health and food safety. With the advent of the smartphone, the digital imaging property causes it to be an ideal diagnostic substrate to point-of-care analysis probes. Besides, merging the versatility of carbon dots nanostructures and bioreceptor abilities has opened an innovative assortment of construction blocks to design advanced nanoprobes or improving those existing ones. On this ground, massive endeavors have been made to combine mobile phones with smart nanomaterials to produce portable (bio)sensors in a reliable, low cost, rapid, and even facile-to-implement area with inadequate resources. Herein, this work outlines the latest advancement of carbon dots nanostructures on smartphone for onsite detecting of agri-food pollutants. Particularly, we afford a summary of numerous approaches applied for target molecule diagnosis (pesticides, mycotoxins, pathogens, antibiotics, and metal ions), for instance microscopic imaging, fluorescence, colorimetric, and electrochemical techniques. Authors tried to list those scaffolds that are well-recognized in complex media or those using novel constructions/techniques. Lastly, we also point out some challenges and appealing prospects related to the enhancement of high-efficiency smartphone based carbon dots systems.

Kernel principal component analysis and differential non-linear feature extraction of pesticide residues on fruit surface based on surface-enhanced Raman spectroscopy

Surface-enhanced Raman spectroscopy (SERS) has attracted much attention because of its high sensitivity, high speed, and simple sample processing, and has great potential for application in the field of pesticide residue detection. However, SERS is susceptible to the influence of a complex detection environment in the detection of pesticide residues on the surface of fruits, facing problems such as interference from the spectral peaks of detected impurities, unclear dimension of effective correlation data, and poor linearity of sensing signals. In this work, the enhanced raw data of the pesticide thiram residues on the fruit surface using gold nanoparticle (Au-NPs) solution are formed into the raw data set of Raman signal in the IoT environment of Raman spectroscopy principal component detection. Considering the non-linear characteristics of sensing data, this work adopts kernel principal component analysis (KPCA) including radial basis function (RBF) to extract the main features for the spectra in the ranges of 653∼683 cm^-1, 705∼728 cm^-1, and 847∼872 cm^-1, and discusses the effects of different kernel function widths (σ) to construct a qualitative analysis of pesticide residues based on SERS spectral data model, so that the SERS spectral data produce more useful dimensionality reduction with minimal loss, higher mean squared error for cross-validation in non-linear scenarios, and effectively weaken the interference features of detecting impurity spectral peaks, unclear dimensionality of effective correlation data, and poor linearity of sensing signals, reflecting better extraction effects than conventional principal component analysis (PCA) models.

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 and sensitive detection of zearalenone in corn using SERS-based lateral flow immunosensor

Zearalenone (ZEN) is a universal mycotoxin contaminant in corn and its products. A surface-enhanced Raman scattering (SERS) based test strip was proposed for the detection of ZEN, which had the advantages of simplicity, rapidity, and high sensitivity. Core-shell Au@AgNPs with embedded reporter molecules (4-MBA) were synthesized as SERS nanoprobe, which exhibited excellent SERS signals and high stability. The detection range of ZEN for corn samples was 10-1000 μg/kg with the limit of detection (LOD) of 3.6 μg/kg, which is far below the recommended tolerable level (60 μg/kg). More importantly, the SERS method was verified by HPLC in the application on corn samples contaminated with ZEN, and the coincidence rates were in the range of 86.06%-111.23%, suggesting a high accuracy of the SERS assay. Therefore, the SERS-based test strip with an analysis time of less than 15 min is a promising tool for accurate and rapid detection of ZEN-field contamination.

Mxenes–Au NP Hybrid Plasmonic 2D Microplates in Microfluidics for SERS Detection

Combined with microfluidics, surface-enhanced Raman spectroscopy (SERS) exhibits huge application prospective in sensitive online detection. In current studies, the design and optimization of plasmonic enhanced structures in microfluidics for SERS detection could be an interesting challenge. In this work, hybrid plasmonic 2D microplates composed of Mxenes (Ti3C2Tx) microplates and in-situ synthesized Au nanoparticles (Au NPs) are fabricated in a microchannel for enhanced structures in SERS microfluidics. Benefiting from the 2D Mxenes microplates with complex distributions, the enhanced areas generated by Au NPs are quite enlarged in a microchannel, which exhibits high sensitivity in SERS detection at 10−10 M for Nile blue (NB) molecules in microfluidics. The mechanism of electromagnetic enhancement (EM) and chemical enhancement (CM) is analyzed. The experimental data indicate the ultrasonic times of Mxenes and the concentration of Au3+ play important roles in the sensitivity of SERS detection, which is confirmed by the simulated electric field distributions. Furthermore, a typical pesticide (thiram) at 100 ppm in water is detected on these SERS microfluidics with hybrid plasmonic enhanced structures, which demonstrates that our work not only strengthens the knowledge of plasmonics but also enlarges the application of SERS.

Recent advances in the application of Raman spectroscopy for fish quality and safety analysis

Fish is one of the highly demanded aquatic products, and its quality and safety play a pivotal role in daily diet. However, the possible hazardous substance in perishable fish both in pre- and postharvest periods may decrease their values and pose a threat to public health. Laborious and expensive traditional methods drive the need of developing effective tools for detecting fish quality and safety properties in a rapid, nondestructive, and effective manner. Recent advances in Raman spectroscopy (RS) and surface-enhanced Raman scattering (SERS) have shown enormous potential in various aspects, which largely boost their applications in fish quality and safety evaluation. They have incomparable merits such as providing molecule fingerprint information and allowing for rapid, sensitive, and noninvasive detection with simple sample preparation. This review provides a comprehensive overview focusing on the applications of RS and SERS for fish quality assessment and safety inspection, highlighting the hazardous substance and illegal behavior both in preharvest (veterinary drug residues and environmental pollutants) and postharvest (freshness and illegal behavior) particularly. Moreover, challenges and prospects are also proposed to facilitate the vigorous development of RS and SERS. This review is aimed to emphasize potential opportunities for applying RS and SERS as promising techniques for routine food quality and safety detection. PRACTICAL APPLICATION: With these applications, it can be clearly indicated that RS and SERS are promising and powerful in fish quality and safety surveillance, thereby reducing the occurrence of commercial fraud and food safety issues. More efforts still should be concentrated on exploiting the high-performance Raman instruments, establishing a universal Raman database, developing reproducible SERS substrates and combing RS with other versatile spectral techniques to promote these technologies from laboratory to practice. It is hoped that this review should arouse more research interests in RS and SERS technologies for fish quality and safety surveillance, as well as provide more insights to make a breakthrough.

Detection of Bioactive Metabolites in Escherichia Coli Cultures Using Surface-Enhanced Raman Spectroscopy

Detection of bioactive metabolites produced by bacteria is important for identifying biomarkers for infectious diseases. In this study, a surface-enhanced Raman spectroscopy (SERS)-based technique was developed for the detection of bioactive metabolite indole produced by Escherichia coli (E. coli) in biological media. The use of highly sensitive Au@Ag core-shell nanoparticles resulted in the detection of indole concentration as low as 0.0886 mM in standard solution. The supplementation of growth media with 5 mM of exogenous tryptophan resulted in the production of a maximum yield of indole of 3.139 mM by E. coli O157:H7 at 37 °C. The growth of bacterial cells was reduced from 47.73 × 10⁸ to 1.033 × 10⁶ CFU/mL when the cells were grown in 0 and 10 mM exogenous tryptophan, respectively. The amount of indole in the Luria-Bertani (LB) media had an inverse correlation with the growth of cells, which resulted in a three-log reduction in the colony-forming unit when the indole concentration in the media was 20 times higher than normal. This work demonstrates that SERS is an effective and highly sensitive method for rapid detection of bioactive metabolites in biological matrix.

Ultrasensitive detection of pectin based on the decarboxylation reaction and surface-enhanced Raman spectroscopy

In the present study, a novel simple and sensitive method was developed for the determination of pectin based on the decarboxylation derivatization reaction and surface-enhanced Raman scattering (SERS) without complicated separation steps. The derivatization reaction can be controlled by the experimental parameters such as reaction time, temperature and the amount of hydrochloric acid. Additionally, the method was used to accurately and reliably detect pectin added in honey or apple, which can be detected at levels as low as 0.5 or 0.01 ppm, respectively. Based on the conventional decarboxylation reaction, a simple and sensitive SERS method was proposed for the detection of pectin, which shows potential for practical application.

The novel sandwich composite structure: a new detection strategy for the ultra-sensitive detection of cyclotrimethylenetrinitramine (RDX)

This study presents a novel sandwich composite structure that was designed for the ultra-sensitive detection of cyclotrimethylenetrinitramine (RDX). Au nanorod arrays (Au NRAs) were prepared and bound to 10^-7M 6-MNA as adsorption sites for RDX, while Au nanorods (Au NRs) were modified using 10^-5M 6-MNA as SERS probes. During detection, RDX molecules connect the SERS probe to the surface of the Au NRAs, forming a novel type of Au NRAs-RDX-Au NRs 'sandwich' composite structure. The electromagnetic coupling effect between Au NRs and Au NRAs is enhanced due to the molecular level of the connection spacing, resulting in new 'hot spots'. Meanwhile, Au NRAs and Au NRs have an auto-enhancement effect on 6-MNA. In addition, the presence of charge transfer in the formed 6-MNA-RDX complex induced chemical enhancement. The limits of detection of RDX evaluated by Raman spectroscopy using 6-MNA were as low as 10^-12mg ml^-1(4.5 × 10^-15M) with good linear correlation between 10^-12and 10^-8mg ml^-1(correlation coefficientR² = 0.9985). This novel sandwich composite structure accurately detected RDX contamination in drinking water and on plant surfaces in an environment with detection limits as low as 10^-12mg ml^-1and 10^-8mg ml^-1.

Gap controlled self-assembly Au@Ag@Au NPs for SERS assay of thiram

Thiram (TRM), one dithiocarbamate fungicide, is hazardous due to its ever-growing threat to our production and living. In order to detecting TRM more sensitively, a subtle surface-enhanced Raman scattering (SERS) substrate was reported to achieve TRM detection based on oil-water biphasic self-assembly interface of multi-interstitial Au@Ag@Au NPs crosslinking with 4,4' -Diamino-p-Terphenyl (DATP). This Au@Ag@Au@DATP array shows a noteworthy enhanced Raman signal and stability by controlling the inter-particle spacing of Au@Ag@Au NPs, which overcomes problems of traditional randomly self-assembly methods without cross linker. The Au@Ag@Au@DATP array attained the limit of detection (LOD) of 7.56 × 10^-3 ppb for TRM. In addition, this work gives a new approach for controlling gap of SERS hot spot, which have distinct potential in rapid assessment and identification of pesticides on foods.

A fluorescence aptasensor based on carbon quantum dots and magnetic Fe3O4 nanoparticles for highly sensitive detection of 17β-estradiol

Trace amounts of 17β-estradiol (E2) in food and the environment poses a threat to human health, which has created the demand for sensitive analytical methods to detect E2. In this study, a novel fluorescent aptasensor was developed for sensitive detection of E2 based on double-chain hybridization between carbon quantum dots-labelled with E2 aptamer (CQDs-aptamer) and Fe₃O₄ nanoparticles modified by complementary DNA (Fe₃O₄-cDNA). Under the optimal conditions, the aptasensor displayed a good linear range of 10^-11-10^-6 M for E2 with the coefficient of determination (R²) of 0.996, and a low detection limit of 3.48 × 10^-12 M was obtained. Besides, the aptasensor showed high selectivity and good reproducibility for E2 detection, which was successfully applied to the sensitive detection of E2 in milk as compared with tap water and lake water with satisfactory recoveries from 85.21% to 114.80%, suggesting the great significance of this aptasensor for detecting food contaminants in the food industry.

Interfacing metal-polyphenolic networks upon photothermal gold nanorods for triplex-evolved biocompatible bactericidal activity

Gold nanorods (GNRs) outstand in photothermal disinfection but are faced with severe surface chemistry and dose relevant biotoxicity. Herein, a naturally green building block, metal-phenolic networks (MPNs), was employed to functionalize GNRs via coordination reaction, yielding a tunable and biocompatible core-shell photothermal nano-bactericide (GNRs@MPNs). The bioactive GNRs@MPNs built with iron and polyphenols (tannic acid, epigallocatechin gallate, and procyanidins) exhibited superior light-to-heat conversion efficiencies with η = 29.29-44.00%, remarkably preceding that of GNRs (η = 12.24%), which could rapidly ablate 99.8% of Escherichia coli O157: H7 and 98.6% of Staphylococcus aureus bacteria in relatively low efficacy doses (10 ppm of Au). Moreover, local heat triggered by GNRs@MPNs accelerated the healing of the cutaneous wound of a mice model infected by methicillin-resistant S. aureus. The facile synthesis, photothermal synergy, polyphenolic bioactivity, and significantly low efficacy dose of GNRs@MPNs empower them satisfactory efficiency and biosafety in the future broad-spectrum photothermal sterilization applications.

Ti3C2Tx MXenes loaded with Au nanoparticle dimers as a surface-enhanced Raman scattering aptasensor for AFB1 detection

Mycotoxin B1 (AFB1) contamination in agricultural products pose a deadlydangertoanimal and human health and its rapid and reliable detection is thus very important. Herein, a ratiometric surface-enhanced Raman scattering (SERS) aptasensor for AFB1 detection was developed, in which 1,2-bis(4-pyridyl) ethylene (BPE) was used to trigger the assembly of Au nanoparticle dimers (AuNP dimers) and form intensive SERS "hot spots", and MXenes nanosheets could load aptamer-modified AuNP dimers due to the hydrogen bonding and the chelation between the phosphate groups of aptamers and the Ti ion of MXenes. With the presence of AFB1 preferentially binding to AFB1 aptamer, AuNP dimers were separated from MXenes nanosheets, leading to a decrease in SERS intensity. Regression analysis in the range from 0.001 to 100 ng·mL^-1 showed the limit of detection (LOD) being 0.6 pg·mL^-1 in standard solution, indicating that the great prospects of the AuNP dimers/MXenes SERS substrate for detecting AFB1.

Facile and robust fabrication of hierarchical Au nanorods/Ag nanowire SERS substrates for the sensitive detection of dyes and pesticides

Surface enhanced Raman spectroscopy (SERS) has emerged as a promising tool for the rapid and ultrasensitive recognition of trace amounts of environmental pollutants. Hierarchical SERS substrates usually show superior performance to single-component substrates but require complicated preparation protocols. Herein, a facile, robust and low-cost route for the fabrication of hierarchical SERS substrates has been reported, in which no complicated laborious protocols or sophisticated equipment is needed. In the hierarchical SERS substrate, Au nanorods were distributed onto the network of Ag nanowires through evaporation induced self-assembly. The density of the Au nanorods and Ag nanowires could be easily tailored by tuning the number of droplets of gold nanorod solution and the concentration of silver nanowire solution. The nanogaps formed between Au nanorods and Ag nanowires were able to induce a rich enhanced electromagnetic field area via localized surface plasmon resonances and surface plasmon polaritons to achieve amplification of the Raman signal. The as-prepared substrate showed high uniformity and was capable of identifying 10^-12 M rhodamine 6G, 10^-10 M thiram and 10^-10 M crystal violet, with correlation coefficients (R²) all higher than 0.98. This approach can be employed for the detection of trace dyes, pesticides or other environmental pollutants with high sensitivity and uniformity.

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.

State of the Art on Green Route Synthesis of Gold/Silver Bimetallic Nanoparticles

Recently, bimetallic nanoparticles (BMNPs) blending the properties of two metals in one nanostructured system have generated enormous interest due to their potential applications in various fields including biosensing, imaging, nanomedicine, and catalysis. BMNPs have been developed later with respect to the monometallic nanoparticles (MNPs) and their physicochemical and biological properties have not yet been comprehensively explored. The manuscript aims at collecting the main design criteria used to synthetize BMNPs focusing on green route synthesis. The influence of experimental parameters such as temperature, time, reagent concentrations, capping agents on the particle growth and colloidal stability are examined. Finally, an overview of their nanotechnological applications and biological profile are presented.

Facile tuning of tip sharpness on gold nanostars by the controlled seed-growth method and coating with a silver shell for detection of thiram using surface enhanced Raman spectroscopy (SERS)

Developing SERS substrates based on individual gold and silver metals, either with rough surfaces or bare nanoparticles, has certain limitations in practical analysis applications. In order to improve the range of applications of the noble metallic substrates, a comprehensive approach has been proposed for preparing non-traditional SERS nano-substrates by combining tip-enhanced gold nanostars and Raman signal amplification of the silver layer. This preparation process is conducted in two steps, including tuning the sharpness and length of tips by a modified seed growth method followed by coating the silver layer on the formed star-shaped nanoparticles. The obtained AuNS-Ag covered with an average size of around 100 nm exhibited interesting properties as a two-component nano-substrate to amplify the activities in SERS for detecting thiram. The controllable and convenient preparation route of gold nanostars is based on the comproportionation reaction of Au seed particles with Au(iii) ions, achieved by governing the stirring times of the mixture of the Au seed and the growth solution. Thus, the citrate-seed particles decreased in size (below 2 nm) and grew into nanostars with sharp tips. The thickness of Ag covering the Au particles' surface also was appropriately controlled and the tips were still exposed to the outside, which is a benefit for matching with the source excitation wavelength to achieve good SERS performance. The Raman signals of thiram can be instantly and remarkably detected with the enhancement of the substrates. Thiram can be determined without any pretreatment. It was found that the limit of detection for thiram is 0.22 ppm, and the limit of quantification is 0.73 ppm. These experimental results shed some light on developing the SERS method for detecting pesticide residue.

Developing SERS substrates based on the star-like morphology of gold nanoparticles covered by a silver layer to overcome limitations in practical analysis application.

Surface Enhanced Raman Spectroscopy: Applications in Agriculture and Food Safety

Recent global warming has resulted in shifting of weather patterns and led to intensification of natural disasters and upsurges in pests and diseases. As a result, global food systems are under pressure and need adjustments to meet the change—often by pesticides. Unfortunately, such agrochemicals are harmful for humans and the environment, and consequently need to be monitored. Traditional detection methods currently used are time consuming in terms of sample preparation, are high cost, and devices are typically not portable. Recently, Surface Enhanced Raman Scattering (SERS) has emerged as an attractive candidate for rapid, high sensitivity and high selectivity detection of contaminants relevant to the food industry and environmental monitoring. In this review, the principles of SERS as well as recent SERS substrate fabrication methods are first discussed. Following this, their development and applications for agrifood safety is reviewed, with focus on detection of dye molecules, melamine in food products, and the detection of different classes of pesticides such as organophosphate and neonicotinoids.

A universal strategy for the incorporation of internal standards into SERS substrates to improve the reproducibility of Raman signals

The uneven distribution of metal nanoparticles is a vital influencing factor in the poor uniformity of surface-enhanced Raman scattering (SERS) substrates, which is a challenge in SERS quantitative analysis. Recent reports showed that the reproducibility of a nonuniform SERS substrate can be effectively improved by the use of an internal standard (IS). However, most of these approaches require the investment of time for precise regulation, and those approaches based on the addition of an IS are specific to a certain substrate. In this work, we proposed a simple, rapid and universal method to incorporate an IS into a SERS substrate for improving the reproducibility of Raman signals based on the systematic evaluation of the influencing factors of the competitive adsorption between the IS and the target analytes. Following the proposed pressure drop-coating (PDC) method, an IS-modified gold nanobipyramids (Au NBPs)/anodic aluminum oxide (AAO) SERS substrate was fabricated within 1 min, showing high reproducibility of Raman signals. In addition, the IS-modified Au NBPs/AAO SERS substrate was successfully applied to analyze thiram in freshly squeezed apple juice and the result showed a stable Raman signal with a relative standard deviation of less than 6.00%. What is more, three different commercial SERS chips were modified with an IS molecule using the PDC method. Compared to the traditional SERS chips, the Raman signal reproducibility of the functionalized SERS chips was improved significantly. Since the addition of an IS is not based on a certain substrate, the proposed approach could be useful for all the researchers working in the field of SERS.