Tuneable surface enhanced Raman spectroscopy hyphenated to chemically derivatized thin-layer chromatography plates for screening histamine in fish

Automated identification of pesticide mixtures via machine learning analysis of TLC-SERS spectra

Identification of components in pesticide mixtures has been a major challenge in spectral analysis. In this paper, we assembled monolayer Ag nanoparticles on Thin-layer chromatography (TLC) plates to prepare TLC-Ag substrates with mixture separation and surface-enhanced Raman scattering (SERS) detection. Spectral scans were performed along the longitudinal direction of the TLC-Ag substrate to generate SERS spectra of all target analytes on the TLC plate. Convolutional neural network classification and spectral angle similarity machine learning algorithms were used to identify pesticide information from the TLC-SERS spectra. It was shown that the proposed automated spectral analysis method successfully classified five categories, including four pesticides (thiram, triadimefon, benzimidazole, thiamethoxam) as well as a blank TLC-Ag data control. The location of each pesticide on the TLC plate was determined by the intersection of the information curves of the two algorithms with 100 % accuracy. Therefore, this method is expected to help regulators understand the residues of mixed pesticides in agricultural products and reduce the potential risk of agricultural products to human health and the environment.

Construction of SERS output-signal aptasensor using MOF/noble metal nanoparticles based nanozyme for sensitive histamine detection

Herein, a signal output SERS aptasensor for Histamine (HA) detection is designed. MIL-100(Fe) was loaded with gold nanoparticles (AuNPs) to form composite nanozyme MIL-100(Fe)@AuNPs, which was used in the reaction system TMB/H2O2. Silver nanoparticles (AgNPs) were synthesized as "amplifier" for the SERS signal of ox TMB. After nucleic acid functionalization, the two parts were assembled to form the multifunctional substrate with both high catalytic and SERS efficiency. In the detection system, the specific binding effect of HA aptamer toward HA induced a decrease in the assembly of AgNPs on MIL-100(Fe)@AuNPs which caused a decrease in ox TMB SERS signals. The linear relation of HA ranged from 10-11 M to 5 × 10-3 M with LOD as low as 3.9 × 10-12 M. Recovery ratio in fermented soybean products (94.42-105.75 %) proved the real sample applicability. The fabricated SERS aptasensor will provide technical support for the safety during food processing and storage.

Thin layer chromatography coupled with surface enhanced Raman scattering for rapid separation and on-site detection of multi-components

The separation and detection of multi-component mixtures has always been a challenging task. Traditional detection methods often suffer from complex operation, high cost, and low sensitivity. Surface enhanced Raman scattering (SERS) technique is a high sensitivity, powerful and rapid detection tool, which can realize the specific detection of single substance components, but it must solve the problem that multi-component mixtures cannot be accurately determined. Thin layer chromatography (TLC) technology, as a high-throughput separation technology, uses chromatographic plate as the stationary phase, and could select different developing phases for separation experiments. The advantages of TLC technology in short distance and rapid separation are widely used in protein, dye and biomedical fields. However, TLC technology has limitations in detection ability and difficulty in obtaining ideal signal intensity. The combination of TLC technology and SERS technology made the operation procedure simple and the sample size small, which can achieve rapid on-site separation and quantitative detection of mixtures. Due to the rapid development of TLC-SERS technology, it has been widely used in the investigation of various complex systems. This paper reviews the application of TLC-SERS technology in food science, environmental pollution and biomedicine.

HPTLC-Bioluminescent Bioautography Screening of Herbal Teas for Adulteration with Hypolipidemic Drugs

Teas based on nutraceutical herbs are an effective tool against hyperlipidemia. However, the adulteration with chemical drugs is frequently detected. By coupling bioluminescent bioautography with high performance thin-layer chromatography (HPTLC), we developed a facile method suitable for screening hypolipidemic drugs (ciprofibrate and bezafibrate) adulteration in five different herbal teas (lotus leaf, Apocynum, Ginkgo biloba, Gynostemia and chrysanthemum). First, the sensitivity of a bioluminescent bacteria to the analyte was evaluated on different HPTLC layer materials, revealing that the best performance was achieved on the silica gel layer. On this basis, sample extracts were separated on silica gel plates via a standardized HPTLC procedure, forming a selective detection window for the targeted compound. Then, the separation results were rapidly visualized by the bioluminescence inhibition of bacteria cells within 6 min after dipping. The observed inhibition displayed an acceptable limit of detection (<20 ng/zone or 2 mg/kg) and linearity (R² ≥ 0.9279) within a wide concentration range (50-1000 ng/zone). Furthermore, the optimized method was performed with artificially adulterated samples and the recovery rates were determined to be within the range of 71% to 91%, bracing its practical reliability. Showing superiorly high simplicity, throughput and specificity, this work demonstrated that the analytical method jointly based on HPTLC and bioautography was an ideal tool for screening bioactive compounds in complex biological matrix.

Review of Thin-Layer Chromatography Tandem with Surface-Enhanced Raman Spectroscopy for Detection of Analytes in Mixture Samples

In the real world, analytes usually exist in complex systems, and this makes direct detection by surface-enhanced Raman spectroscopy (SERS) difficult. Thin layer chromatography tandem with SERS (TLC-SERS) has many advantages in analysis such as separation effect, instant speed, simple process, and low cost. Therefore, the TLC-SERS has great potential for detecting analytes in mixtures without sample pretreatment. The review demonstrates TLC-SERS applications in diverse analytical relevant topics such as environmental pollutants, illegal additives, pesticide residues, toxic ingredients, biological molecules, and chemical substances. Important properties such as stationary phase, separation efficiency, and sensitivity are discussed. In addition, future perspectives for improving the efficiency of TLC-SERS in real sample detecting are outlined.

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.

Multiplex Sensing of Complex Mixtures by Machine Vision Analysis of TLC-SERS Images

Thin layer chromatography in tandem with surface-enhanced Raman scattering (TLC-SERS) has demonstrated tremendous potentials as a new analytical chemistry tool to detect a wide range of substances from real-world samples. However, it still faces significant challenges of multiplex sensing from complex mixtures due to the imperfect separation by TLC and the resulting interference of SERS detection. In this article, we propose a multiplex sensing method of complex mixtures by machine vision analysis of the scanning image of the TLC-SERS results. Briefly, various pure substances in solution and the complex mixture solution are separated by TLC followed by one-dimensional SERS scanning of the entire TLC plate, which generates TLC-SERS images of all target substances along the chromatography path. After that, a machine vision method is employed to extract the template images from the TLC-SERS images of pure substance solutions. Finally, we apply a feature point matching strategy based on the Winner-take-all principle, which matches the template image of each pure substance with the mixture image to confirm the existence and derive the position of each target substance in the TLC plate, respectively. Our experimental results based on the mixture solution of five different substances show that the proposed machine vision analysis is highly selective, sensitive and does not require artificial analysis of the SERS spectra. Therefore, we envision that the proposed machine vision analysis of the TLC-SERS imaging is an objective, accurate, and efficient method for multiplex sensing of trace level of target substances from complex mixtures.

A surface-imprinted surface-enhanced Raman scattering sensor for histamine detection based on dual semiconductors and Ag nanoparticles

A highly sensitive molecularly imprinted surface-enhanced Raman scattering (SERS) sensor was developed for selective detection of histamine. A combination of two semiconductors and Ag nanoparticles (NPs) was used as the SERS substrate. The SERS was induced by Ag NPs plasmon resonances as well as charge-transfer between the semiconductors and the Ag NPs. The Raman intensity and the logarithm of the histamine concentration were linear over the range 10^-8-10^-3 mol L^-1. The sensor exhibited good selectivity and had a sensitivity limit of 3.088 × 10^-9 mol L^-1. Histamine was detected in a spiked liquor sample, and its recoveries were in the range of 89.89%-109.18%.

Strong histamine torsion Raman spectrum enables direct, rapid, and ultrasensitive detection of allergic diseases

Allergic diseases are closely related to degranulation and release of histamine and difficult to diagnose because non-allergic diseases also exhibit the same clinical symptoms as allergy. Here, we report direct, rapid, and ultrasensitive detection of histamine using low-frequency molecular torsion Raman spectroscopy. We show that the low-frequency (<200 cm-1) Raman spectral intensities are stronger by one order of magnitude than those of the high-frequency Raman ones. Density functional theory calculation and nuclear magnetic resonance spectroscopy identify the strong spectral feature to be from torsions of carbon-carbon single bonds, which produce large variations of the polarizability densities in the imidazole ring and ethyl amino side chain. Using an omniphobic substrate and surface plasmonic effect of Au@SiO2 nanoparticles, the detection limit (signal-noise ratio >3) of histamine reaches 10-8 g/L in water and 10-6 g/L in serum. This scheme thus opens new lines of inquiry regarding the clinical diagnosis of allergic diseases.

Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg⁻¹ using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r²) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg⁻¹ and root mean square of cross-validation (RMSECV) ≤ 6 mg kg⁻¹ were achieved. Both models were optimal also in the validation stage, showing r² values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg⁻¹ and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

Biosensors for Biogenic Amines: A Review

Biogenic amines (BAs) are well-known biomolecules, mostly for their toxic and carcinogenic effects. Commonly, they are used as an indicator of quality preservation in food and beverages since their presence in higher concentrations is associated with poor quality. With respect to BA’s metabolic pathways, time plays a crucial factor in their formation. They are mainly formed by microbial decarboxylation of amino acids, which is closely related to food deterioration, therefore, making them unfit for human consumption. Pathogenic microorganisms grow in food without any noticeable change in odor, appearance, or taste, thus, they can reach toxic concentrations. The present review provides an overview of the most recent literature on BAs with special emphasis on food matrixes, including a description of the typical BA assay formats, along with its general structure, according to the biorecognition elements used (enzymes, nucleic acids, whole cells, and antibodies). The extensive and significant amount of research that has been done to the investigation of biorecognition elements, transducers, and their integration in biosensors, over the years has been reviewed.

Sensing Technology for Fish Freshness and Safety: A Review

Standard analytical methods for fish freshness assessment are based on the measurement of chemical and physical attributes related to fish appearance, color, meat elasticity or texture, odor, and taste. These methods have plenty of disadvantages, such as being destructive, expensive, and time consuming. All these techniques require highly skilled operators. In the last decade, rapid advances in the development of novel techniques for evaluating food quality attributes have led to the development of non-invasive and non-destructive instrumental techniques, such as biosensors, e-sensors, and spectroscopic methods. The available scientific reports demonstrate that all these new techniques provide a great deal of information with only one test, making them suitable for on-line and/or at-line process control. Moreover, these techniques often require little or no sample preparation and allow sample destruction to be avoided.

Development and Validation of a TLC-Densitometry Method for Histamine Monitoring in Fish and Fishery Products

Histamine poisoning is a significant public health problem. Therefore, the monitoring of histamine content in fish and fishery products is considered to be a crucial measure in the seafood industry. In the present study, a simple and rapid densitometric thin-layer chromatographic (TLC) method for histamine determination in fish samples was developed and validated. The samples were homogenized with 10% trichloroacetic acid and histamine was efficiently extracted. Then, an appropriate derivatization procedure was adopted with dansyl chloride. Once the derivatization was carried out, the samples were applied to silica gel TLC plates and developed by ascending chromatography with chloroform-triethylamine (6:4, v/v) as the mobile phase. The intensity of the histamine-dansyl derivative spots was measured by densitometry at 365 nm, and the quantitation was performed by BIO-1D image processing software. The validation of this method revealed good linearity and specificity over a concentration range from 6.25 to 100 mg/kg. Adequate precision was shown by relative standard deviations (RSD) smaller than 4.82%, accuracy ranged from −6.88% to 5.28%, and satisfactory recoveries ranging from 93% to 105% were obtained. The Limit of Detection and the Limit of Quantification were calculated at 4.4 mg/kg and 10.5 mg/kg, respectively. In addition, the effectiveness of the proposed method was assessed by the analysis of various samples, and the obtained results were confirmed with those achieved by the HPLC-UV method. Moreover, the developed method was found to be simple, cheap, and suitable for application to analyze several samples simultaneously.

Forecasting structure of natural products through color formation process by thin layer chromatography

With booming of computer technology, it is feasible to quantitatively extract valuable information from readily available image of objects, which dramatically reduces the cost and improves the efficiency. In this work, a structural classification method, based on data extracted from color formation process on thin layer chromatography (TLC) plates through computer processing, was established for natural products. Representative natural products exhibited good clustering and separation according to the extracted color feature, and structure of natural products can be classified by the distribution region in the color system. This method provides structural information for typical types of natural products directly from the formed color on TLC, which is very efficient and make portable device-based structure analysis of natural products possible. In addition, a general mechanism of color formation was proposed. This method is free from special instrument, high-throughput, and would facilitate large-scale screening of bioactives from natural sources.

Facile Histamine Detection by Surface-Enhanced Raman Scattering using SiO2@Au@Ag Alloy Nanoparticles

Histamine intoxication associated with seafood consumption represents a global health problem. The consumption of high concentrations of histamine can cause illnesses ranging from light symptoms, such as a prickling sensation, to death. In this study, gold-silver alloy-embedded silica (SiO2@Au@Ag) nanoparticles were created to detect histamine using surface-enhanced Raman scattering (SERS). The optimal histamine SERS signal was measured following incubation with 125 μg/mL of SiO2@Au@Ag for 2 h, with a material-to-histamine solution volume ratio of 1:5 and a phosphate-buffered saline-Tween 20 (PBS-T) solvent at pH 7. The SERS intensity of the histamine increased proportionally with the increase in histamine concentration in the range 0.1-0.8 mM, with a limit of detection of 3.698 ppm. Our findings demonstrate the applicability of SERS using nanomaterials for histamine detection. In addition, this study demonstrates that nanoalloys could have a broad application in the future.

Optical sensors for determination of biogenic amines in food

This review presents the state-of-the-art of optical sensors for determination of biogenic amines (BAs) in food by publications covering about the last 10 years. Interest in the development of rapid and preferably on-site methods for quantification of BAs is based on their important role in implementation and regulation of various physiological processes. At the same time, BAs can develop in different kinds of food by fermentation processes or microbial activity or arise due to contamination, which induces toxicological risks and food poisoning and causes serious health issues. Therefore, various optical chemosensor systems have been devised that are easy to assemble and fast responding and low-cost analytical tools. If amenable to on-site analysis, they are an attractive alternative to existing instrumental analytical methods used for BA determination in food. Hence, also portable sensor systems or dipstick sensors are described based on various probes that typically enable signal readouts such as photometry, reflectometry, luminescence, surface-enhanced Raman spectroscopy, or ellipsometry. The quantification of BAs in real food samples and the design of the sensors are highlighted and the analytical figures of merit are compared. Future instrumental trends for BA sensing point to the use of cell phone-based fully automated optical evaluation and devices that could even comprise microfluidic micro total analysis systems.

A new HPTLC platformed luminescent biosensor system for facile screening of captan residue in fruits

This study presented a HPTLC platformed luminescent biosensor system for screening captan residue. First, the potential bio-effects of layers materials on the detectability of a luminescent bacteria Photobacterium phosphoreum (ATCC 11040) as the sensor cell were assessed. From comparison, it was noteworthy that the combination of sensor cells with normal silica gel layer exclusively gave outstanding detectability (<10 ng/zone). On this basis, HPTLC mediated separation and biosensing was further optimized. Then, the obtained graphic results were digitally quantified via software processing, offering satisfactory selectivity, linearity (R² = 0.9901 within 10-80 ng/zone) and sensitivity (0.5 mg/kg against MRLs ≥ 6 mg/kg). Additionally, the performance of the established method was validated with different fruits (recover rates 75-96%, RSD < 11.8%). Meanwhile, it was demonstrated that detectability of this hybrid system would be tuneable by altering the combination of bacteria strains and layer materials, which was meaningful to strengthen the usability of microbial biosensors.

Fabrication of Fe3O4/Au@ATP@Ag Nanorod sandwich structure for sensitive SERS quantitative detection of histamine

We have successfully prepared a highly sensitive sandwich nanosensor combined Fe₃O₄ and Au@ATP@Ag nanorods for histamine detection based on surface-enhanced Raman spectroscopy (SERS). The Fe₃O₄ beads with -COOH served as a capture part to enrich histamine. The Au@ATP@Ag core-shell nanorods functionalized with Nalpha,Nalpha-Bis(carboxymethyl)-l-lysine (AB-NTA) were then used to connect with the imidazolyl group of histamine, simultaneously the internal standard 4-aminothiophenol (4-ATP) in the core-shell structure was used as the SERS signal. PLS regression model based on concentration range 10^-3-10^-8mol/L showed a linear trend with R² = 0.9907. Our new approach can quickly and reliably determine histamine in fish sample and RAW264.7 cell lysates. This protocol for histamine extraction and SERS analysis enables the development of ultra-sensitive method for histamine detection.

Quantitative TLC-SERS detection of histamine in seafood with support vector machine analysis

Scombroid fish poisoning caused by histamine intoxication is one of the most prevalent allergies associated with seafood consumption in the United States. Typical symptoms range from mild itching up to fatal cardiovascular collapse seen in anaphylaxis. In this paper, we demonstrate rapid, sensitive, and quantitative detection of histamine in both artificially spoiled tuna solution and real spoiled tuna samples using thin layer chromatography in tandem with surface-enhanced Raman scattering (TLC-SERS) sensing methods, enabled by machine learning analysis based on support vector regression (SVR) after feature extraction with principal component analysis (PCA). The TLC plates used herein, which were made from commercial food-grade diatomaceous earth, served simultaneously as the stationary phase to separate histamine from the blended tuna meat and as ultra-sensitive SERS substrates to enhance the detection limit. Using a simple drop cast method to dispense gold colloidal nanoparticles onto the diatomaceous earth plate, we were able to directly detect histamine concentration in artificially spoiled tuna solution down to 10 ppm. Based on the TLC-SERS spectral data of real tuna samples spoiled at room temperature for 0 to 48 hours, we used the PCA-SVR quantitative model to achieve superior predictive performance exceling traditional partial least squares regression (PLSR) method. This work proves that diatomaceous earth based TLC-SERS technique combined with machine-learning analysis is a cost-effective, reliable, and accurate approach for on-site detection and quantification of seafood allergen to enhance food safety.

In situ analysis of pesticide residues on the surface of agricultural products via surface-enhanced Raman spectroscopy using a flexible Au@Ag–PDMS substrate

In situ analysis of pesticide residues on the surface of agricultural products via surface-enhanced Raman spectroscopy using a flexible Au@Ag–PDMS substrate.

HPTLC-FLD-SERS as a facile and reliable screening tool: Exemplarily shown with tyramine in cheese

The serious cytotoxicity of tyramine attracted marked attention as it induced necrosis of human intestinal cells. This paper presented a novel and facile high performance thin-layer chromatography (HPTLC) method tailored for screening tyramine in cheese. Separation was performed on glass backed silica gel plates, using methanol/ethyl acetate/ ammonia (6/4/1 v/v/v) as the mobile phase. Special efforts were focused on optimizing conditions (substrate preparation, laser wavelength, salt types and concentrations) of surface enhanced Raman spectroscopy (SERS) measurements directly on plates after derivatization, which enabled molecule-specific identification of targeted bands. In parallel, fluorescent densitometry (FLD) scanning at 380</400 nm offered satisfactory quantitative performances (LOD 9 ng/zone, LOQ 17 ng/zone, linearity 0.9996 and %RSD 6.7). Including a quick extraction/cleanup step, the established method was successfully validated with different cheese samples, both qualitatively (straightforward confirmation) and quantitatively (recovery rates from 83.7 to 108.5%). Beyond this application, HPTLC-FLD-SERS provided a new horizon in fast and reliable screening of sophisticated samples like food and herb drugs, striking an excellent balance between specificity, sensitivity and simplicity.

Bimodal counterpropagating-responsive sensing material for the detection of histamine

A dual-mode system for simultaneous fluorescence and SERS sensing of histamine.