4-Aminothiophenol capped halloysite nanotubes/silver nanoparticles as surface-enhanced Raman scattering probe for in-situ derivatization and selective determination of nitrite ions in meat product

Dual-mode SERS/colorimetric sensing of nitrite in meat products based on multifunctional au NPs@COF composite

The presence of nitrite in food products has generated significant public concern. A simple and rapid dual-mode surface-enhanced Raman spectroscopy (SERS)/colorimetric detection of nitrite is proposed based on a diazo reaction and multifunctional gold nanoparticle-doped covalent organic framework (Au@COF) composite. Under acidic conditions, the reaction between toluidine blue and nitrite yielded a colorless diazo salt, simultaneously attenuating its characteristic absorption peak and Raman signal. The multifunctional Au@COF materials enhanced the Raman signal and ensured good reproducibility. Additionally, the reaction rates improved, and the sensitivity was enhanced due to the excellent adsorption capacity of the COF. The proposed method demonstrated high sensitivity and excellent recovery rates for nitrite detection in food samples. This approach shows potential for precisely detecting nitrite content in real-world food samples by integrating the simplicity of colorimetric analysis with the enhanced sensitivity of SERS.

Internal standard optimization advances sensitivity and robustness of ratiometric detection method

We design a p-aminothiophenol (pATP) modified Au/ITO chip to determine nitrite ions in lake water by a ratiometric surface-enhanced Raman scattering (SERS) method based on nitrite ions triggering the transformation of pATP to p,p'-dimercaptoazobenzene (DMAB). Intriguingly, by using the SERS peak (at 1008 cm-1) from benzoic ring deforming as an internal standard instead of the traditional peak at 1080 cm-1, the detection sensitivity of the method was improved 10 times.

Robust and sensitive determination of nitrites in pickled food by surface-enhanced Raman spectroscopy

Nitrites are ubiquitous in food and pose a serious threat to human health. Therefore, the rapid and accurate determination of nitrite ion concentration in food is a prerequisite for eliminating the damage of nitrites. In this study, a robust, rapid, and sensitive method is proposed for nitrite detection in pickled food, in which Au@Ag nanoparticles are used as a reliable surface-enhanced Raman spectroscopy (SERS) substrate taking advantage of the high enhancement effect of silver and the good stability of gold. Nitrites were anchored to the surface of the SERS substrate by bridging with 4-aminophenylthiophenol (PATP). With Raman scattering cross-section amplification and internal calibration by PATP, a satisfactory linear relationship (R2 = 0.987) was established for nitrite detection in the concentration range of 5.00-100.00 μM, and the limit of detection (LOD) was 0.17 μM. This SERS-based method demonstrated high selectivity, good precision (RSD < 7.00 %), and satisfying recovery rates (101.42-107.35 %) in real samples, thus improving the determination method for nitrites. Therefore, this method has application potential in food safety and supervision.

A simple and efficient alginate hydrogel combined with surface-enhanced Raman spectroscopy for quantitative analysis of sodium nitrite in meat products

Sodium nitrite is a commonly used preservative and color protectant in the food industry. Conventional analytical methods are highly susceptible to food matrix interference, time-consuming and costly. In this study, the ion cross-linking method was employed to prepare alginate hydrogel substrates, and phenosafranin was chosen as a single-molecule probe to analyze sodium nitrite. Our investigation centered on elucidating the effects of alginate and cross-linking ion concentrations on Raman signal characteristics. The optimal Raman response was observed in the precursor solution with 1% sodium alginate and 0.1 mol L-1 cross-linking ions. The relative standard deviations (RSDs) of the feature peaks from the three substrate batches ranged from 1.22% to 16.30%, attesting the robustness and consistency of the substrates. The signal reduction of the substrates after a four-week storage period remained below 10%, indicating that the substrates had good reproducibility and stability. The limits of detection (LODs) for sodium nitrite in extracts from cured meat, luncheon meat, and sliced ham were determined to range from 3.75 mg kg-1 to 8.11 mg kg-1, with low interference from the food matrix. The support vector machine algorithm was utilized to train and predict the data, which proved to be more accurate (98.6%-99.8% recovery) than the traditional linear regression model (81.9%-112.7% recovery) in predicting the spiked samples. The application of hydrogel-based surface-enhanced Raman spectroscopy (SERS) substrates for nitrite detection in food, combined with machine learning for regression prediction in data processing, collectively augmented the potential of SERS technology in the field of food analysis.

Selective and Accurate Detection of Nitrate in Aquaculture Water with Surface-Enhanced Raman Scattering (SERS) Using Gold Nanoparticles Decorated with β-Cyclodextrins

A surface-enhanced Raman scattering (SERS) method for measuring nitrate nitrogen in aquaculture water was developed using a substrate of β-cyclodextrin-modified gold nanoparticles (SH-β-CD@AuNPs). Addressing the issues of low sensitivity, narrow linear range, and relatively poor selectivity of single metal nanoparticles in the SERS detection of nitrate nitrogen, we combined metal nanoparticles with cyclodextrin supramolecular compounds to prepare a AuNPs substrate enveloped by cyclodextrin, which exhibits ultra-high selectivity and Raman activity. Subsequently, vanadium(III) chloride was used to convert nitrate ions into nitrite ions. The adsorption mechanism between the reaction product benzotriazole (BTAH) of o-phenylenediamine (OPD) and nitrite ions on the SH-β-CD@AuNPs substrate was studied through SERS, achieving the simultaneous detection of nitrate nitrogen and nitrite nitrogen. The experimental results show that BTAH exhibits distinct SERS characteristic peaks at 1168, 1240, 1375, and 1600 cm-1, with the lowest detection limits of 3.33 × 10-2, 5.84 × 10-2, 2.40 × 10-2, and 1.05 × 10-2 μmol/L, respectively, and a linear range of 0.1-30.0 μmol/L. The proposed method provides an effective tool for the selective and accurate online detection of nitrite and nitrate nitrogen in aquaculture water.

Machine-learning-assisted SERS nanosensor platform toward chemical fingerprinting of Baijiu flavors

A novel fingerprinting platform for multiplex detection of flavor molecules in Baijiu was developed by using a surface-enhanced Raman scattering (SERS) nanosensor array in combination with machine learning. The SERS sensors were constructed by core-shell Fe₃O₄@Ag nanoparticles modified with molecules carrying end-groups of hydroxyl, pyridyl, methyl, and amino, respectively, which interacted with flavors and led to changes in the sensors' spectra. All the Raman spectra acquired from the nanosensor array contacting with the sample were concatenated into a single SERS super-spectrum, representing the flavor fingerprint which was recognized through machine learning. Principal component analysis, support vector machine, and partial least squares were utilized to build classification and quantitation models for predictive analyses. The SERS nanosensor array was successfully used for fingerprinting ten typical flavors in Baijiu including four esters, three alcohols, and three acids, with an accuracy of 100%, linear detection ranges over two orders of magnitude, and limits of detection ranging from 3.45 × 10^-3 mg/L of phenylethyl acetate to 1.21 × 10^-2 mg/L of ethyl hexanoate. It was also demonstrated that satisfactory accuracies (recoveries) ranging from 96.2 to 104% and relative standard deviations ranging from 0.65 to 2.78% were obtained for the simultaneous quantification of 3-methylbutyl acetate and phenylethyl acetate in eighteen Baijiu samples of three flavor types including sauce flavor, strong flavor, and light flavor. Compared with the existing detection techniques, this chemical fingerprinting platform is easy to use, highly sensitive, and can perform multiplex detection, which has great potential for practical applications.

A fluorescent carbon dots synthesized at room temperature for automatic determination of nitrite in Sichuan pickles

In this paper, highly fluorescent carbon dots were synthesized from sodium ascorbate and polyethyleneimine at room temperature (R-CDs). The proposed green synthesis method was energy-saving, environmentally friendly and easy online. R-CDs exhibit an optimal emission peak of 490 nm under excitation at 380 nm with a quantum yield of 32 %. R-CDs morphology, composition, and properties were characterized using TEM, FTIR, XPS, UV-vis and fluorescence spectroscopy. The study revealed that nitrite quenched the fluorescence of R-CDs under acidic conditions. Subsequently, this discovered reaction of R-CDs and nitrite was combined with flow-injection technology, and a simple, precise and automatic fluorescence strategy for nitrite determination was accomplished. The response to nitrite was linear in 5-300 μg·L^-1 concentration range and the limit of detection was 2.85 μg·L^-1 (3.3 S/k). This method was applied to nitrite determination in Sichuan pickles during the pickling process and results were consistent with the standard method, demonstrating its feasibility in practical applications.

Accurate quantification, naked eyes detection and bioimaging of nitrite using a colorimetric and near-infrared fluorescent probe in food samples and Escherichia coli

Nitrite (NO₂^-) is an inorganic contaminant that exists widely in the environment including water and food products, excessive amounts of NO₂^- would threaten humans and aquatic life. Developing a rapid and convenient sensing method for NO₂^- remains a great challenge. Herein, a colorimetric and near-infrared fluorescent probe (TBM) was synthesized and applied for sensitively and selectively detecting NO₂^- in water, food samples and Escherichia coli (E. coli). With the addition of NO₂^-, the probe TBM solution has a distinct visual color changed from red to colorless and fluorescence intensity at 620 nm quickly decreased. The probe TBM could detect NO₂^- quantitatively with a detection limit of 85 nM based on a 3σ/slope. Under optimum conditions, TBM has been successfully used to detect NO₂^- in real-world environmental and dietary samples, with positive results. Besides, paper strips loaded with TBM have been used to visually determine NO₂^- levels. Most importantly, TBM has also been proven to be able to discriminate from different concentrations of NO₂^- in E. coli by fluorescence imaging. In summary, the probe TBM was successfully developed for the accurate quantification, naked eyes detection and bioimaging of NO₂^- in water, food samples and E. coli, which provides a useful tool to better guarantee the quality and safety of daily life and food industry.

Sensitive detection of trace 4-methylimidazole utilizing a derivatization reaction-based ratiometric surface-enhanced Raman scattering platform

Herein, a facile and fast surface-enhanced Raman scattering (SERS) method with ratiometric strategy was developed for detection of 4-methylimidazole (4-MI). Via a chemical derivatization reaction with 3-amino-5-mercapto-1,2,4-triazole (AMTA) diazonium salts, 4-MI could be converted to SERS-sensitive species. The SERS intensity ratio between the peaks at 1243 cm^-1 and 1110 cm^-1 (I₁₂₄₃/I₁₁₁₀) was used for the quantification of 4-MI. In addition, the method sensitivity was further improved by the aggregation of beta-cyclodextrin-modified Ag nanoparticles (beta-CD-AgNPs). Under the optimal conditions, the limit of detection (LOD) and the limit of quantification (LOQ) for 4-MI were 1.7 nM (S/N = 3) and 5.7 nM (S/N = 10), respectively. The relative standard deviation (RSD) for 0.5 μM 4-MI was 8.2% (n = 20). This method was successfully used for the determination of 4-MI in cola samples with recoveries ranging from 92% to 106%. The present method is convenient, sensitive, selective, reliable and may have a promising application in determination of the compounds with an imidazole ring containing active hydrogen atoms.

A nanocomposite adsorbent of metallic copper, polypyrrole, halloysite nanotubes and magnetite nanoparticles for the extraction and enrichment of sulfonamides in milk

A composite adsorbent composed of metallic copper (Cu), polypyrrole (PPy), halloysite nanotubes (HNTs) and magnetite nanoparticles (Fe₃O₄) was developed to extract and enrich sulfonamides by dispersive magnetic solid phase extraction. The composite could adsorb sulfonamides via hydrogen bonding and hydrophobic, π-π and π-electron-metal interactions. The extraction conditions were optimized and the developed composite adsorbent was characterized and provided a large surface area that enhanced extraction efficiency for sulfonamides. Coupled with high performance liquid chromatography, the adsorbent was used to quantitatively determine sulfonamides found in milk samples. The response of the developed method exhibited linearity from 5.0 to 150.0 μg kg^-1 for sulfathiazole, and from 2.5 to 100.0 μg kg^-1 for sulfamerazine, sulfamonomethoxine and sulfadimethoxine. Limits of detection were between 2.5 and 5.0 μg kg^-1. Recoveries of sulfonamides in milk samples ranged from 83.0 to 99.2% with RSDs lower than 6%. The developed composite adsorbent showed good reproducibility and reusability.

Point-of-Care Detection of Salivary Nitrite Based on the Surface Plasmon-Assisted Catalytic Coupling Reaction of Aromatic Amines

Rapid quantification of nitrite (NO₂^-) in food, drink and body fluids is of significant importance for both food safety and point-of-care (POA) applications. However, conventional nitrite analytical methods are complicated, constrained to sample content, and time-consuming. Inspired by a nitrite-triggered surface plasmon-assisted catalysis (SPAC) reaction, a rapid point-of-care detection salivary nitrate was developed in this work. NO₂^- ions can trigger the rapid conversion of p-aminothiophenol (PATP) to p,p'-dimercaptozaobenzene (DMAB) on gold nanoparticles (GNPs) under light illumination, and the emerged new bands at ca. 1140, 1390, 1432 cm^-1 originating from DMAB can be used to the quantification of nitrite. Meanwhile, to make the method entirely suitable for on-site fast screen or point-of-care application, the technique is needed to be further optimized. The calibration graph for nitrates was linear in the range of 1-100 µM with a correlation coefficient of 0.9579. The limit of detection was 1 µM. The facile method could lead to a further understanding of the progression and treatment of periodontitis and to guide professionals in planning on-site campaigns to effectively control periodontal diseases.

A novel ratiometric and colorimetric probe for rapid and ultrasensitive detection of nitrite in water based on an Acenaphtho[1,2-d] imidazole derivative

The concentration of nitrite (NO₂^-) ions above allowable limits in water resources and food stuffs is considered hazardous and has been proven to be of great threat to the environment and public health. In this work, an acenaphtho [1,2-d] imidazole derivative (1) as a ratiometric colorimetric probe is developed. UV-Vis experiments demonstrate that the probe 1 shows excellent selectivity toward NO₂^- in the presence of other potential interfering species, a rapid response (20 s) and a low detection limit (100 nM) by a distinct visual color change with a bathochromic shift of 120 nm from colorless to intense yellow. Besides, this probe is further used for the quantification of nitrite ions in environmental water resources such as tap water, underground water, and surface water samples. The high recoveries (96-99% with relative standard deviations (RSD) of <2.0%) make the probe 1 a promising candidate for practical applications in daily life in the detection of nitrite ions.