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27 records · Page 2Linked to original sources
PubMed2026

Machine learning-assisted Mn-N-C nanozyme colorimetric sensor array for trace-level detection of biogenic amines in meat.

Accurate detection of biogenic amines (BAs) in meat remains challenging due to their high structural similarity and co-occurrence. Herein, an Mn-N-C nanozyme was synthesized via a metal-organic framework confined pyrolysis strategy, possessing excellent oxidase (OXD)- and peroxidase (POD)-like activities. The dual enzyme-like activity showed Km values of 0.1584 mM (OXD) and 0.1498 mM (POD), respectively, in detection system. Leveraging these properties, a colorimetric sensor array was constructed, enabling the detection of four representative BAs within a concentration range of 2-10 ppm with 100% classification accuracy. In addition, a concentration independent recognition model based on an artificial neural network was developed to address signal nonlinearity interference in meat. The integrated system achieved accurate trace-level identification of BAs in perishable fish, pork, and chicken, demonstrating its applicability for early-stage BAs monitoring and quality deterioration warning during storage and transportation.

Biogenic Amines↗
PubMed2026

The journey of fluxapyroxad, mandipropamid and mefentrifluconazole residues in two morphologically distinct chilli peppers: A comprehensive risk assessment from field to processing.

Understanding the residue fate of novel pesticides in crops is crucial for ensuring their safe application and safeguarding public health. This study examined the dissipation, processing factors (PFs), and risk assessment of fluxapyroxad, mandipropamid, and mefentrifluconazole in two morphologically distinct varieties of chilli peppers from field to processing. The half-lives of the three pesticides ranged from 5.42 to 10.05 days, following first-order kinetics. The initial residues were higher in Chaotian chilli peppers (CCP) than in long green chilli peppers (GCP). However, dissipation occurred more rapidly in CCP. Washing notably reduced the residues (PF: 0.60-0.89), whereas sun drying and oven drying concentrated them (PF: 1.92-3.74), with oven drying leading to greater concentrations. Both chronic and acute dietary risk assessments suggested acceptable risk levels for the general population. This study offers reliable guidance for the rational application of these three pesticides in chilli pepper cultivation.

Capsicum↗
PubMed2026

PdIr bimetallic nanozyme engineered metal-organic frameworks integrated dual-mode sensor toward Stx2 detection in food.

Shiga toxin II (Stx2) has attracted extensive attention due to its toxicity and pathogenicity, making the development of sensitive detection methods urgent. This study constructed a dual-mode sensing platform for the sensitive detection of Stx2 in food. Composite material UIO-66@PdIr with peroxidase-like activity and fluorescent properties was synthesized and combined with cDNA as the signal probe, while aptamer-modified magnetic beads served as the capture probe. Specific binding of Stx2 to the aptamer triggered the release of the signal probe, enabling colorimetric and fluorescence signal readout. The colorimetric mode showed a linear range of 0.05-100 ng/mL with an LOD of 0.039 ng/mL, and the fluorescence mode exhibited 0.01-1000 ng/mL with an LOD of 0.0097 ng/mL. Additionally, this method was successfully applied to the detection of Stx2 in food, and the recovery rates were 94.33% ∼ 102.20%. It indicated that the constructed sensor holds great practical potential for Stx2 detection.

Food Contamination↗
PubMed2026

Evaluation of the effects of domestic tomato processing on biopesticide residue using natural deep eutectic solvents (NADES) extractions.

The present study evaluated the fate of fourteen botanical biopesticides in processed tomato samples. Various processing methods were employed, including washing, dehydration, and the preparation of juice and sauce. The extraction was performed using more sustainable techniques, aimed at minimizing the environmental impact of conventional organic solvents by substituting them with natural deep eutectic solvents (NADES). Solid-liquid extraction (SLE) and dispersive liquid-liquid microextraction with solidification of floating organic drop (DLLME-SFOD) were utilized for solid and liquid tomato samples, respectively. The NADES used was choline chloride:2,3-butanediol (ChClBt) at a 1:4 molar ratio for both techniques, resulting in recovery values ranging from 69.2 to 106.2% for SLE, and extraction efficiencies reaching up to 46.2% for DLLME-SFOD. The impact of these processes was evaluated employing the processing factor (PF), yielding PF values of less than 1 in all cases. Compounds as pyrethrins, azadirachtin, and rotenone persisted after processing, posing a potential consumer risk.

Solanum lycopersicum↗
PubMed2026

A MIL-88@Ru-based molecularly imprinted electrochemiluminescence sensor for highly selective and sensitive detection of enrofloxacin residues in animal-derived foods.

Using a metal-organic framework (MOF) - supported Ru(bpy)32+ (MIL-88@Ru) composite luminescent material, this study innovatively adopted electropolymerization to fabricate a molecularly imprinted polymer-based electrochemiluminescent (MIP-ECL) sensor for enrofloxacin (ENR) detection in animal-derived foods. Systematic investigation of the ECL luminescence and ENR's quenching mechanism confirmed that the sensor integrates ECL's high sensitivity and MIP's high specificity, enabling rapid and accurate recognition of ENR. Experimental results show a good linear response in the range of 1 nmol/L-20 μmol/L (R2 = 0.99), a limit of detection (LOD) as low as 0.28 nmol/L, as well as excellent selectivity and stability. Recoveries of ENR in all investigated matrices ranged from 97.7% to 106.4%, confirming the reliability of the established method. This ECL-MIP coupling strategy provides a new technical approach and application references for the efficient detection of trace pollutants in food safety and environmental monitoring fields.

Enrofloxacin↗
PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12 min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22 ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗
PubMed2026

Systematic evaluation of one-dimensional-to-two-dimensional near-infrared spectroscopy transformations with deep learning for quantifying coconut sap adulteration.

Near-infrared (NIR) spectroscopy have limitations when combined with deep learning (DL) algorithms because they rely on low-dimensional datasets. Therefore, we investigated the potential of transforming one-dimensional (1D) NIR spectra into two-dimensional (2D) spectrograms using synchronous and asynchronous techniques and the continuous wavelet transform (CWT) and their effectiveness by integrating with DL for detecting adulteration in coconut sap. NIR spectra (12,500-4000 cm-1) were collected from binary mixtures (0%-100%;w/w). The performance of all DL (convolutional neural networks-CNN, AlexNet and ResNet) models was compared with that of partial least squares (PLS). The models were ranked in the mentioned order based on their performances: 2D-CWT > 2D-asynchronous > 2D-synchronous > 1D/2D-PLS. The important features of the best model can be explained and visualized using gradient-weighted-class-activation-mapping. The findings highlight that the 1D-to-2D NIR data transformation combined with DL is a highly robust approach because it addresses the feature representation gap in NIR data and effectively captures the spatial-spectral correlations.

Spectroscopy, Near-Infrared↗
PubMed2026

Interfacial engineering of cobalt tungstate-halloysite nanotube nanocomposite for electrochemical detection of synthetic vanillin in food matrices.

In processed foods and medicine, synthetic vanillin is widely used, although excessive intake poses toxicological risks. Due to the rising usage of synthetic vanillin in food products and associated health hazards, quick, sensitive, and reliable analytical methods are needed to precisely measure vanillin in complex food matrices. This work introduces a CoWO4@F-HNT/GCE nanocomposite as an efficient electrocatalytic modifier for glassy carbon electrodes aimed at trace-level synthetic vanillin detection. Structural and microscopic analyses confirmed phase-pure monoclinic CoWO4, preservation of the tubular aluminosilicate framework, and homogeneous nanoparticle anchoring on F-HNT. Differential pulse voltammetry provided a broad linear range from 0.01 to 372.14 μM and a low detection limit of 4.3 nM, together with excellent selectivity against common interferents, good cycling stability, and high inter-electrode reproducibility. These characteristics position the CoWO4@F-HNT-modified electrode as a cost-effective and reliable platform for on-site quality control of synthetic vanillin in complex food matrices.

Benzaldehydes↗
PubMed2026

Health bill beneath the plastic feast: A phthalate contamination alert from takeout food containers.

The rapid growth of takeout food consumption in China has raised concerns regarding exposure to phthalic acid esters (PAEs) from food packaging. This study investigated the presence, source, contribution, and health risk of PAEs in commonly used takeout containers. Widespread contamination was observed, with total PAE concentrations ranging from below the limit of detection to 222,000 ng/g. Diisobutyl phthalate (DIBP), dibutyl phthalate (DBP), and bis(2-ethylhexyl) phthalate (DEHP) were identified as the predominant compounds, accounting for 7.50 %, 14.7 %, and 18.7 % of the total concentration, respectively. These PAEs may originated from additives during manufacturing and potential contamination of raw materials. Human exposure assessment showed that daily exposure doses of DIBP, DBP, and DEHP via container ranged from 0.00 to 2340 ng/(kg·day) among frequent takeout consumers, contributing substantially to overall PAE body burdens. To further assess exposure and associated risks, a nationwide online questionnaire survey was conducted across China. Based on this national-scale behavioral dataset, the health risks among Chinese residents were evaluated. Although the modeled non-carcinogenic risks of DIBP, DBP, and DEHP remained within acceptable limits, the simulation suggested that approximately 70 % of participants may experience potential exceedance of the carcinogenic risk threshold for DEHP. The frequency of takeout food consumption was identified as the most important factor affecting PAE exposure. These findings underscore the importance of limiting takeout frequency and reducing reliance on plastic containers to mitigate health risks. This study provides scientific evidence to support the development of safer packaging materials and informs public health strategies.

Phthalic Acids↗