Search Results (361)

Background/Objectives: Antibiotic detection in honey is challenging due to the complexity of this product, the typically low levels of residues, and the absence of Maximum Residue Levels (MRLs) for beehive products. The use of antibiotics in apiculture poses potential risks to human health, including antimicrobial resistance and toxic effects. Reliable, sensitive, and selective analytical methods are essential to ensure food safety and enable accurate monitoring of antibiotic contamination in honey. This study aimed to validate a multi-analyte procedure in accordance with the parameters established in Commission Implementing Regulation (EU) 2021/808 for the identification and quantification of antibiotics, including tetracyclines, lincosamides, quinolones, macrolides, β-lactams, sulfonamides, and diaminopyrimidines. Methods: An extraction protocol was developed using 0.1% formic acid in ACN:H₂O (80:20, v/v), followed by a modified QuEChERS with the addition of 1 g NaCl and 2 g MgSO₄. The extracts were analyzed by UHPLC-TOF-MS. Results: The method, validated under CIR (EU) 2021/808, demonstrated robust performance, with recoveries ranging from 80.1% to 117.6%, repeatability between 0.5% and 32.2%, reproducibility between 2.3% and 31.6%, and determination coefficients (R²) ranging from 0.9429 to 0.9982. Validation was achieved for 15 antibiotic residues, with CCβ from 3 to 15 μg·kg⁻¹, LODs between 0.09 and 6.19 μg·kg⁻¹, and LOQs between 0.29 and 18.77 μg·kg⁻¹. Application to 10 commercial Portuguese honey revealed no detectable levels of the target antibiotics. Conclusions: The combination of a simplified extraction with UHPLC-TOF-MS provides a reliable approach for the determination of antibiotics in honey. This validated method represents a valuable tool for food safety monitoring and risk assessment of apiculture practices. Full article

(1) Background: Medicinal plants are widely used in folk medicine. Hypericum perforatum L. (St. John’s wort) is a medicinal plant that is used domestically and exported to other countries. This study addresses the need to develop methods for determining the composition and content of St. John’s wort to determine its biological activity. (2) Methods: High-performance liquid chromatography (HPLC) equipped with an Electrochemical Detector (ECD) and a Photodiode Array Detector (PDA) was employed to identify and quantify major phenolic compounds—gallic acid, catechin, epicatechin, hyperoside, quercetin, and hyperforin—in extracted and lyophilized St. John’s wort flower; stem; and leaf samples. Key analytes exhibited linear responses across both detection systems, within a quantification range of 0.5–10 µg/mL. (3) Results: The PDA method, validated according to ICH Q2(R1) guidelines, demonstrated specificity, linearity, precision, and accuracy, with limits of detection (LOD) ranging from 0.24 to 0.61 µg/mL and limits of quantification (LOQ) between 0.26 and 0.62 µg/mL. PDA effectively identified gallic acid, epicatechin, hyperoside, quercetin, and hyperforin, although catechin was not detected. ECD yielded comparable compound levels across the samples. (4) Conclusions: The novelty of this study lies in identifying the influence of climatic factors associated with the altitude at which St. John’s wort is grown on the content and ratio of biologically active components. Overall, the chemometric approach demonstrates the utility of raw chromatographic data in distinguishing samples by plant part and geographic origin; even when traditional compound-based comparisons may be limited. Full article

Aflatoxin B₁ (AFB₁) contamination in Scutellaria baicalensis poses a serious threat to the safety of traditional Chinese medicinal products. In this study, a sensitive and reliable ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was developed for the quantitative determination of AFB₁ in Scutellaria baicalensis. Method optimization included selection of chromatographic columns, mobile phase composition, and mass spectrometric parameters. Sample pretreatment was also optimized to reduce matrix interference and enhance extraction efficiency. The method showed excellent linearity (R² > 0.999) in the range of 0.1–10.0 µg/L, with a limit of detection (LOD) of 0.03 µg/kg and a limit of quantification (LOQ) of 0.10 µg/kg. Precision and recovery studies demonstrated good repeatability and accuracy, with intra- and inter-day relative standard deviations (RSDs) below 5.2% and recoveries ranging from 88.7% to 103.4%. Application of the method to six commercial Scutellaria baicalensis samples revealed detectable AFB₁ in two samples, though all levels were below national safety limits. This method provides a robust tool for routine monitoring of AFB₁ in herbal medicines and supports the establishment of quality control systems for Scutellaria baicalensis. Full article

Wild mushroom poisoning is an emerging global food safety issue, especially in subtropical regions like southwestern China, where incidents are geographically clustered. Current detection methods are often time-consuming and overlook region-specific toxins. We developed a rapid, sensitive, and accurate method for the simultaneous detection of ten characteristic mushroom toxins prevalent in Guizhou, China. The method combines graphite multi-walled carbon nanotubes (G-MWCNTs) for sample preparation with Orbitrap high-resolution mass spectrometry (HRMS). Wild mushroom samples were extracted via ultrasonic-assisted methanol–water extraction, purified using G-MWCNTs, and separated on a Hypersil GOLD C18 column (100 mm × 2.1 mm, 1.9 μm). Gradient elution was performed with 0.1% formic acid + 0.01% ammonia and acetonitrile; quantification used the external standard method. The method achieved LODs of 0.005–0.2 mg/kg and LOQs of 0.015–0.6 mg/kg, with RSDs below 18.11% and excellent linearity (R² = 0.9936–0.9989). Among 45 wild mushroom samples, toxin levels ranged from 0.032 to 445.10 mg/kg, with a detection rate of 22.22%, suggesting notable poisoning risk. This method reduces pretreatment time while ensuring high analytical performance, offering a reliable tool for rapid toxin screening and supporting regional surveillance of wild mushroom poisoning. Full article

Introduction: Amoxicillin and Ampicillin are among the most widely used antibiotics for treating bacterial infections. While traditional drug monitoring methods often face challenges relative to accuracy and analysis speed, optical-based techniques offer a promising alternative. Fourier Transform Infrared Spectroscopy (FTIR), a well-established tool, is particularly suited for this purpose. As their molecular structures and characteristic infrared absorption features are very similar, they could be difficult to differentiate using FTIR spectroscopy. Hence, chemometric analysis is important to overcome this challenge. This study introduces a novel approach to the standard methods of antibiotic detection and monitoring, leveraging the capabilities of vibrational spectroscopy and helping in antimicrobial stewardship. Attenuated Total Reflection (ATR)–FTIR is carried out with chemometric tools to investigate Amoxicillin and Ampicillin over different degradation processes. Principal Component Analysis (PCA) was used in the fingerprint region to detect differences between the studied antibiotics. Additionally, absorbance intensity in the fingerprint region was monitored to assess the degradation of each antibiotic over time. To achieve this, the area under the curve was calculated and subjected to inferential statistical tests for both intragroup (the degradation of the same antibiotic) and intergroup (degradation within the same time interval, comparing the two antibiotics) comparisons. All analyses were performed in OriginLab and using Python in the Google Colab and Orange environments. For the calculations of the limit of detection (LoD), the method based on the calibration curve was used. Through the experiments, it was possible to identify the fingerprints of each antibiotic and statistically separate them, despite both belonging to the same class of antibiotics, where the spectral peaks appear in the same region. For degradation, all tests were conducted with a significance level of α = 5%. In this investigation, our results show several quantification characteristics with a detection limit of 96.76 mM for Ampicillin and 66.01 mM for Amoxicillin using the peak intensity. This research demonstrates that FTIR spectroscopy is effective for antibiotic detection and has the potential to be further developed into a monitoring protocol. Full article

Polycyclic aromatic hydrocarbon (PAH) derivatives, specifically azaarenes and nitrated and oxygenated PAHs, are emerging contaminants of concern due to their increased toxicity and persistence compared to the parent PAHs. Despite their toxicity, their simultaneous analysis in complex matrices, such as in fumes emitted from bituminous mixtures, remains challenging due to limitations of conventional analytical techniques. To address this, an advanced methodology was developed using Ultra-High-Performance Liquid Chromatography coupled with High-Resolution Mass Spectrometry (UHPLC-HRMS Orbitrap Eclipse) equipped with an APCI source for the simultaneous identification and quantification of 14 PAH derivatives. Chromatographic and ionization parameters were optimized to ensure maximum sensitivity and selectivity. Following ICH Q2(R2) guidelines, the method was validated, demonstrating excellent linearity (R² > 0.99), high mass accuracy (≤5 ppm), strong precision (<15%), and excellent sensitivity. Limits of detection (LODs) ranged from 0.1 µg L⁻¹ to 0.6 µg L⁻¹ and limits of quantification (LOQs) ranged from 0.26 µg L⁻¹ to 1.87 µg L⁻¹. The validated method was successfully applied to emissions from asphalt pavement materials collected on quartz filters under controlled conditions, enabling the identification and quantification of all 14 targeted compounds. These results confirm the method’s robustness and suitability for trace-level analysis of PAH derivatives in complex environmental matrices. Full article

Building height information plays an important role in many urban-related applications, such as urban planning, disaster management, and environmental studies. With the rapid development of real scene maps, street view images are becoming a new data source for building height estimation, considering their easy collection and low cost. However, existing studies on building height estimation primarily utilize remote sensing images, with little exploration of height estimation from street-view images. In this study, we proposed a deep learning-based method for estimating the height of a single building in Baidu panoramic street view imagery. Firstly, the Segment Anything Model was used to extract the region of interest image and location features of individual buildings from the panorama. Subsequently, a cross-view matching algorithm was proposed by combining Baidu panorama and building footprint data with height information to generate building height samples. Finally, a Two-Branch feature fusion model (TBFF) was constructed to combine building location features and visual features, enabling accurate height estimation for individual buildings. The experimental results showed that the TBFF model had the best performance, with an RMSE of 5.69 m, MAE of 3.97 m, and MAPE of 0.11. Compared with two state-of-the-art methods, the TBFF model exhibited robustness and higher accuracy. The Random Forest model had an RMSE of 11.83 m, MAE of 4.76 m, and MAPE of 0.32, and the Pano2Geo model had an RMSE of 10.51 m, MAE of 6.52 m, and MAPE of 0.22. The ablation analysis demonstrated that fusing building location and visual features can improve the accuracy of height estimation by 14.98% to 69.99%. Moreover, the accuracy of the proposed method meets the LOD1 level 3D modeling requirements defined by the OGC (height error ≤ 5 m), which can provide data support for urban research. Full article

Selenium (Se) is an essential trace element involved in antioxidant redox regulation, thyroid hormone metabolism, and cancer prevention. Among its different forms, elemental selenium (Se⁰), particularly at the nanoscale, has gained growing attention in food, feed, and biomedical applications due to its lower toxicity and higher bioavailability compared to inorganic selenium species. However, the detection of Se⁰ in real samples remains challenging as current analytical methods are time-consuming, labour-intensive, and often unsuitable for rapid analysis. In this study, we developed a method for rapidly measuring Se⁰ using carbon nanodots (CNDs) produced from the Maillard reaction between glucose and glycine. The fabricated CNDs were water-dispersible and strongly fluorescent, with an average particle size of 3.90 ± 1.36 nm. Comprehensive characterisation by transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), fluorescence spectroscopy, and Raman spectroscopy confirmed their structural and optical properties. The CNDs were employed as fluorescent probes for the selective detection of Se⁰. The sensor showed a wide linear detection range (0–12.665 mmol L⁻¹), with a low detection limit (LOD) of 0.381 mmol L⁻¹ and a quantification limit (LOQ) of 0.465 mmol L⁻¹. Validation with spiked real samples—including ultra-pure water, tap water, and soft drinks—yielded high recoveries (98.6–108.1%) and low relative standard deviations (<3.4%). These results highlight the potential of CNDs as a simple, reliable, and environmentally friendly sensing platform for trace-level Se⁰ detection in complex food and beverage matrices. Full article

A sensitive method was developed for detecting diazepam residues in aquatic products using magnetic dispersive solid-phase extraction (MDSPE) coupled with ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). Samples extracted with 1% ammonia–acetonitrile were purified using synthesized Fe₃O₄@SiO₂-PSA nanoparticles via MDSPE before UPLC-MS/MS analysis. Separation was performed on a C₁₈ column with gradient elution using 0.1% formic acid–2 mM ammonium acetate/methanol. Detection employed positive electrospray ionization (ESI⁺) in multiple reaction monitoring (MRM) mode. Characterization confirmed Fe₃O₄@SiO₂-PSA’s mesoporous structure with excellent adsorption capacity and magnetic properties. The method showed good linearity (0.1–10 μg/L, r > 0.99) with an LOD and LOQ of 0.20 μg/kg and 0.50 μg/kg, respectively. Recoveries at 0.5–15.0 µg/kg spiking levels were 74.9–109% (RSDs 1.24–11.6%). This approach provides rapid, accurate, and high-precision analysis of diazepam in aquatic products, meeting regulatory requirements. Full article

Nitrite (NO₂⁻) has long been recognized as a contaminant of concern due to its detrimental effects on both human health and the environment. As a result, there is a continuing need to develop sensitive, real-time, low-cost, and portable systems for the accurate detection of trace levels of NO₂⁻ in drinking water. We present a novel, low-cost, and easy-to-fabricate amperometric sensor designed for detecting low concentrations of NO₂⁻ in drinking water. The fabrication technique involves the electrodeposition of manganese and copper oxides onto a carbon working electrode. CuO and MnO₂ act synergistically as efficient catalysts for the electrooxidation of nitrite to nitrate (NO₃⁻) thanks to their complementary redox properties. The resulting sensor exhibits high catalytic activity toward the electrooxidation of NO₂⁻, with a sensitivity of 10.83 μA/µM, a limit of detection (LOD) of 0.071 µM, and a good linear dynamic concentration range (0.2–60 µM). The sensor’s performance was evaluated against potential interfering analytes (NO₃⁻, Cl⁻, NH₄⁺, and NH₂Cl), all of which showed negligible interference. Reproducibility (maximum standard deviation 2.91%) and repeatability (usable up to three times) were also evaluated. Full article

A rapid, traceable, and highly sensitive method was developed for the simultaneous separation and quantification of 24 water-soluble synthetic colorants in premade cocktails, utilizing ultra-performance liquid chromatography coupled with diode array detection (UPLC-DAD). The purity of each colorant was individually confirmed through multi-wavelength analysis. Chromatographic conditions, including mobile phase composition and gradient elution, were meticulously optimized, achieving the separation of the 24 colorants on a BEH C18 column using a linear gradient elution within 16 min. The mobile phase consisted of an ammonium acetate solution (100 mmol/L, pH 6.25) and a mixed organic solvent of methanol and acetonitrile (2:8, v/v). The method exhibited excellent linearity across the concentration range of 0.005–10 μg/mL, with limits of detection (LODs) ranging from 0.66 to 27.78 μg/L for all 24 colorants. The method also demonstrated good precision (0.1–4.9%) at various concentration levels and recoveries ranging from 87.8% to 104.5% at spiked concentrations of 0.1, 0.5, and 1.0 μg/mL. A comparison with other published methods for colorant determination in food samples using HPLC-DAD and LC-MS (2014–2024) revealed that the proposed method offers superior performance in terms of the number of analytes detected, lower limits of detection, and reduced analytical time. Finally, the method was successfully applied to the analysis of colorants in premade cocktails from different sources. Full article

Development of sensitive and convenient alkaline phosphatase (ALP) detection methods is of great significance for food analysis, biomedical applications, and clinical tests. In this work, a sensitive detection method for ALP was established based on nanochannel-modified electrodes, where the electrochemical luminescence (ECL) signal was quenched by the enzymatic reaction product. Vertically ordered mesoporous silica film (VMSF) was rapidly grown on low-cost ITO via the electrochemically assisted self-assembly (EASA) method. The resulting modified electrode (VMSF/ITO) exhibited a uniform and ordered nanochannel structure with nanochannel diameter of 2–3 nm and charge-selective permeability, enabling the enrichment of cationic ECL emitter tris(2,2′-bipyridyl)ruthenium(II) (Ru(bpy)₃²⁺). Compared to the ITO electrode, VMSF/ITO increased the ECL signal by 60 times. In the presence of ALP, it catalyzes the hydrolysis of its substrate, disodium phenyl phosphate hydrate (DPP), generating phenol (Phe), which quenched the ECL signal of Ru(bpy)₃²⁺ and the co-reactant N,N-Dipropyl-1-propanamine (TPA). Based on this principle, ECL detection of ALP can be achieved. The linear detection range for ALP was 0.01 U/L to 30 U/L, with a limit of detection (LOD) of 0.008 U/L. The sensor exhibited high selectivity. Combined with the anti-contamination and anti-interference capabilities of VMSF, the constructed sensor enabled the detection of ALP levels in milk samples. Full article

Microbial detection in milk is crucial for food safety and quality, as beneficial and harmful microorganisms can affect consumer health and dairy product integrity. Identifying and quantifying these microorganisms helps prevent contamination and spoilage. The study employs advanced molecular techniques to detect and quantify the genomic DNA for the target hydrolytic enzyme coding genes lipA and aprX based on the multi-align sequence conserved region, specific primer pair, and hydrolysis probes designed using the singleplex qPCR and multiplex qPCR. Cultured isolates and artificially contaminated sterilized ultra-high-temperature (UHT) milk were analyzed for their specificity, cross-reactivity, and sensitivity. The finding indicated that strains with lipA and aprX genes were amplified while the other strains were not amplified. This indicated that the designed primer pairs/probes were very specific to the target gene of interest. The specificity of each design primer pair was checked using SYBR Green qPCR using 16 different isolate strains from the milk sample. The quantification specificity of each strain target gene was deemed to be with a mean Ct value for positive pseudomonas strain > 16.98 ± 1.76 (p < 0.0001), non-pseudomonas positive strain ≥ 27.47 ± 1.25 (p < 0.0001), no Ct for the negative control and molecular grade water. The sensitivity limit of detection (LOD) analyzed based on culture broth and milk sample was >10⁵ and >10⁴ in PCR amplification while it was >10⁴ and >10³ in real-time qPCR, respectively. At the same time, the correlation regression coefficient of the standard curve based on the pure culture cell DNA as the DNA concentration serially diluted (20 ng/µL to 0.0002 ng/µL) was obtained in multiplex without interference and cross-reactivity, yielding R² ≥ 0.9908 slope (−3.2591) and intercepting with a value of 37, where the efficiency reached the level of 95–102% sensitivity reached up to 0.0002 ng/µL concentration of DNA, and sensitivity of microbial load was up to 1.2 × 10² CFU/mL. Therefore, multiplex TaqMan qPCR simultaneous amplification was considered the best method developed for the detection of the lipA and aprX genes in a single tube. This will result in developing future simultaneous (three- to four-gene) detection of spoilage psychrotrophic bacteria in raw milk. Full article

Saffron is a high-cost spice due to the specific conditions for optimal growth and because of being harvested by hand. The massive income from commercializing saffron substituted with other plant parts or low-cost spices makes this spice the main target of fraudsters. Background: Different methods have been developed for detecting saffron adulteration. Most of them are time consuming and complex, and in some types of analysis, the whole untargeted dataset is combined with advanced chemometric tools to differentiate authentic from non-authentic saffron. The official method, combining UV–vis spectroscopy and LC to determine the colour strength and the crocin content, is unable to detect saffron adulterants (safflower, marigold, or turmeric) added at a level lower than 20% (w/w). As a result, innovative approaches based on rapid, high-throughput methods for the identification of adulterated saffron samples are urgently demanded to counteract food frauds. Methods: This paper describes, for the first time, the development of a method combining Direct Analysis in Real Time (DART) with the triple quadrupole MS EVOQ based on the detection of specific MS/MS transitions, promoting a rapid, robust and chromatography-free method capable of monitoring safflower and turmeric adulteration in saffron. Results: The method proved to reach low LODs, allowing the determination of tiny amounts of turmeric and safflower powder in saffron as low as 3% and 5%, respectively, speeding up the whole analytical workflow and enabling us to perform 20 analyses in 10 min. Finally, the greenness of the method was also assessed according to the 0.88 score achieved by submitting it to the greenness calculator AGREE. Conclusions: Given its speed, simplicity, and robustness, this method stands out as a strong candidate for routine implementation in testing laboratories as a rapid screening tool to detect saffron adulteration with safflower or turmeric. Full article

Nanocomposite hydroxypropyl-beta-cyclodextrin functionalized reduced graphene oxide sheets (HpβCD@rGOs) with zinc oxide flaky structures (ZnOFs) were synthesized. The ZnOFs/HpβCD@rGOs were first characterized to examine their physicochemical characteristics. The ZnOFs exhibited a highly crystalline structure intertwined with HpβCD@rGO sheets. The electrocatalyst experienced excellent electrochemical oxidation current responses toward melatonin (MTN). The interaction between the catalyst and MTN improves electrochemical activity through a synergistic action, which can be measured by a glassy carbon electrode (GCE) modified with ZnOFs/HpβCD@rGOs. This modified electrode with the increased reactive sites and a large electrochemically active surface area allows the rapid oxidation reaction of MTN. The oxidation of MTN was detected and measured with a linearity range around 0.014–0.149 and 1.149–643.341 (µM), with a low detection limit (LOD) of around 0.0105 µM or 10.5 nM. The sensitivity was around 6.19 μA μM⁻¹ cm⁻². The constructed electrode demonstrated a notable level of selectivity to MTN when the interfering (biological) chemicals with a similar structure to MTN were introduced. The real samples were tested in order to examine whether the ZnOFs/HpβCD@rGOs/GCE can be developed for the biomedical monitoring of compounds. The results suggest that ZnOFs/HpβCD@rGOs/GCE can detect MTN in in vitro human samples. Furthermore, the cost-effectiveness, enhanced electrochemical capabilities, and easy fabrication of the electrode make the ZnOFs/HpβCD@rGOs composite a feasible solution for the future industrial development of monitoring tools as sensors. Full article