Food Analytical Methods最新文献

A core–shell structured magnetic molecularly imprinted nanoparticle (MMINP) was developed, capable of forming a photonic crystal (PC) sensor in the presence of a magnetic field for the detection of sulfamethazine (SM2) residues in food. The preparation conditions were meticulously optimized, and the adsorption performance of MMINPs was comprehensively characterized through Adsorption Kinetics Experiments and Equilibrium Binding Experiments. As the concentration of SM2 varied, the structural colors were systematically characterized under a designated magnetic field strength. The experiments revealed that within the range of SM2 concentrations from 10⁻¹ μg/L to 10³ μg/L, there was a shift in the reflected wavelength from 570 to 610 nm, and the color changed from green to red–orange. The sensor achieved a minimum detection limit of 2.75 μg/L, a maximum adsorption capacity of 3.86 mg/g, an imprint factor of 1.70, and was reused for at least five adsorption-resolution cycles. The recoveries ranged from 69.97% to 102.68% and RSD < 8.73%. The sensor introduces an innovative approach for the rapid visual colorimetric detection of SM2 in complex food matrices.

In the detection of quinolone residues in freshwater shrimp across various regions of China, more samples were found to contain residues of the banned drug norfloxacin using liquid chromatography-quadrupole tandem mass spectrometry (LC-QQQ). To further validate these results, three qualitative methods were developed: optimized LC-QQQ, liquid chromatography-quadrupole linear ion trap tandem mass spectrometry (LC-Qtrap), and liquid chromatography-quadrupole electrostatic field orbital trap tandem mass spectrometry (LC-Q Exactive). The optimized LC-QQQ involved adjusting the mobile phase gradient and monitoring specific ions, while LC-Qtrap utilized enhanced ion scanning (EPI) mode. For LC-Q Exactive, the full MS-dd-MS² mode was applied. After review, all suspected samples were excluded due to the potential interference from an endogenous substance in the shrimp that has a similar mass to norfloxacin. Each method has distinct features and can be employed as a qualitative method in different laboratory settings, offering robust technical support for food safety oversight.

Determination of progesterone in livestock and milk samples in a simple and minimally invasive way can be a challenging task in animal breeding systems; thus, a voltametric screen-printed electrode (SPE) enhanced with manganese oxide nanoparticles anchored on oxide graphene derivatives (GO/MnO₂), denominated SPE/GO/MnO₂, was successfully optimized for the indirect determination of progesterone by derivatization with hydrochloric phenylhydrazine and then directly tested in livestock and milk samples. Manganese oxide nanoparticles were obtained by a direct single synthesis through the Hummers’ reaction modified. Nanocomposites were characterized by HR-TEM, Raman spectroscopy, XPS, and electrochemical impedance spectroscopy. The combination of MnO₂ and GO nanosheet resulted in a highly sensitive material with superior electrochemical activity regarding the indirect oxidation of P4 when compared to clean disposable (SPE) sensors, and previous works concerning the determination of P4. The GO/MnO₂ nanocomposite promoted an outstanding increase towards peak signal for P4, while also exhibiting an excellent linear range for P4 (0.05–3.0 µmol L⁻¹) and a detection limit (LOD) of 0.001 µmol L⁻¹. The modified sensor also demonstrated a good recovery rate for P4 in cattle serum samples and pasteurized cow’s milk samples, which ranged from 98 to 104%. Interference studies demonstrated that the variation among peak current (Δip) of all possible interferents evaluated in this work did not exceed ± 3%. The newly developed sensor not only stands out for its distinguished sensitivity but also for its rapid and simple way to be produced, providing a direct, practical approach for determining P4 in livestock specimens.

Graphical Abstract

The novel grape cultivar BRS Carmem (Vitis vinifera L.) is highly productive and rich in anthocyanins, yet its potential for natural colorant production remains underexplored at that time. This study optimized a green extraction method using a 2³ multivariate experimental design, evaluating temperature, solvent volume, and extraction time. Citric acid (2% m/v in water) was selected as a non-toxic alternative that best extracted the pigments from the grape. The optimized conditions (64 °C, 90 mL solution, and 5 min) yielded 1061.68 mg of cyanidin-3-glucoside per 100 g of peel. The extract exhibited high reducing capacity (3312.76 mg citric acid eq./100 g of peel) and significant antimicrobial activity against Staphylococcus aureus, Salmonella spp., and Escherichia coli. Toxicity assessment using Galleria mellonella indicated an LD₅₀ of 4.8 g/kg body weight. This cost-effective, eco-friendly method produces an anthocyanin-rich extract with strong bioactivity, reinforcing its potential for natural colorant production and functional food applications.

Triazines are widely utilized in agriculture to control weeds and have been found in food frequently, posing a risk to human health. The analysis of trace contaminants in milk samples generally involves the process of protein precipitation. In this work, a lab-made semi-automated solid-phase extraction (SPE) strategy was developed for the rapid extraction of six triazine herbicides in milk samples. Six triazines were directly extracted with macroporous resin-based SPE followed by high-performance liquid chromatography detection. Some parameters affecting the extraction efficiency, including the type and amount of macroporous resin, salt concentration, pH, flow rate, extraction time, type, and volume of elution solvent, were investigated and optimized. The working curves exhibited good linearity in the concentration range of 0.78–100.00 µg L⁻¹ (R² ≥ 0.9996). LODs and LOQs were in the range of 0.15–0.31 µg L⁻¹ and 0.50–1.05 µg L⁻¹, respectively. The relative standard deviations (RSDs) for intra-day and inter-day were 1.91–3.85% and 0.59–3.78%, respectively. The recoveries and RSDs for five spiked milk samples were 91.5–107.8% and 0.15–6.77%, respectively. The proposed method eliminated the commonly used protein precipitation procedure and could improve the sample throughput, which was a simple, efficient, and economical sample pretreatment with potential applications in complicated matrix pesticide residue analysis.

Herbal teas are a key component of phytotherapy, known for their health benefits due to bioactive compounds like polyphenols and flavonoids. This study focused on optimizing an antioxidant herbal tea formulated from olive buds and leaves, enriched with fennel seeds, lemon zest, and oregano. Olive buds showed the highest polyphenol (78.79 mg GAE/g DM) and flavonoid (56 mg EC/g DM) contents, while olive leaves also contained significant levels (38.66 mg GAE/g DM polyphenols; 39.74 mg EC/g DM flavonoids). HPLC analysis confirmed the predominance of oleuropein (up to 2314 µg/mL) and hydroxytyrosol (1765 µg/mL). Antioxidant assays revealed strong activity, with low IC₅₀ values in DPPH (21–30 µg/mL for oregano, buds, and leaves) and high reducing power in FRAP (EC₅₀ ≈ 101–104 µg/mL for leaves and buds). Sensory optimization identified a balanced formulation (81% buds, 9% leaves, 5.1% fennel, 4.2% oregano, 0.7% lemon), while percolation proved the most effective extraction method, yielding 21.5 mg GAE/100 mL polyphenols and 26.5 mg EC/100 mL flavonoids. These results highlight the potential of olive by-products to develop eco-friendly, functional herbal teas combining health-promoting properties with consumer acceptability.

A novel and efficient analytical method was developed for the determination of 4-methylimidazole (4-MeI) in tea extracts using stir-bar sorptive extraction (SBSE) coupled with gas chromatography-mass spectrometry (GC-MS). Extraction parameters were optimized using ethylene glycol- and silicone-coated stir bars. The ethylene glycol-coated stir bar was used due to its higher extraction efficiency. The method demonstrated excellent linearity over the range of 2 µg/mL and 100 µg/mL (R² = 0.9982), with a limit of detection (LOD) of 1.19 µg/mL and a limit of quantification (LOQ) of 3.97 µg/mL. Method precision was confirmed with intra- and inter-day relative standard deviations of less than 1.6% and recoveries exceeding 102.26 ± 3.82%. The combined and expanded uncertainties were calculated as 0.0187 and 0.0373, respectively. Compared with liquid chromatography mass spectrometry (LC-MS/MS) and Quick, Easy, Cheap, Effective, Rugged and Safe-based (QuEChERS) methods, the developed SBSE-GC/MS protocol offers reduced matrix interference, simplified sample preparation, and comparable sensitivity. Real sample analyses validated the method’s applicability for routine monitoring of 4-MeI in commercial tea-based products. This approach offers a fast, reliable, and eco-friendly alternative for monitoring food safety and detecting thermally generated contaminants.

Aflatoxin B1 (AFB1) is one of the most hazardous foodborne toxins, posing a major risk to food safety and human health worldwide. Traditional detection techniques are often limited by lengthy procedures, high costs, and insufficient sensitivity for on-site applications. To overcome these challenges, we developed a portable, non-Faradaic electrochemical impedance spectroscopy (EIS) platform designed for rapid and highly sensitive detection of AFB1 in overnight-soaked corn samples. The working electrode was modified with a semiconducting-gold composite layer, followed by DTSSP crosslinker chemistry and antibody immobilization, which provided enhanced surface activity and stable biofunctionalization. This configuration enabled fast detection within 5 min, achieving an impressive detection limit of 0.005 ng/mL and a wide dynamic range of 0.01–40.96 ng/mL. The sensor demonstrated excellent reproducibility, with intra- and inter-study %CV consistently below 20%. Validation against laboratory benchtop systems showed a strong correlation (Pearson r = 0.977). Diagnostic evaluation further confirmed its robustness, yielding 90.6% accuracy and an AUC of 0.83. These results highlight the combined benefits of nanocomposite surface engineering and non-Faradaic EIS detection in achieving highly sensitive performance. Compact, user-friendly, and reliable, this sensing platform represents a promising solution for on-site toxin detection in food supply chains, thereby contributing to improved food safety monitoring and reduced public health risks associated with AFB1 exposure.

Graphical Abstract

This study presents a comprehensive approach for detecting and quantifying adulteration in minced meat products using image processing and colorimetric analysis techniques under both raw and cooked conditions. Common adulterants—including soy, chicken skin, sheep lung, gizzard, and bread dough—were added to minced meat at varying concentrations (0 to 80%), and their visual changes were tracked over time using red, green, blue (RGB)-based image analysis. Calibration curves were plotted, and linear regression models were developed for each adulterant. The method demonstrated high sensitivity, with the average slopes of the calibration curves being sheep lung (1.372), chicken skin (1.219), soy (1.067), gizzard (0.704), and bread dough (0.616). Corresponding relative standard deviation (RSD) values were 21.97%, 13.22%, 7.97%, 10.56%, and 10.70%, respectively, indicating reliable accuracy, particularly for soy and gizzard samples. Importantly, even at low adulteration levels, significant deviations in RGB values were detectable, confirming the reliability of the method for early-stage adulteration. Additionally, it was observed that increasing the temperature during cooking led to a reduction in RGB values, highlighting the thermal impact on color characteristics. The results confirm that the proposed hybrid method, combining image analysis, offers a rapid, low-cost, and highly sensitive solution for routine adulteration screening in meat products.