Journal of AOAC International最新文献

Background: Methylimidazole (MEI), classified as a Group 2B carcinogen by the WHO, is primarily formed as a Maillard reaction byproduct in foods. Its recent detection in tea has raised concerns regarding potential food safety risks.

Objective: This study aims to establish an ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) method for the simultaneous determination of MEIs in tea, The validated method was employed to determine the contents of MEIs across various tea types and to explore their potential sources.

Methods: Sample pretreatment was performed using a modified QuEChERS approach with isotope dilution. Chromatographic separation was achieved on a HILIC column using a gradient elution program with mobile phases consisting of 5 mmol/L ammonium acetate containing 0.1% formic acid in water and acetonitrile. Detection was carried out using Q-TOF with SWATH for MS/MS quantification.

Results: The method exhibited excellent linearity (r > 0.999) within the concentration range of 2.0-50.0 µg/L. The limits of detection (LODs) ranged from 0.0024 to 0.0045 mg/kg. The recovery ranged from 82.0% to 100.2%, with RSDs between 1.1% and 4.6%. Statistical analysis indicated that heavily fermented and roasted teas exhibited significantly higher MEI levels than lightly processed teas did (p < 0.001). Laboratory simulations experiments showed that MEI formation increased substantially at the baking temperature of 150 °C.

Conclusions: The developed UHPLC-HRMS method is accurate and precise and is suitable for the simultaneous quantification of three MEIs in tea. These results suggest that the MEI content in tea is associated with degree of fermentation and roasting, likely originating from Maillard reaction-derived byproducts.

Highlights: The proposed HRMS method mitigated the limitations commonly associated with conventional LC-MS approaches, Furthermore, the validated method was successfully employed to quantify MEI contents in tea subjected to various fermentation and roasting processes, thereby contributing to a better understanding of MEI's potential formation pathways.

Background: Increased demand for organic alternatives to soil amendment necessitates improved nitrogen (N) determination, including ammonium (NH4+) a readily available nitrogen source in manure. Current methods of NH4+ quantification include Kjeldahl distillation, ion selective electrode (ISE), and colorimetry. The Kjeldahl method has remained the most accurate and reproducible for analysis of liquid manure agricultural samples, as the latter methods are limited by cation and turbidity interferences. The Kjeldahl method is tedious, waste-generating, presents safety concerns, and only detects exchangeable NH4+ nitrogen; therefore, safer, more efficient, and informative alternatives are needed.

Objective: To create a rapid, accurate, and safer technique that does not generate chemical waste, while providing crucial quantifications.

Results: Three AOAC methods (Kjeldahl NH4+-N 973.49, Dumas TN 992.15, and Kjeldahl TKN 978.02) were utilized to demonstrate the validity of an alternate technique developed in our laboratory for the detection of NH4+-N by Dumas combustion. Known N standards were tested to confirm equivalent detection across methods in this comparative study. Liquid manure samples were analyzed for TN and NH4+ content using the standard methods and the Dumas-based technique, and quantifications were compared. Values were significantly similar between methods, verifying the comparability and effectiveness of the Kjeldahl and alternative Dumas-based techniques.

Conclusions: The technique of NH4+ determination by Dumas combustion provides equivalent quantifications to AOAC methods. This technique is faster and as accurate as the standard Kjeldahl method, without chemical waste or significant safety hazards. The technique is applicable to high-throughput requirements and can provide detection of total nitrogen, NH4+, carbon, and sulfur, as an advantage over the Kjeldahl method.

Background: The accurate identification and removal of outliers are fundamental to the development of a robust model.

Objective: Exclusively relying on a single model for outlier detection may be insufficient for the proper identification of all outliers. This study examines the identification of anomalous data using the multi-model consensus technique to address issues of false positives, false negatives, and model reliance inherent in the identification process using a singular model.

Methods: This study introduces a method called Monte Carlo cross-validation in conjunction with multiple models of Weighted Consensus for outlier identification (MCWC, Monte Carlo Weighted Consensus). The proposed method integrates Monte Carlo random sampling with three distinct modeling methods: Partial Least-Squares Regression (PLSR), Gaussian process regression (GPR), and support vector regression (SVR). This integration allows for the amalgamation of predictions from each model, facilitating the identification of outliers effectively.

Results: This study employed a dataset comprising 305 sorghum samples as the experimental foundation. The predictive model for sorghum protein was built using the data after removing outliers using the single model method and the MCWC method, respectively. The experimental results indicate that the dataset, which was obtained by removing outliers using a single modeling method, is appropriate for further modeling with the same method. However, it is not suitable for modeling with other methods due to issues related to model dependence. After applying the MCWC method to remove outliers, the average R2 of the model prediction set was found to be 0.8525. In contrast, the average R2 of the model prediction set, obtained by applying the Monte Carlo method combined exclusively with PLSR for outlier removal, is 0.8037.

Conclusions: The MCWC method exhibits superior accuracy in identifying outliers and effectively addresses challenges such as false positive, false negative, and model dependence in the process of identifying near-infrared spectral outliers. This enhances the overall predictive performance of the calibration model for spectral quantitative analysis.

Highlights: A multi-model dynamic weighted consensus outlier identification for near-infrared spectroscopy (NIRS) data is proposed. This dynamic weighting method effectively addresses the biases that can occur with simple averaging. The data after removing outliers using consensus methods is more suitable for modeling with a wider range of models.

Background: High-performance thin-layer chromatography (HPTLC) is widely used for the identification and quality assessment of botanical supplements. However, traditional interpretation methods are subjective, and variability between plates hinders reproducibility and inter-plate comparisons.

Objective: This study aimed to enhance the reproducibility and analytical utility of HPTLC by digitizing chromatograms and applying chemometric preprocessing to cranberry dietary supplement analysis.

Method: Cranberry supplements of diverse dosage forms were extracted and analyzed using a standardized HPTLC protocol. Plates were derivatized with natural products and anisaldehyde reagents and imaged under multiple lighting conditions. Digital chromatograms were processed using normalization and retention factor (RF) alignment. Chemometric methods, including principal component analysis (PCA) and analysis of variance principal component analysis (ANOVA-PCA), were applied to assess variability and improve classification.

Results: The digitization and preprocessing workflow significantly reduced plate-related variability while enhancing classification accuracy. RF alignment lowered between-plate variance from 23 to 11%, while increasing sample-type variance from 59 to 79%. Combining data from multiple derivatization and imaging conditions improved chemical fingerprinting and enabled tighter clustering in PCA models.

Conclusions: The integration of digitized HPTLC data with chemometric preprocessing modernizes the analytical workflow, improves reproducibility, and enables more robust and interpretable botanical fingerprinting. This approach supports improved quality control of botanical products and aligns with emerging standards for data transparency and reusability.

Highlights: Digitization and alignment reduce HPTLC variability and enhance reproducibility. Combined profiles from multiple derivatization conditions improve sample classification. Chemometric analysis enables better interpretation and data-driven quality control and assessment for botanicals.

Background: As a leading cause of foodborne illness worldwide, detection of Salmonella enterica subsp. enterica serovar Typhimurium is essential for food safety and public health.

Objective: This study aimed to develop a loop-mediated isothermal amplification (LAMP) assay for the rapid and sensitive detection of Salmonella ser. Typhimurium in egg products.

Methods: The primer set targeting the open reading frame STM3845 of Salmonella ser. Typhimurium was designed using PrimerExplorer v.4. The LAMP assay was optimized by adjusting reagent concentrations, reaction temperature, and incubation time, achieving the highest amplification/fluorescence in a 25.0 µL reaction at 65°C for 30 min.

Results: Results indicated that the newly designed assay could successfully detect and differentiate Salmonella ser. Typhimurium from other Salmonella serotypes and non-Salmonella bacterial pathogens except for Salmonella serotypes Montevideo, Michigan, and Senftenberg after testing 73 Salmonella ser. Typhimurium, 100 non-Typhimurium Salmonella, and 35 non-Salmonella bacterial pathogens of pure cultures. The LAMP assay was further compared with a commercial real-time PCR and FDA BAM culture method by testing pure culture and 200 inoculated (1-5 CFU/25g) egg and egg product samples, and proved to be comparable to the FDA BAM culture method; it also demonstrated 100 times more sensitivity than the real-time PCR assay in pure culture testing, with a detection limit of 0.56 log CFU/mL.

Conclusions: The newly developed LAMP assay offers a rapid, specific, and sensitive method for detecting Salmonella ser. Typhimurium in egg products. Its simplicity, speed, and sensitivity position it as a powerful tool for routine monitoring, outbreak investigation, and on-site testing in the food industry.

Highlights: Developed a LAMP assay for specific detection Salmonella ser. Typhimurium in egg products. The newly developed LAMP assay was 100 times more sensitive than the real-time PCR assay. Our new LAMP assay was validated with hundreds of pure isolates and food samples.

Background: Levamisole is an imidazothiazole anthelmintic agent widely used in poultry and livestock. In Taiwan, the Ministry of Health and Welfare has established maximum residue limits (MRLs) ranging from 0.01 to 1 μg/g for eggs, milk, and various livestock and poultry tissues.

Objective: To support regulatory monitoring, a chiral LC-MS/MS method with simple sample preparation was developed for determining levamisole residues in chicken muscle, porcine muscle, liver, kidney, fat, poultry eggs, and milk from food-producing animals.

Methods: Separation of levamisole and its enantiomer dexamisole was achieved using an Astec Cyclobond I 2000 DMP column with 100 mM ammonium acetate and acetonitrile as the mobile phase. The sample was extracted with acetonitrile-methanol (95 : 5, v/v) containing 1% formic acid, followed by cleanup with acetonitrile-saturated n-hexane.

Results: The method demonstrated good linearity (r > 0.995, 0.5-25 ng/mL) for three quantitative methods in all tested matrixes. The method achieved a LOQ of 0.005 μg/g in all matrixes. While the pre-spiked tissue calibration curve provided higher recoveries (96.3-110.1%) by compensating for both matrix effects and analyte losses during extraction, it was more labor-intensive. In contrast, the matrix-matched calibration curve and isotopically labeled internal standard (ISTD)-normalized solvent calibration curve offered slightly lower recoveries (84.8-100.4%) but showed greater practicality for routine monitoring. All calibration strategies met the accuracy and precision criteria specified in European Commission Decision 2002/657/EC and the Taiwan Food and Drug Administration (TFDA) validation guidelines. Furthermore, levamisole residues were not detected in any of the 10 commercial livestock and poultry products analyzed, confirming the applicability of the method for food surveillance.

Conclusion: A simple and rapid LC-MS/MS method was developed for the determination of levamisole in poultry and livestock matrixes, demonstrating satisfactory sensitivity, accuracy, and selectivity. The method is suitable for routine monitoring and large-scale surveillance of levamisole residues in food products.

Highlights: Development and validation of an LC-MS/MS method involving simple solvent extraction for chiral determination of levamisole in livestock and poultry products with satisfactory sensitivity, accuracy, and selectivity.

Background: Tuberculosis is spreading throughout the globe, and it is a main cause of death especially children in developing countries. Disturbances in the concentrations of essential trace elements are associated with impaired immunity in pulmonary tuberculosis infection.

Objective: In this study, the alterations in concentrations of essential trace elements, copper (Cu), iron (Fe), and zinc (Zn) in biological sample (blood serum) were determined in children with pulmonary tuberculosis (PTB), age 5 to 10 years, before and after a 6-month anti-tuberculosis treatment period.

Methods: An environmentally friendly methodology was used to treat the serum sample by means of a deep eutectic solvent, composed of oxalic acid and choline chloride (Ox-ChCl) at diverse molar ratios, and then shaking the sample mixture was sonicated in ultrasonic bath at different temperatures (40-85°C). Subsequently, dilute HNO3 (0.5 M) was added and tubes centrifuged. The supernatant solution was subjected to inductively coupled emission plasma spectrophotometry. The effects of various factors on the efficiency of digestion of the serum samples to determine Cu, Fe, and Zn, including volume of deep eutectic solvent and its mole ratio, temperature and shaking time of ultrasonic bath (sonication time) were checked.

Results: The data indicate that the PTB patients have a changed profile of all three metals in their sera and this could be more due to the active disease rather than underlying deficiencies. Compared with the non-diseased children, the levels of Fe and Zn in the serum samples of PTB-affected children were considerably lower (P < 0.05), while the Cu/Zn ratio was much higher (P < 0.05).

Conclusion: After 6-month treatment, the levels of Fe and Zn were enhanced about 16% and 30%, respectively, while 23% Cu was decreased in serum samples of PTB children. These values were slightly lower than reference values.

Highlights: Disturbances of essential trace elements levels are associated with impaired immunity. A deep eutectic solvent, composed of choline chloride and oxalic acid, was used for digestion of serum. The levels of Fe and Zn in the serum samples of PTB-affected children were significantly lower (P < 0.05). Negative correlations of Zn and Fe with Cu in serum samples of PTB-infected children were observed.

Background: Lactose is a disaccharide composed of D-galactose and D-glucose. Lactose composes 2-8% of milk by weight. Lactose is digested in the small intestine by the enzyme lactase. Lactase deficiency can lead to lactose intolerance in adults.

Objective: Enzytec™ Liquid Combi Lactose/D-Galactose is an enzymatic test kit for the determination of lactose and D-galactose in milk, milk products, infant formula, chocolate, sausage meat, almond milk, salad dressing, bread, and cookies. Excluded are lactose-free dairy products that have been enzymatically treated with lactase.

Methods: The kit contains two sets of reagents in a ready-to-use format and is suitable for automation. Lactose is cleaved with ß-galactosidase. Resulting D-galactose is oxidized by galactose-dehydrogenase and NAD+. The amount of resulting NADH is equivalent to the converted amount of lactose and free D-galactose. For measurement of free D-galactose alone the second set of reagents is used.

Results: Trueness of the lactose measurement was checked using certified reference materials with recoveries for milk, milk products, infant formula, and chocolate between 94 and 103%. Spiking experiments at low levels in almond milk, salad dressing, feta cheese, cookies, and bread revealed recoveries between 92 and 121%. Intermediate precision varied between 3 and 10.6% for lactose and between 6.5 and 7.8% for D-galactose. For automation, three applications with different test volumes were validated. Linearity is given from 12.5 mg/L to 12.5 g/L for lactose and 4.0 mg/L up to 6.25 g/L for galactose.

Conclusions: The method is robust and accurate for manual and automated applications. The method was approved as AOAC Official Method of AnalysisSM.

Highlights: The ready-to-use components of the test kit have a shelf life of at least 24 months.

Background: The U.S. Food and Drug Administration (FDA) batch certifies the anthraquinone color additive Ext. D&C Violet No. 2 (XV2, "Ext." stands for "External") to ensure that it meets requirements published in the Code of Federal Regulations (CFR). XV2 is manufactured by condensing 1,4-dihydroxy-9,10-anthracenedione (DHAQ) with p-toluidine (pT) followed by sulfonation of the condensation product at the ortho position of the pT group. Organic impurities include residual intermediates, DHAQ and pT, and reaction byproducts, 1-hydroxy-9,10-anthracenedione (MHAQ) and p-toluidine-m-sulfonic acid (PTMS). Sulfonation of the condensation product at the meta position produces an isomeric subsidiary color (mXV2). Other subsidiary colors include a dye which is itself certifiable as D&C Green No. 5 (G5) and a sulfonated phthaloylcarbazole (AV43C).

Objective: This paper describes a simple and sensitive UHPLC method for the determination of CFR-specified organic impurities in XV2 samples submitted to the FDA for batch certification.

Methods: The UHPLC method uses a 1.7 mm particle size C-18 column with aqueous ammonium acetate and acetonitrile as eluants and photodiode array detection at two wavelengths. Analytes are identified by comparing their retention times and ultraviolet-visible spectra to those of reference standards.

Results: Method validation demonstrates linearity, limits of detection, limits of quantitation, accuracy, and precision. Excellent regression coefficients for the calibration curves were obtained, with values >0.999. Overall accuracy was 98.2-104.3% and precision was 0.0075-5.27% for all analytes.

Conclusion: The UHPLC method satisfies the accuracy and precision requisites for routine certification.

Highlights: The UHPLC method reported here can be used for the determination of CFR-specified organic impurities including intermediate starting materials, reaction byproducts, and subsidiary colors in samples of XV2 submitted to the FDA for batch certification. The method's LOD is well below the CFR specification levels.