Journal of AOAC International最新文献

Background: To address medication safety concerns from depleted Notopterygium incisum Ting ex H. T. Chang (NI) resources and inconsistent quality, this study employed the Quality Markers (Q-Marker) concept of Traditional Chinese Medicine to screen potential Q-Markers via multi-step compositional transfer analysis and network pharmacology.

Objective: This study aimed to screen the Q-Markers of NI for treating cardiovascular diseases.

Methods: An approach integrating mass transfer analysis, network pharmacology, and High Performance Liquid Chromatography (HPLC) fingerprinting was employed. First, HPLC fingerprints of thirteen batches of NI were established. A representative batch was selected to prepare fresh medicinal materials, processed decoction pieces, and standard decoctions. Additionally, blood-absorbed components were collected, and fingerprints for all sample types were established. The transfer rates of seven index components (chlorogenic acid, nodakenin, ferulic acid, psoralen, bergapten, phenethyl ferulate, and isoimperatorin) were determined via similarity evaluation and least squares discriminant analysis. Network pharmacology and molecular docking were further used to analyze the associations between NI's bioactive components and therapeutic targets for cardiovascular diseases.

Results: This study employed an integrated approach of HPLC fingerprinting, mass transfer analysis, network pharmacology, and molecular docking. After establishing HPLC fingerprints for thirteen NI batches, a representative batch was processed from fresh herbs, decoction pieces, standard decoctions, and blood-absorbed components for analysis, after which a determination was made for the transfer rates of seven index components and their associations with cardiovascular disease targets.

Conclusion: Chlorogenic acid, nodakenin, ferulic acid, phenethyl ferulate, and isoimperatorin are potential Q-Markers of NI for the treatment of cardiovascular diseases.

Highlights: In this study, mass transfer analysis, network pharmacology, and HPLC fingerprinting were integrated, combined with orthogonal partial least squares-discriminant analysis (OPLS-DA) and molecular docking. Potential Q-Markers of NI for the treatment of cardiovascular diseases were identified.

Background: The postharvest quality of yellow-flesh peach is compromised by rapid deterioration, necessitating effective preservation strategies.

Objective: This study investigated the efficacy of exogenous melatonin in enhancing the postharvest quality, phenolic compounds, and endogenous melatonin levels in yellow-flesh peaches.

Methods: Fruits were treated with 0.1 mM melatonin and stored for 28 days at 4 °C and 90% relative humidity. Key quality parameters, phenolic profiles, gene expression, and enzyme activities were analyzed.

Results: Melatonin treatment significantly enhanced ascorbic acid content and elevated the levels of specific phenolic compounds, including gallic, chlorogenic, p-coumaric, and caffeic acids, as well as the flavonoids rutin and catechin. This biochemical improvement was underpinned by the upregulated expression of phenolic biosynthesis genes PpPAL, PpC4H, and Pp4CL. Concurrently, the treatment boosted the activities of key enzymes in the melatonin biosynthesis pathway, including tyrosine decarboxylase (TDC), tryptamine 5-hydroxylase (T5H), serotonin N-acetyltransferase (SNAT), and N-acetylserotonin methyltransferase (ASMT), leading to a significant accumulation of endogenous melatonin.

Conclusion: Postharvest melatonin application is a promising technique for preserving quality and stimulating the biosynthesis of bioactive phenolic compounds and endogenous melatonin in yellow-flesh peaches.

Highlights: Postharvest melatonin treatment improved peach fruit quality by elevating ascorbic acid and phenolic compounds, specifically enhancing four phenolic acids and two flavonoids. Mechanistic analysis revealed these improvements were driven by upregulated phenolic biosynthetic genes (PpPAL, PpC4H, Pp4CL) and concurrent activation of melatonin pathway enzymes (TDC, T5H, SNAT, ASMT), which collectively enhanced both phenolic and endogenous melatonin biosynthesis.

Background: The AOAC Stakeholder Panel on Strategic Food Analytical Methods approved AOAC INTERNATIONAL Standard Method Performance Requirements (SMPRs®) 2023.003 for per- and polyfluoroalkyl substances (PFAS) in produce, beverages, dairy products, eggs, seafood, meat products, and feed. The U.S. Food and Drug Administration's (FDA's) method is a single laboratory validated (SLV) method for determination of 30 PFAS in food and feed.

Objective: In response to a call for minimum method performance characteristics and analytical requirements, the FDA's method for detection of PFAS in food and feed was validated in a single laboratory study with comparison to AOAC SMPR 2023.003.

Methods: Samples were extracted using (Quick, Easy, Cheap, Effective, Rugged, Safe) QuEChERS followed by solid phase extraction (SPE) clean-up and concentration using nitrogen. Analysis was performed using isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS). The method was validated for parameters such as limit of quantification, recovery, repeatability, system suitability, and reference materials were analyzed.

Results: A full validation was conducted in European Union (EU)-regulated matrixes (eggs, shrimp, clams, salmon, chicken, beef liver) and other matrixes (produce, milk, baby food, ground coffee, fish oil, protein powder, corn snaplage) with satisfactory performances both in terms of recovery and reproducibility. Recovery percentages at target limits of quantification (LOQ) and two additional levels for perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorohexane sulfonic acid (PFHxS) were between 80-120% and repeatability (RSDr) results were ≤20% for EU-regulated matrixes. For other matrixes recovery percentages were between 65-135% and repeatability results were ≤25%. All were within acceptable ranges as per AOAC SMPR 2023.003.

Conclusions: The FDA's method for detection of 30 PFAS in food and feed compares favorably with the requirements of AOAC SMPR 2023.003 and should be adopted as a First Action AOAC Official Method.

Highlights: The FDA's single lab validated method for PFAS detection in food and feed meets the requirements of AOAC SMPR 2023.003.

Background: D-gluconic acid is found in honey, ripe fruits and wine. In food industry, D-gluconic acid is used as a complexing agent and acidifier in desserts, beverages, fruit and vegetable products. D-glucono-δ-lactone is derived from gluconic acid, which hydrolyzes slowly with the release of protons. It can be used wherever slow acidification is desired.

Objective: To validate the Enzytec™ Liquid D-Gluconic acid test kit for the determination of the sum of D-gluconic and D-glucono-δ-lactone in food and beverages such as fruit juices, wine, fermented soft drinks, kombucha, and heated sausage meat.

Methods: The kit contains two ready-to-use components which makes handling easy and suitable for automation. Gluconic acid reacts with ATP in the presence of gluconate kinase to D-gluconate-6-phosphate and ADP followed by an indicator reaction that produces NADH, which is measured at 340 nm.

Results: The test is specific to D-gluconic acid and shows no side activities or interferences to relevant acids at or below 6.55 g/L. SO2 does not interfere at or below 0.5 g/L. Linearity for a test volume of 100 µL is given from 6 to 1500 mg/L. For 1000 µL, the LOQ is 0.8 mg/L. Intermediate precision is between 2.73 and 7.2% for different matrixes. Mean recovery for an incurred meat sausage is 84% at 799 mg/kg and 96% for the higher level. Spiking of the other matrixes resulted in recoveries between 96 and 103%. For automation, three applications with different test volumes were validated. Linearity is given from 2 up to 9375 mg/L.

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

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

Background: Accurate probiotic enumeration ensures the dose delivered to the mammalian host. Plate counting (PC) detects only culturable cells and can underestimate the total number of viable cells, particularly when some cells are injured or dormant and do not form colonies.

Objective: To qualify a flow cytometry assay reporting active fluorescent units (AFU) and to compare counts with the plate-count (PC) method for micro-encapsulated Lacticaseibacillus rhamnosus GG in a snack product.

Methods: Following AOAC/ICH/USP principles, precision, accuracy, ruggedness, specificity, and robustness of plate count and flow cytometry methods were evaluated for the first time in a commercial yogurt-bite snack product.

Results: Both methods fulfilled the pre-specified performance targets (%RSD ≤ 15; AFU recovery 100-104%; live/dead R2 ≥ 0.95). Analyst to analyst differences were not significant. Flow cytometry spike recoveries were 100-104% across targets. Live/dead mixtures tracked linearly (R2 ≥ 0.95). Across matched samples, AFU and CFU values were equivalent within a pre-specified ± 0.5 log band; batch means typically differed by ≤ 0.2 log with no systematic bias.

Conclusions: The qualified flow cytometry method provides same-day counts and enumerates all membrane-intact cells, complementing plate counts while meeting analytical performance criteria. Findings endorse the use of AFU in tandem to CFU assessment for probiotic quantification, label accuracy and estimation of microbiome-relevant dose in snack and finished-product matrixes.

Highlights: Flow-cytometry provided same-day results and enumerated all membrane-intact cells for label verification in snack matrixes.s.

Background: The BioSystems Gluten is an automated quantitative method based on immunoturbidimetry for quantification of the 33-mer peptidic immunotoxic fraction of gluten in food and beverages, crucial for ensuring safety for those with gluten-related disorders like celiac disease.

Objective: An AOAC Performance Tested Methods  SM validation study was performed to evaluate the BioSystems Gluten method for the quantification of gluten from wheat, barley, and rye flours across selected food and beverage commodities, including both non processed and processed products.

Methods: Validation covered non-processed (rice flour, corn flour, wine, sausage) and incurred matrixes (cornbread, rice cookies), spiked with wheat, barley, and rye gluten (0-30 mg/kg). Twelve test portions were analyzed for each matrix and contamination level using three different kit lots. The study evaluated linearity, bias, recovery, precision, limit of detection, and limit of quantification, selectivity and interferences, evaluated by recovering gluten in a defined gluten-free matrix group, stability studies of the kit components and method robustness following AOAC Guidelines for Quantitative Gluten Methods.

Results: The method met AOAC performance requirements for the quantitative determination of gluten from wheat, barley, and rye across a variety of representative food commodities and spiking levels. The validated working range spans from the limit of quantification (2.5 mg/kg) up to 200 mg/kg. The method achieved satisfactory recovery rates within the established acceptance limits, showed no evidence of analytical interferences, and yielded comparable results between the method developer and an independent laboratory, supporting its robustness and reproducibility.

Conclusions: The validation study conclusively establishes the test kit as an automated, precise, rapid, and user-friendly method for quantifying gluten concentrations in both food and incurred matrixes derived from wheat, barley, and rye flours.

Highlights: Novel automated method for gluten quantification based on spectrophotometric analysis in a Biosystems Y15 analyzer with ready-to-use and liquid reagents.

Background: Natamycin is a naturally occurring antimycotic used to prevent mold in a variety of foodstuffs, mainly processed meat, cheese and wine, and more recently certain fresh fruits.

Objective: The aim of the present study was to develop and validate a sensitive and selective method for the quantification of natamycin residues in blueberries.

Method: A methanolic extraction followed by solid phase extraction clean up and analysis by liquid chromatography coupled to high resolution tandem mass spectrometry validated for the analysis of natamycin residues in blueberries following the SANTE guidelines.

Results: The method was validated at 0.025, 0.25 and 11 mg/kg with average recoveries between 86 and 105%, and precision (%RSD) was below 15%. The detection limit for natamycin was below 0.010 mg/kg. Residues of natamycin in treated blueberries were found to range from 1 to 29 mg/kg and remained stable over 4 weeks of storage at 4 °C.

Conclusions: The LC-HRMS analysis reported here is shown to be an accurate and sensitive method for quantifying natamycin residues in blueberries.

Highlights: A method suitable for use in the regulatory and commercial monitoring of natamycin residues in blueberries is developed and presented.

Background: Water determination for plant materials generally uses loss on drying (LOD) methods. The azeotropic-toluene distillation (ATD) method is often used in pharmacopeial and food compendial monographs to determine the water content of plant materials containing volatile components because LOD will lose both water and volatile components. ATD is an environmentally hazardous method since it uses relatively large amounts of toluene with distillation.

Objective: To seek a greener approach for water determination in plant materials, USP <921> Water Determination, Method I, also known as the Karl Fischer (KF) test, is recommended due to its efficiency, specificity, and accuracy. However, it may be difficult to determine water content of plant materials using direct titration since water is tightly trapped in plant cells. An alternative approach is needed.

Methods: The United States Pharmacopeial Convention (USP) laboratory therefore developed and validated an alternative method-KF direct titration with extraction using formamide as the extraction solvent.

Results: The validation results demonstrated that the newly developed method met the required criteria for accuracy, repeatability and robustness8.

Conclusion: Using the newly established method, the water content in different species with different plant parts including fruit peel, root, rhizome, bark, cremocarp and bulb was effectively determined.

Highlights: The results generated using the KF direct titration with extraction were also compared with results of LOD applying different heating times and direct titration using different solvents (see Table 1). The differences in the results between the methods will be discussed.

Background: Polygonatum cyrtonema Hua (PCH) is widely used in traditional Chinese medicine. The components and activity are important for simultaneously quality evaluation in PCH.

Objective: This study aimed to establish an accurate, rapid and comprehensive quality evaluation method by near-infrared spectroscopy (NIR) for forecasting the total polysaccharides content (TPsC), total flavonoids content (TFC), and antioxidant activity (AA) in PCH.

Methods: PCH samples were used to establish model of TPsC, TFC, and AA in PCH by NIR combined with partial least squares regression (PLS). To enhance the accuracy of the models and remove non-essential variables, we used multiple spectral preprocessing methods and multiple chemometrics to analyze the processed full spectrum, such as competitive adaptive reweighted sampling-partial least squares regression (CARS-PLS), moving window-partial least squares regression (MW-PLS), and interval random frog-partial least squares regression (iRF-PLS). The remaining samples were used to complete external validation.

Results: Satisfactory prediction results of PLS models combined with chemometrics were obtained. The optimal chemometric of TPsC, TFC, and AA selected 157, 105, and 134 variables, respectively. For the TPsC, TFC, and AA models, which incorporated optimal spectral preprocessing and chemometric, the root mean square error of calibration (RMSEC, %) values were 0.743, 0.069, and 0.136, while the R2 values were above 0.95. The root mean square error of prediction (RMSEP, %) for these models were 1.00, 0.074, and 0.153, while R2 values were above 0.90. The remaining 20 samples were used to complete external validation, which confirmed the preeminent comparability and ability of the proposed method.

Conclusion: NIR combined with chemometrics provide an effective, fast, and nondestructive approach for evaluating quality via multiple indicators of PCH and provides a meaningful reference for evaluation of herbal medicine quality.

Highlights: NIR combined with chemometrics offers an effective, quick, nondestructive way to evaluate herbal medicine quality with multiple indicators.