United States

The objective of this work was to develop methods for the analysis of antibiotics and veterinary drugs in milk listed by Food Safety and Standards Authority of India (FSSAI) using a PerkinElmer QSight 420 LC-MS/MS system with a StayClean™ ion source. To improve spiked recoveries and better method performance, two separate methods were developed for the analysis of over 30 analytes in milk due to their different polarities. For polar analytes, a mixed mode LC method was used for analyte separation and a trichloroacetic acid/acetonitrile mixed solution was used for protein precipitation. For other less polar analytes, a reversed phase UHPLC method was used for analyte separation and an acidified acetonitrile extraction was applied for sample preparation. For both methods, EDTA was used to reduce analyte-metal (i.e., calcium) ion complex formation and d-SPE was performed to remove fatty matrix using end-capped C18 sorbent. To reduce matrix effects, matrix-matched calibration with isotopic mass dilution method was performed. Both methods were validated by spiking different concentrations of analytes in a milk sample matrix. The recoveries of most analytes are between 70 to 120%. The results demonstrated that all the analytes could be determined with LOQ below the tolerance limits set by FSSAI. In addition, StayClean ion source allows continuing injections of large amounts “dirty” samples with virtually no instrument cleaning and maintenance.  An instrument robust test result dataset with continuing injections of 25,500 samples will be presented. This methodology can be extended to analysis of similar analytes in milk and milk products regulated by other governmental agencies.

2025 AOAC INTERNATIONAL Annual Meeting &amp; Exposition

Stay Clean LC-MS/MS for Determination of Antibiotics and Veterinary Drugs in Milk

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2025 AOAC INTERNATIONAL Annual Meeting & Exposition

The AOAC Annual Meeting & Exposition provides unparalleled professional development, networking, and collaboration in methods-based science.

A collaborative study was conducted to validate the suitability of an LC-MS/MS method for quantifying 128 residual veterinary drugs in six food matrices: honey, milk, egg, beef, pork liver, and lard. Twelve laboratories participated, including seven governmental, four commercial, and one incorporated foundation. Standard compounds, extraction powders, and matrices were provided to minimize material-related variations. Laboratories spiked samples with 5 ppb, 25 ppb, and 50 ppb levels, and reported recoveries along with chromatograms. At the 5 ppb spiking level, a significant number of compounds showed recoveries below 60% or above 125%, with the highest occurrence in milk (82 compounds), followed by honey (70), lard (68), pork liver (59), beef (54), and egg (49). However, at the 25 ppb level, the number of compounds with recoveries outside the range of 70%–120% significantly decreased, with pork liver showing the highest number (8  compounds), followed by honey (4), and only 2 compounds in other matrices. At the 50 ppb level, the numbers outside the range further decreased, with pork liver (5  compounds), beef (4), egg (4), lard (3), milk (1), and honey (1). These results indicate that the LC-MS/MS method performs optimally at a limit of quantification (LOQ) of 25 ppb, as the number of compounds with unacceptable recoveries significantly decreases at this level. By setting the LOQ at 25 ppb and filtering out poorly performing compounds, this method can be effectively optimized to serve as a reliable and robust approach for veterinary drug residue analysis in complex food matrices.

Collaborative Test of an LC-MS/MS Method for the Determination of 128 Veterinary Drugs in Six Food Matrices

Biofilm formation on food contact surfaces poses significant challenges to food safety due to increased resistance to disinfectants and risk of cross-contamination. This study aims to develop a machine learning–enhanced nanosensor array for the classification and prediction of bacterial biofilms on food processing surfaces, particularly stainless steel. A fluorescence-based sensor array composed of 2D nanoparticles and ssDNA probes was designed to capture compositional and developmental features of biofilms formed by four pre-screened species: Escherichia coli, Staphylococcus aureus, Salmonella enterica, and Pseudomonas fluorescens. Biofilms were cultivated in 96-well plates and on stainless steel coupons across three timepoints (days 1, 3, and 5). Sensor responses were recorded and analyzed using three machine learning algorithms—random forest (RFC), support vector classification (SVC), and multilayer perceptron (MLP)—to classify species and biofilm maturity (12 total classes). Data preprocessing included normalization, imputation, and stratified train-test splitting. Model performance was evaluated using accuracy, F1 score, and ROC-AUC with a one-vs-rest strategy. Preliminary results indicate species-specific fluorescence patterns and distinct clustering in PCA analysis. The sensor array is expected to achieve over 90% classification accuracy, with slightly lower performance for early-stage biofilms. This approach enables rapid, label-free biofilm identification and maturity assessment, offering a scalable solution for real-time monitoring of microbial contamination in food environments. The findings support the integration of advanced sensing and machine learning techniques for biofilm control strategies in food safety applications.

Machine Learning–Integrated Nanosensor Array for Predictive Biofilm Classification on Food Processing Surfaces

Introduction 
Food allergens are proteins that can trigger an immune response in allergic individuals such as nausea, vomiting, asthma, or in extreme cases anaphylactic shock.  One of the most common food allergies in children is a milk allergy.  Typically caused by cow’s milk, this allergy can also come from sheep, goats, buffalo, and other mammals.  Symptoms include wheezing, vomiting, hives, digestive problems, and even anaphylaxis.  Fortunately, studies have shown that most children will outgrow a milk allergy.
 
Objective 
To evaluate the performance of two rapid lateral flow milk assays on various market basket products. 
 
Materials and Methods 
10 milk-containing (n=6) and non-milk-containing (n=10) products were analyzed.  Milk containing samples were analyzed neat and diluted to extinction.  Non milk containing samples were spiked using a qualified milk spike stock increasing in 1 ppm increments until a positive result was achieved. In addition, milk spikes were swabbed off a stainless-steel surface (n=3 per level) to verify the detection level of a swab for each test kit.  
 
Results 
Both rapid milk test kits performed exceptionally well.  For non-milk containing samples, spiking data showed recovery down to 5 ppm total food (1.8 ppm protein) on all samples.  With market basket samples containing milk, the test kits detected milk below kit detection levels to ensure kit sensitivity within various matrices, down to 3 ppm total food (1.1 ppm protein).  In addition, the surface swabbing analysis indicated that the test kits can detect low levels of milk on food contact surfaces.   
 
Significance 
To ensure the safety of consumers with a milk allergy, it is of high importance to have a quick and reliable test for food manufacturers to use at their facilities.  The data shows that Neogen has two such rapid test kits allowing food manufacturers to have cost effective options when analyzing for milk allergens. 

An Evaluation of Rapid Lateral Flow Assays for Total Milk Detection

Per- and polyfluoroalkyl substances (PFAS) are known potential contaminants in eggs which are commonly consumed by humans. Recently, the European Union has set regulatory limits for four PFAS compounds (PFOA, PFOS, PFNA, PFHxS) in eggs, and interest in testing food for PFAS is growing in the United States. Individuals who consume eggs from backyard chickens may assume they are safer or healthier yet remain unaware of potential PFAS contamination due to unknown exposures in the chickens feed, bedding, water, and environment – potential routes through which PFAS can enter the eggs they produce.
This study compares PFAS concentrations in cage-free store-bought eggs and eggs from backyard chickens, which may be exposed to a broader range of environmental factors and dietary variations. A workflow for analysis of this challenging matrix will be presented which utilizes an automated sample preparation method that reduces analyst involvement, limits variability, and enhances throughput. The automated sample extraction process takes less than 15 minutes per sample, and the automated solid-phase extraction (SPE) system can process up to 8 samples simultaneously in under 70 minutes. This method uses dual-phase Graphitized Carbon Black and Weak Anion Exchange SPE cartridges to clean up challenging samples to ensure precise and repeatable results across samples. The automation of both the sample preparation and SPE limits variability, reduces method time, and increases throughput. Ultimately, this study aims to provide a clearer understanding of PFAS contamination in both commercially and locally sourced eggs, contributing valuable insights for public health and food safety policies.

Cracking the Challenge: Automated Extraction of PFAS in Backyard and Store-Bought Cage-Free Eggs using LC/MS-MS and dual-phase WAX/GCB Cartridges

The D3 Array Combined assay (PTM 012201) is a qualitative test for the detection of Aspergillus flavus, Aspergillus fumigatus, Aspergillus niger, Aspergillus terreus, Salmonella species, and a broad range of Shiga toxin-producing Escherichia coli (STEC) serogroups in cannabis matrixes. The test involves extraction of nucleic acids from samples followed by preamplification, Loci polymerase chain reaction (PCR), and subsequent Labeling PCR. The PCR amplification product is then hybridized to a DNA microarray. Detection of bacterial and fungal pathogens is determined by fluorescence. 
The objective of this study was to validate the D3 Array Combined method with addition of an optional enrichment step in dried cannabis flower, with the use of the Live/Dead Enrichment reagent. The method modification was validated with optional enrichment time points at 0, 2, and 24 hours.
The evaluation followed study designs from the AOAC Microbiology guidelines and AOAC Standard Method Performance Requirements (SMPRs®) 2019.001, 2020.02, and 2020.012. The modified method was compared to SMPR confirmation procedures and an unpaired Aspergillus consensus method. The results were evaluated utilizing a probability of detection (POD) statistical model.
Results showed no statistically significant difference, at the 95% and 90% confidence intervals, between the candidate method presumptive D3 Array Combined positive results and the confirmed cultural positive results at all contamination levels and enrichment time points.
This study provides data that demonstrate the PathogenDx D3 Array Combined is a reliable method for detection of Aspergillus flavus, Aspergillus fumigatus, Aspergillus niger, Aspergillus terreus, Salmonella species, and a broad range of STEC serogroups in dried cannabis flower from 0-24 hours enrichment, for all these organisms. This highly sensitive method provides results within hours of sample acquisition, compared to qPCR or cultural methods where results are obtained in 2-7 days. This method also provides the option of enrichment, providing compliance options for all cannabis testing state regulations.

Unenriched vs Enriched AOAC Performance Test MethodSM 012201 for the Detection of Aspergillus, Salmonella, and Shiga Toxin-Producing Escherichia coli in Dried Cannabis Flower

Per- and polyfluoroalkyl substances (PFAS) are synthetic fluorinated chemicals widely used in industrial and consumer products. Many are environmentally persistent and toxic. Food contact materials (FCM) containing PFAS pose human health risks via ingestion, inhalation, and environmental exposure. In response, twelve U.S. states have implemented regulations banning food packaging with total organic fluorine (TOF) levels above 100 ppm.
Conventional targeted PFAS analysis by liquid chromatography-mass spectrometry (LC-MS) may underestimate total fluorine content due to limited analyte coverage. To address this, we developed a method using a new combustion-ion chromatography (C-IC) system for comprehensive TOF determination in FCM. The method involves sample combustion under oxygen and argon, collection of combustion gases in water, followed by ion separation using anion exchange chromatography with conductivity detection. Total fluorine (TF) is measured by combusting 10–15 mg of FCM, while total inorganic fluorine (TIF) is quantified via water extraction and direct injection. TOF is calculated as TF minus TIF.
This method is implemented on the Thermo Scientific™ Cindion™ C-IC System, which minimizes PFAS contamination sources and includes a compact Z-fold combustion tube alongside full system control via Thermo Scientific™ Chromeleon™ Chromatography Data System (CDS) software. A notable advantage of this new system is the 2-in-1 system configuration for seamless switching between C-IC and standalone IC modes. This provides flexibility, allowing for measurement of TF and TIF easily. Importantly, this method supports compliance with evolving PFAS regulatory limits in FCM, providing a means for easy sample screening and determination of TF, TIF, and TOF in many sample matrices.

Determination of total PFAS in Food Contact Materials using a new combustion- ion chromatography system for total organic fluorine (TOF) analysis

Listeria species are significant foodborne pathogens with a major impact on public health. Detecting Listeria species and L. monocytogenes in foods before it can cause infection is crucial. Current detection methods use a 25 g food sample, but testing larger sample sizes has benefits such as increased sensitivity, reduced cost per test by pooling smaller samples, and meeting regulatory requirements.
This study aimed to validate the performance of the Thermo Scientific™ SureTect™ Listeria monocytogenes PCR Assay and Thermo Scientific™ SureTect™ Listeria species PCR Assay using a 125 g sample size for dairy and multi-component foods. The studies followed ISO 16140-2:2016 and AOAC Appendix J guidelines. In the unpaired study, 125 g samples were tested using the SureTect methods, and 25 g samples were tested using the reference methods. For dairy products, the SureTect method was compared to ISO 11290-1:2017 and FDA BAM Chapter 10 reference methods. For multi-component foods, the SureTect methods were compared to ISO 11290-1:2017 and USDA FSIS MLG 8.15 reference methods.
The sensitivity of the SureTect Listeria monocytogenes method was 91.2%, compared to 90.0% for the reference method. For SureTect Listeria species, it was 91.0%, versus 88.7% for the reference method. The RLOD for dairy and multi-component foods was 0.843 and 1.935 respectively for L. monocytogenes, and 0.843 and 0.780 respectively for Listeria species.
The SureTect Listeria PCR Assays are accurate and reliable for detecting Listeria species and L. monocytogenes from large sample sizes of dairy and multi-component foods. 

Listeria detection in 125g of dairy and multi-component foods using a Real-Time PCR method

Per- and polyfluoroalkyl substances (PFAS) are a group of man-made chemicals that have been in use since the mid-20th century. Solid phase extraction (SPE) is a common approach used in many published methods to concentrate and clean up samples to obtain required low part-per-trillion reporting levels in LC-MS/MS analysis.  The technique, however, is labor intensive, prone to background contamination from SPE cartridges, and can provide poor precision among operators.  Automated systems have been developed for large sample volumes (100mL – 1L), but they are tied to costly SPE extraction cartridges which consume large volumes of solvent, are generally limited to less than 10 sample positions, and need extensive rinsing to reduce carryover.
Dispersive liquid-liquid microextraction (DLLME) is a highly effective sample preparation technique, due to its simplicity, low cost, robustness, and high enrichment factors. DLLME is a miniaturized form of liquid-liquid extraction that uses minimal amounts of extraction solvent. Briefly, a small volume of sample with labeled internal standards (15 mL) is acidified, then a dispersant and extractant are added to the sample and vortexed to form a cloudy solution.  It is then centrifuged, and the top separated organic layer is moved to another vial to which a secondary extractant is added, vortexed, and centrifuged.  The PFAS contained in the extractant layer at the bottom of the vial is injected into the LCMS system.  All of this is done automatically with full control by Chromelon CDS in combination with a Thermo Scientific™ TriPlus™ RSH SMART robotic autosampler. 

Dispersive liquid-liquid micro-extraction for the automated sample preparation of PFAS as a viable alternative to solid phase extraction techniques

South Korea’s National Post-Market Surveillance (NPMS) program annually collects and tests approximately 1,650 marketed veterinary chemical drugs under formulation- and ingredient-based plans. Eighteen public authorities including 17 provincial governments and the Animal and Plant Quarantine Agency (APQA) collect products, while a testing laboratory designated by APQA has performed all active ingredient assays since 2018.
The Efficacy & Adverse-Effect Monitoring (EAEM) program complements NPMS by retesting manufacturer-retained products from NPMS noncompliants and investigating complaints submitted through public portals and repeat-offender targeting. Though separately operated, the two systems are linked by a risk-tiered feedback mechanism.
From 2018 to 2024, NPMS tested 11,579 products, detecting 193 non-compliances (1.7%), mainly powders (42%) and injectables (31%). Frequent noncompliances involved vitamin A, dexamethasone, spiramycin, amoxicillin, colistin, and florfenicol. Retained-product retesting confirmed 87 noncompliants (58.8%), but the system was abolished in 2024 due to growing concerns over the reliability of equivalence between retained and marketed products in some manufacturers.
In 2024, following the phase-out of retained-collected product testing, additional tests focusing on formulation-specific quality features such as sterility, pH, and disintegration were conducted. EAEM also performs regular tasks such as contract lab proficiency testing, LC-MS/MS cross-contamination screening, bioequivalence trials, disinfectant efficacy evaluation (ASF, AI, FMD), and veterinary diagnostic kit performance tests.
Through structured NPMS sampling, EAEM verification, and targeted pharmacovigilance inspections, Korea has maintained a noncompliance rate below 2% for veterinary chemical drugs, and uses NPMS and EAEM data to guide GMP oversight and improve regulatory policy.

Post-Market Surveillance and Risk-Based Quality Assessment of Veterinary Chemical Drugs in South Korea (2018–2024): Seven-Year Data Analysis and Regulatory Follow-Up Mechanism

Introduction:
Postbiotic materials have immense growth potential in the supplement industry (11.3% CAGR 2024-32). However, the inactivation process limits downstream QC methods since traditional plate count methods are inapplicable. Digital PCR (dPCR) is a technique that can be employed to accurately and precisely count postbiotics, provided the dPCR enumeration methods are validated and fit for purpose.
Purpose: 
To validate a dPCR method for postbiotics and establish accuracy of the method by comparison with a reference value (flow cytometry).
Method: 
Postbiotic Lacticaseibacillus paracasei raw material was validated according to AOAC Appendix K parameters and acceptance criteria. Parameters included specificity, precision/intermediate precision, accuracy, and robustness. For accuracy, low, medium, and high concentrations of L. paracasei blended with excipient were analyzed by dPCR and flow cytometry for comparison with an acceptance criterion of 70-125% recovery.
Results: 
The dPCR method for the enumeration of postbiotic L. paracasei passed the acceptance criteria for all parameters of the validation. Closely related specificity strains had no dPCR detection, whereas the eight-strain blend spiked with L. paracasei had 90% recovery, passing the specificity criterion. The low, medium, and high concentration L. paracasei products had an average of 94, 81, and 91% recovery, respectively, compared to flow cytometry, thus meeting accuracy criterion.
Significance:
dPCR is a powerful tool for postbiotic quantification. This validation demonstrates the method’s reliability and suitability for QC release testing in third-party laboratories.

Next from 2025 AOAC INTERNATIONAL Annual Meeting & Exposition

Collaborative Test of an LC-MS/MS Method for the Determination of 128 Veterinary Drugs in Six Food Matrices

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