Food Safety Inspection Service Research Articles

How trustful are food safety control measures – insight into their validation

PurposeThe main purpose of this paper was to evaluate the validation process of food safety control measures.Design/methodology/approachThe validation of control measures has been analyzed at 50 food companies in Serbia. The sample included companies that produce food of both plant and animal origin and have certified food safety management systems. A total of 156 control measures that combat physical hazards (41.6%), followed by microbial hazards (34.0%) and chemical hazards (24.4%), have been analyzed. To enable quantification of the validation protocols, each control measure was assigned a score.FindingsThe validation scores showed that the highest level of validation was observed in large companies, as opposed to small and medium-sized companies (p < 0.05). The type of food safety hazards and the food sector did not reveal any statistical differences in-between the scores. The main approach to validating control measures was referring to the technical documentation of equipment used (52.6%), followed by scientific and legal requirements (30.7%). Less than 20% of the analyzed control measures were validated with operational data collected on-site. No mathematical modeling was observed for the sampled food companies. Future steps should include the development of validation guides for different types of control measures and training modules.Practical implicationsThis study can serve as an improvement guide for food safety consultants, food safety auditors, certification bodies, inspection services, food technologists and food managers.Originality/valueThis study is one of the first to provide an insight into how food companies validate their control measures to combat microbial, chemical and physical food safety hazards.

Development of a Rapid and Sensitive CANARY Biosensor Assay for the Detection of Shiga Toxin 2 from Escherichia coli.

Shiga-toxin-producing Escherichia coli (STEC) causes a wide spectrum of diseases including hemorrhagic colitis and hemolytic uremic syndrome (HUS). The current Food Safety Inspection Service (FSIS) testing methods for STEC use the Food and Drug Administration (FDA) Bacteriological Analytical Manual (BAM) protocol, which includes enrichment, cell plating, and genomic sequencing and takes time to complete, thus delaying diagnosis and treatment. We wanted to develop a rapid, sensitive, and potentially portable assay that can identify STEC by detecting Shiga toxin (Stx) using the CANARY (Cellular Analysis and Notification of Antigen Risks and Yields) B-cell based biosensor technology. Five potential biosensor cell lines were evaluated for their ability to detect Stx2. The results using the best biosensor cell line (T5) indicated that this biosensor was stable after reconstitution with assay buffer covered in foil at 4 °C for up to 10 days with an estimated limit of detection (LOD) of ≈0.1-0.2 ng/mL for days up to day 5 and ≈0.4 ng/mL on day 10. The assay detected a broad range of Stx2 subtypes, including Stx2a, Stx2b, Stx2c, Stx2d, and Stx2g but did not cross-react with closely related Stx1, abrin, or ricin. Additionally, this assay was able to detect Stx2 in culture supernatants of STEC grown in media with mitomycin C at 8 and 24 h post-inoculation. These results indicate that the STEC CANARY biosensor developed in this study is sensitive, reproducible, specific, rapid (≈3 min), and may be applicable for surveillance of the environment and food to protect public health.

Evaluation of Long-Read Sequencing Simulators to Assess Real-World Applications for Food Safety.

Shiga toxin-producing Escherichia coli (STEC) and Listeria monocytogenes are routinely responsible for severe foodborne illnesses in the United States. Current identification methods utilized by the U.S. Food Safety Inspection Service require at least four days to identify STEC and six days for L. monocytogenes. Adoption of long-read, whole genome sequencing for food safety testing could significantly reduce the time needed for identification, but method development costs are high. Therefore, the goal of this project was to use NanoSim-H software to simulate Oxford Nanopore sequencing reads to assess the feasibility of sequencing-based foodborne pathogen detection and guide experimental design. Sequencing reads were simulated for STEC, L. monocytogenes, and a 1:1 combination of STEC and Bos taurus genomes using NanoSim-H. At least 2500 simulated reads were needed to identify the seven genes of interest targeted in STEC, and at least 500 reads were needed to detect the gene targeted in L. monocytogenes. Genome coverage of 30x was estimated at 21,521, and 11,802 reads for STEC and L. monocytogenes, respectively. Approximately 5-6% of reads simulated from both bacteria did not align with their respective reference genomes due to the introduction of errors. For the STEC and B. taurus 1:1 genome mixture, all genes of interest were detected with 1,000,000 reads, but less than 1x coverage was obtained. The results suggested sample enrichment would be necessary to detect foodborne pathogens with long-read sequencing, but this would still decrease the time needed from current methods. Additionally, simulation data will be useful for reducing the time and expense associated with laboratory experimentation.

High-Pressure Processing Helps Meet the Escherichia coli O157:H7 and Shiga Toxin–Producing E. coli (STEC) Performance Standards for Beef Summer Sausage

The United States Department of Agriculture–Food Safety Inspection Service (USDA-FSIS) performance standards require that manufacturers of fermented beef sausages validate their processes to achieve a 5-log reduction of Escherichia coli O157:H7 and Shiga toxin–producing E. coli (STEC). Most processors rely on rapid fermentation to a low pH and a mild heat treatment to achieve the lethality performance standard. However, this process alters the sensorial characteristics of traditional fermented sausages. An alternative method to achieve lethality using high-pressure processing (HPP) during the manufacture of summer sausage with higher pH (5.0) and minimal heat treatment was evaluated. Sausages inoculated with circa 9.1 log CFU/g of E. coli O157:H7 and 8.9 log CFU/g of STEC were fermented to target pH values of 4.6 or 5.0. Subsequently, fermented sausages were heated to endpoint temperatures of 54.4°C, 48.9°C, or 43.3°C to the total process treatments of (1) Process A: pH 4.6 and 54.4°C, simulated cold air chilling, (2) Process B: pH 5.0 and 54.4°C, simulated cold air chilling, (3) Process C: pH 5.0 and 54.4°C, ice bath chilling, (4) Process D: pH 5.0 and 48.9°C, ice bath chilling, and (5) Process E: pH 5.0 and 43.3°C, ice bath chilling. After processing, the product was subjected to HPP (586 MPa; 4°C±2°C) for hold times of 1, 150, or 300 s and a nontreated (no HPP) control. All treatments subjected to HPP for 150 and 300 s reduced (P≤0.05) E. coli (O157:H7 and STEC) populations by&amp;gt;5.0 log CFU/g and &amp;gt;7.5 logCFU/g, respectively. The use of HPP allows for the production of more mild beef summer sausage (pH 5.0 and a mild thermal treatment of 43.3°C) while still achieving USDA-FSIS performance standards for lethality.

Assessment of United States Department of Agriculture Food Safety Inspection Service Humane Handling Enforcement Actions: 2018-2020.

Federally inspected slaughter establishments in the United States must adhere to the Humane Methods of Slaughter Act and regulations that enforce it. Failure to comply with this law results in a Humane Handling Enforcement Action (HHEA) issued by the United States Department of Agriculture Food Safety Inspection Service (USDA FSIS). The objective of this study was to systematically analyze and describe HHEAs issued between 2018 and 2020. Enforcement action notification letters were accessed from the USDA FSIS website and date, location, regulatory action, reason for noncompliance, species, and follow up action for each HHEA was recorded. Summary statistics (proportions and percentages) were calculated for the entire population dataset. Between 2018 and 2020, FSIS issued 293 HHEAs; 109 in 2018, 85 in 2019, and 99 in 2020. The majority of HHEAs (64.16%; 188 of 293) were related to the mechanical stunning of bovine (39.93%; 117 of 293) and porcine (24.23%; 71 of 293) species. The majority (50.23%; 107 of 213) of causative reasons for mechanical stun failure across all species were not clearly described; however, of those that were, most (39.12%; 68 of 213) were related to the placement of mechanical stuns. Addressing these issues through improved training and research would help to reduce the total number of HHEAs. Additional detail in reporting the events that result in HHEAs from USDA FSIS would aid in guiding corrective actions on an industry-wide scale.

Evaluation of the GENE-UP®Salmonella Method for the Detection of Salmonella Species in a Broad Range of Foods and Select Environmental Surfaces: Collaborative Study, First Action 2020.02.

The GENE-UP®Salmonella assay (Performance Tested MethodSM [PTM] 121802) is a PCR detection method that utilizes fluorescence resonance energy transfer (FRET) hybridization probes for the rapid detection of Salmonella species in foods and on environmental surfaces. The purpose of this validation was to evaluate the method's interlaboratory performance for submission to AOAC INTERNATIONAL for adoption as First Action Official Method of AnalysisSM. The GENE-UP method was evaluated in a multi-laboratory study using unpaired test portions for one food matrix, raw ground beef (80% lean). The candidate method was compared to the US Department of Agriculture (USDA), Food Safety Inspection Service, Microbiology Laboratory Guidebook (MLG) 4.10 reference method. An alternative confirmation procedure, using ASAP™ and CHROMID®Salmonella chromogenic agars, was included in the validation study. Fifteen collaborators from 14 laboratories participated. Three levels of contamination were evaluated: a non-inoculated control level (0 CFU/test portion), a low contamination level (∼0.7 CFU/test portion), and a high contamination level (∼2 CFU/test portion). Data were analyzed using the probability of detection (POD) statistical model. The dLPODC values with 95% confidence interval for the GENE-UP Salmonella method, with either alternative or traditional confirmation, were: 0.00 (-0.03, 0.03), -0.02 (-0.15, 0.12), and 0.02 (-0.03, 0.09) for the non-inoculated, low, and high contamination levels respectively. The dLPODC results demonstrate no difference in performance between the candidate method and reference method for the matrix evaluated. The GENE-UP Salmonella method, with ASAP and CHROMID Salmonella, provides industry with a simplified, rapid, and accurate workflow for the detection of Salmonella in a broad range of foods and select environmental surfaces.

Integrating the Food and Drug Administration Office of the Coordinated Outbreak Response and Evaluation Network's foodborne illness outbreak surveillance and response activities with principles of the National Incident Management System.

The Food Safety Modernization Act mandates building a national Integrated Food Safety System, which represents a seamless partnership among federal, state, local, territorial, and tribal agencies. During multistate foodborne illness outbreak investigations, local and state partners, the Centers for Disease Control and Prevention, the United States Food and Drug Administration (FDA), or the United States Department of Agriculture Food Safety Inspection Service, depending on the regulated food product, become engaged and assist in coordinating the efforts between partners involved and determine the allocation of resources. The FDA Center for Food Safety and Applied Nutrition (CFSAN) Office of the Coordinated Outbreak Response and Evaluation (CORE) Network coordinates foodborne illness outbreak surveillance, response, and post-response activities related to incidents involving multiple illnesses linked to FDA-regulated human food, dietary supplements, and cosmetic products. FDA has implemented the National Incident Management System (NIMS) Incident Command System (ICS) principles across the agency to coordinate federal response efforts, and CORE has adapted NIMS ICS principles for the emergency management of multistate foodborne illness outbreaks. CORE's implementation of ICS principles has provided several benefits to the operational cycle of foodborne illness outbreak investigations, including establishing a consistent, standardized, and transparent step-by-step approach to outbreak investigations. ICS principles have been instrumental in the development of a national platform for rapid and systematic laboratory, traceback, and epidemiologic information sharing, data analysis, and decision-making. This allows for partners across jurisdictions to reach a consensus regarding outbreak goals and objectives, deploy resources, and take regulatory and public health actions.

The Western United States has Greater Antibiotic Resistance Among Salmonella Recovered from Intestinal Cecal Samples of Food Animals.

As part of the National Antimicrobial Resistance Monitoring System (NARMS) activities, the United States Department of Agriculture (USDA) Food Safety Inspection Service (FSIS) collected cecal samples from food animal slaughter facilities throughout the country between 2014 and 2018. Of the 26,780 cecal samples from cattle, swine, chicken and turkey , 6,350 (23.71%) tested positive for Salmonella . NARMS tested Salmonella for susceptibility to aminoglycosides, folate pathway inhibitors, macrolides, phenicols, quinolones, beta lactams, and tetracyclines. Using the regional subdivisions defined in the USDA Office of Investigation, we used chi-square test to assess potential association between the region from which the samples were collected and both Salmonella prevalence and susceptibility. The results show a significant association between region and Salmonella prevalence, when accounting for source and establishment size, with the southeast region having the highest probability of finding Salmonella . However, the western region had the highest resistance probability across all antimicrobial classes except for macrolides, which showed no regional association. This association between region and resistance was strongest among isolates from cattle. Analysis of whole-genome sequencing data indicated that a significantly higher prevalence of Salmonella Newport in cattle in the western region (accounting for 9.52% of cattle isolates, compared to 3.44% in other regions) may account for the greater resistance to multiple drug classes. Approximately 90% of Salmonella Newport in the west exhibited the MDR-AmpC phenotype encoded by aph(3'')-Ib/aph(6)-Id , bla CMY-2 , floR , sul2 , and tetA. . Thus, differences in resistance across regions may be due to geographical differences in the prevalence of specific Salmonella serotypes and their accompanying resistance genes.

Ground beef recalls and subsequent food safety performance

The U.S. Food Safety Inspection Service recalled more than 370 million pounds of meat and poultry products and oversaw 680 Class 1 recalls over 1998–2014. The cost to firms was about $109 million in lost market value (Pozo and Schroeder, 2016). Thomsen and McKenzie (2001) argue that firms internalize the costs of recalls, and Marino (1997) asserts that high food safety costs lead to food safety investment, but no research has examined the impact of recalls on plant food safety performance. Using performance on tests for Salmonella conducted by the Food Safety Inspection Service as a measure of food safety, this article examines the performance on Salmonella tests of ground beef plants with Class 1 recalls. The results show that plants have high Salmonella levels before and during the year of the recall and have much lower levels afterward. The paper also shows that ground beef plants with recalls are less likely to meet the FSIS standard for Salmonella and that the likelihood of failing to meet the standard increases as the standard becomes more stringent.

Use of slaughter condemnation data to detect cattle health events in near real-time

ObjectiveUse United States cattle slaughter condemnation data as an animal health indicator for early detection of health events and to characterize trends in condemnation reasons.IntroductionData collected at livestock slaughter can be a useful source of non-specific health indicators including clinical signs, symptoms and proxy measures1. When monitored in near real-time, this data can enable the detection of both livestock and human health threats1. In the United States (US), the Federal Meat Inspection Act requires ante-mortem inspection of animals and post-mortem inspection of carcasses by veterinarians to ensure the meat product will be fit for human consumption2. Inspections are carried out by the United States Department of Agriculture (USDA) Food Safety Inspection Service (FSIS) and results are recorded in the Public Health Information System (PHIS), including the reason for condemnation if the animal or carcass is deemed unfit. Since April 2016 the USDA, Animal and Plant Health Inspection Service (APHIS), Veterinary Services (VS) has used data from the PHIS to monitor changes in the weekly count/rate of cattle condemnations for three cattle types, beef cows, dairy cows, and fed cattle (steers and heifers), and for selected condemnation reasons (central nervous system (CNS), dead, emaciation, mastitis, moribund, pneumonia, pyrexia, and septicemia). These eight reasons were chosen from 45 potential reasons recorded at condemnation as likely to identify clinical signs associated with foreign animal diseases of interest and to monitor trends in important animal health issues such as pneumonia and mastitis.MethodsPHIS slaughter and condemnation data is downloaded weekly and stored and analyzed in an Access database. Tableau visualization software is used for mapping and time series signaling charts (example basin chart Figure 1). Only establishments slaughtering more than 600 cattle/week are included in analysis because smaller establishments may not operate weekly and many have very low slaughter volumes. With the small establishments excluded, our monitoring covers 93%, 90%, and 85% of slaughtered beef, dairy, and fed cattle, respectively. Weekly analysis is conducted by cattle type for each included establishment and for establishments grouped into geographic based catchment basins. The basins were created to identify signals occurring over a region, even if at the establishment level the increase is not large enough to produce a signal. Another purpose for basins is to allow sharing of results at a summary level that does not identify an individual establishment. Weekly normalized condemnation counts are created by dividing the actual condemn counts by the total number destined for slaughter that week, and then multiplying by the average number destined for slaughter per week for the past year. The Early Aberration Reporting System (EARS C3) time series alerting algorithm is used to identify unusual increases (signals) in these weekly normalized condemnation counts. An analyst characterizes establishment and basin signals as unremarkable, notable or needing follow up with FSIS. An unremarkable signal is defined as at least one previous signal or normalized count of similar magnitude in the past 12 months and no signal for that establishment the previous week. A notable signal is defined as no previous signal or normalized count of similar magnitude in the past 12 months or two or more signals occurring over sequential weeks. Basin signals are researched to determine which establishments are responsible for the signal. An analyst determines which highly notable basin and establishment signals need follow up with FSIS. Results are summarized in a weekly report for VS cattle commodity staff about any noteworthy increases in condemnations which could indicate the emergence of disease and may warrant further investigation. In addition a 2017 annual report was completed to describe, visualize, summarize and compare condemnations from 2015-17 by cattle type and condemnation reason.ResultsIn 2017 the percentage of beef, dairy and fed cattle condemned for the eight monitored reasons out of all cattle presented for slaughter at the monitored establishments was 0.375%, 1.651%, and 0.022%, respectively. For beef cows the three most frequent reasons were pneumonia, dead and septicemia, accounting for 84.3% of monitored condemnations. Cows that either arrive at the establishment dead or die at the establishment prior to slaughter are included in the dead condemnation count. For dairy cows the three most frequent reasons were dead, septicemia and pneumonia, accounting for 93.6% of condemnations. For fed cattle the three most frequent reasons were pneumonia, dead, and septicemia, accounting for 98.2% of condemnations. Beef cow condemnations exhibited consistent seasonal trends for dead, emaciation, mastitis and pneumonia. Dairy cow condemnations exhibited consistent seasonal trends for dead, emaciation and pyrexia. Fed cattle condemnations were less influenced by seasonal trends with only dead and septicemia showing some consistent seasonality. During 2017 three notable establishment signals required follow up with FSIS: CNS in dairy cows, septicemia in fed cattle, and dead in beef cows. For 2018 (through August) 5 notable establishment signals required follow up: septicemia in both beef and dairy cows, emaciation and CNS in beef cows, and dead in dairy cows. Signals were attributed to various reasons including: changes in establishment protocol (CNS), relief inspectors classifying condemns differently and animals not responding to treatment on the farm (septicemia), a holiday effect with sick animals held longer in holding pens before slaughter (dead), a decrease in the quality of cattle purchased by the establishment (emaciation), and extremely hot weather (dead).ConclusionsA higher percentage of dairy cattle were condemned overall and were more likely to be condemned for being dead on arrival or just prior to slaughter compared to beef or fed cattle. Culled dairy cows tend to be older than beef or fed cattle and are maintained in an intense production system, therefore they are more likely to develop age related problems or chronic diseases3. In addition to timely identification of potential animal health issues, cattle producers could use this information to help focus on management practices which may decrease condemnations and result in improved animal health and revenue for producers2. Some limitations to this work are that trends described only apply to the cattle population slaughtered at FSIS inspected facilities and included in our monitoring. Condemnations are determined by FSIS inspectors at each individual slaughter establishment resulting in the potential for inspector bias to affect the data.

Properties of Gaussian Beam Propagating in Ring Resonator Sensor

In this paper, we deduce the paraxial analytical expression for the Gaussian beam propagating in the sandwich slab system which contained double negative material based on light transfer matrix and generalized Huygens-Fresnel integral equation; the evolution properties of emerging Gaussian beam contour graph intensity distribution on the receiver plane, the relation between beam spot size and negative refractive index coefficient, and beam side transmission view in slab system changed with three negative refractive index parameters are illustrated through numerical examples. What is more, we propose a ring resonator sensor to measure the concentration of NaCl solution on the basis of above theory, of which the operating principle is deliberatively analyzed, the influence of the concave mirror curvature radius on the emerging beam evolution is acquired, the functional relation between the normalized central intensity of the emerging beam, the beam spot size, and NaCl solution concentration is further developed by fit linear method, and the mathematical statistics results reach high precision and linearity. It is expected that the proposed ring resonator sensor and the corresponding conclusions can be useful for precise optical measurement, especially for food safety inspection and medical services of health care.

Evaluation of Antimicrobial Interventions against E. coli O157:H7 on the Surface of Raw Beef to Reduce Bacterial Translocation during Blade Tenderization.

The US Department of Agriculture, Food Safety Inspection Service (USDA-FSIS) considers mechanically-tenderized beef as “non-intact” and a food safety concern because of the potential for translocation of surface Escherichia coli O157:H7 into the interior of the meat that may be cooked “rare or medium-rare” and consumed. We evaluated 14 potential spray interventions on E. coli O157:H7-inoculated lean beef wafers (~106 CFU/cm2, n = 896) passing through a spray system (18 s dwell time, ~40 pounds per square inch, PSI) integrated into the front end of a Ross TC-700MC tenderizer. Inoculated and processed beef wafers were stomached with D/E neutralizing broth and plated immediately, or were held in refrigerated storage for 1-, 7-, or 14-days prior to microbial enumeration. Seven antimicrobials that showed better performance in preliminary screening on beef wafers were selected for further testing on beef subprimals in conjunction with blade tenderization. Boneless top sirloin beef subprimals were inoculated at ~2 × 104 CFU/cm2 with a four-strain cocktail of E. coli O157:H7 and passed once, lean side up, through an integrated spray system and blade tenderizer. Core samples obtained from each subprimal were examined for the presence/absence of E. coli O157:H7. The absence of E. coli O157:H7 in core samples correlated with the ability of the antimicrobials to reduce bacterial levels on the surface of beef prior to blade tenderization.

The outbreak that changed meat and poultry inspection systems worldwide.

In the course of history, one of the best recognized constants is that change happens most often and most rapidly in response to a dire situation. Even when efforts to introduce improvements have been ongoing for quite a while, it is not until an emergency or a crisis develops that people are ready to accept change to resolve the problem at hand. Such has been the case with meat and poultry safety. Many in the community, whether regulators, the industry, researchers, or advocates would agree that the most significant and impactful such event was the 1993 outbreak of foodborne illness associated with the Jack-in-the-Box restaurant chain. According to the Washington Department of Health (WDOH), where the outbreak was first reported, a cluster of children were suffering from hemolytic uremic syndrome (HUS) caused by infection with Escherichia coli O157:H7, a little-known bacterial pathogen (CDC, 1993). The investigation quickly determined that the regular-sized hamburger patties and jumbo patties produced by Vons’ Companies of California and sold to the public by Jack-in-the Box were the source of the organism. The outbreak resulted in more than 600 illnesses with four children dead from having consumed undercooked hamburgers. To say that this was a scandal is an understatement. This situation was so dire that the outbreak was discussed as an agenda item during President Bill Clinton’s first cabinet meeting in 1993, after his inauguration as the 42nd President of the United States (Cross, Personal Communication, 2018). Many things changed following that meeting, culminating in a regulatory mandate by USDA’s Food Safety & Inspection Service (FSIS) for industry to implement the Hazard Analysis and Critical Control Point (HACCP) system at every federally inspected meat and poultry slaughter and processing plant in the United States. However, it may come as a surprise to some that the foundation for changes in food safety processes had already been in the works the year preceding the outbreak. A review of the events that took place in 1992 and how those activities had a direct impact on the events to come is justified.

A Novel Selective Medium for Simultaneous Enrichment of Shiga Toxin–Producing Escherichia coli and Salmonella in Ground Beef

Microbiological analysis of ground beef for contamination by both Salmonella and Shiga toxin-producing Escherichia coli (STEC) is performed by the U.S. Department of Agriculture, Food Safety Inspection Service (FSIS), as part of its Performance Standards Verification Testing program. FSIS has established a zero tolerance for STEC serotype O157:H7 and serogroups O26, O45, O103, O111, O121, and O145 because they are regarded as adulterants. The detection and isolation of these specific serogroups presents a technical challenge necessitating time-consuming and costly laboratory procedures that often exceed the technical capabilities of many small internal and reference laboratories. We describe here a method using a novel STEC and Salmonella selective (SSS) broth that allows for simultaneous selective enrichment of STEC and Salmonella sp., providing isolation and detection from the same broth. The method only involves direct plating from beef enrichments to detect suspect isolates that can be easily confirmed by using immunoassays or PCR, rendering the isolation simpler and less costly than the current described methods. In a side-by-side comparison with modified tryptic soy broth (mTSB), the use of SSS broth resulted in primarily isolating STEC and Salmonella sp., while substantially suppressing the growth of other gram-negative Enterobacteriacae by 90%. Significantly more (χ2 < 3.84) samples containing E. coli O157:H7 and STEC O26, O111, O121, and O145 and a nondifferent (χ2 > 3.84) number of samples containing STEC O103 and O45 were identified when enriching in SSS broth. Coenrichment using six different Salmonella serovars showed numerically greater but not significant (χ2 < 3.84) positive samples by using SSS broth compared with mTSB for a majority of serotypes.

Evaluation of mericon E. coli O157 Screen Plus and mericon E. coli STEC O-Type Pathogen Detection Assays in Select Foods: Collaborative Study, First Action 2017.05.

QIAGEN mericon Escherichia coli O157 Screen Plus and mericon E. coli Shiga toxin-producing E. coli (STEC) O-Type Pathogen Detection Assays use Real-Time PCR technology for the rapid, accurate detection of E. coli O157 and the "big six" (O26, O45, O103, O111, O121, O145) (non-O157 STEC) in select food types. Using a paired study design, the assays were compared with the U.S. Department of Agriculture, Food Safety Inspection Service Microbiology Laboratory Guidebook Chapter 5.09 reference method for the detection of E. coli O157:H7 in raw ground beef. Both mericon assays were evaluated using the manual and an automated DNA extraction method. Thirteen technicians from five laboratories located within the continental United States participated in the collaborative study. Three levels of contamination were evaluated. Statistical analysis was conducted according to the probability of detection (POD) statistical model. Results obtained for the low-inoculum level test portions produced a difference between laboratories POD (dLPOD) value with a 95% confidence interval of 0.00 (-0.12, 0.12) for the mericon E. coli O157 Screen Plus with manual and automated extraction and mericon E. coli STEC O-Type with manual extraction and -0.01 (-0.13, 0.10) for the mericon E. coli STEC O-Type with automated extraction. The dLPOD results indicate equivalence between the candidate methods and the reference method.

Determination of Monensin in Bovine Tissues: A Bridging Study Comparing the Bioautographic Method (FSIS CLG-MON) with a Liquid Chromatography-Tandem Mass Spectrometry Method (OMA 2011.24).

The U.S. Department of Agriculture, Food Safety Inspection Service regulatory method for monensin, Chemistry Laboratory Guidebook CLG-MON, is a semiquantitative bioautographic method adopted in 1991. Official Method of AnalysisSM (OMA) 2011.24, a modern quantitative and confirmatory LC-tandem MS method, uses no chlorinated solvents and has several advantages, including ease of use, ready availability of reagents and materials, shorter run-time, and higher throughput than CLG-MON. Therefore, a bridging study was conducted to support the replacement of method CLG-MON with OMA 2011.24 for regulatory use. Using fortified bovine tissue samples, CLG-MON yielded accuracies of 80-120% in 44 of the 56 samples tested (one sample had no result, six samples had accuracies of >120%, and five samples had accuracies of 40-160%), but the semiquantitative nature of CLG-MON prevented assessment of precision, whereas OMA 2011.24 had accuracies of 88-110% and RSDr of 0.00-15.6%. Incurred residue results corroborated these results, demonstrating improved accuracy (83.3-114%) and good precision (RSDr of 2.6-20.5%) for OMA 2011.24 compared with CLG-MON (accuracy generally within 80-150%, with exceptions). Furthermore, χ2 analysis revealed no statistically significant difference between the two methods. Thus, the microbiological activity of monensin correlated with the determination of monensin A in bovine tissues, and OMA 2011.24 provided improved accuracy and precision over CLG-MON.

Closing gaps for performing a risk assessment on Listeria monocytogenes in ready‐to‐eat (RTE) foods: activity 2, a quantitative risk characterization on L. monocytogenes in RTE foods; starting from the retail stage

EFSA Supporting PublicationsVolume 14, Issue 7 1252E External scientific reportOpen Access Closing gaps for performing a risk assessment on Listeria monocytogenes in ready-to-eat (RTE) foods: activity 2, a quantitative risk characterization on L. monocytogenes in RTE foods; starting from the retail stage Fernando Pérez-Rodríguez, Fernando Pérez-Rodríguez Departamento de Bromatología y Tecnología de los Alimentos, University of Cordoba (UCO), Córdoba, SpainSearch for more papers by this authorElena Carrasco, Elena Carrasco Departamento de Bromatología y Tecnología de los Alimentos, University of Cordoba (UCO), Córdoba, SpainSearch for more papers by this authorSara Bover-Cid, Sara Bover-Cid Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Food Safety Programme, Monells, SpainSearch for more papers by this authorAnna Jofré, Anna Jofré Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Food Safety Programme, Monells, SpainSearch for more papers by this authorAntonio Valero, Antonio Valero Departamento de Bromatología y Tecnología de los Alimentos, University of Cordoba (UCO), Córdoba, SpainSearch for more papers by this author Fernando Pérez-Rodríguez, Fernando Pérez-Rodríguez Departamento de Bromatología y Tecnología de los Alimentos, University of Cordoba (UCO), Córdoba, SpainSearch for more papers by this authorElena Carrasco, Elena Carrasco Departamento de Bromatología y Tecnología de los Alimentos, University of Cordoba (UCO), Córdoba, SpainSearch for more papers by this authorSara Bover-Cid, Sara Bover-Cid Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Food Safety Programme, Monells, SpainSearch for more papers by this authorAnna Jofré, Anna Jofré Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Food Safety Programme, Monells, SpainSearch for more papers by this authorAntonio Valero, Antonio Valero Departamento de Bromatología y Tecnología de los Alimentos, University of Cordoba (UCO), Córdoba, SpainSearch for more papers by this author First published: 13 July 2017 https://doi.org/10.2903/sp.efsa.2017.EN-1252Citations: 14 Requestor: European Food Safety Authority Question number: EFSA-Q-2014-00025 Disclaimer: The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors. AboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. 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Food safety recall effects across meat products and regions

Food safety is one of the key issues for the international meat market. As a major meat exporter, few things facing the U.S. meat industry in recent years have garnered more attention than food safety events and policies. The impacts of Food Safety Inspection Services (FSIS) recalls on United States consumer meat demand are estimated using monthly grocery-scanner data identifying effects across products, geographic regions, and recall type. Results suggest beef E. coli recalls significantly reduce the demand for recalled ground beef contemporaneously among most, but not all, regions in the United States. Evidence of heterogeneity in demand impacts across regions and products is provided for the first time. Domestic and international implications for policy makers, industry leaders, and researchers are discussed.

Comparison of Listeria monocytogenes recoveries from spiked mung bean sprouts by the enrichment methods of three regulatory agencies

Three selective enrichment methods, the United States Food and Drug Administration's (FDA method), the United States Department of Agriculture Food Safety Inspection Service's (USDA method), and the EN ISO 11290-1 standard method, were assessed for their suitability for recovery of Listeria monocytogenes from spiked mung bean sprouts. Three parameters were evaluated; the enrichment L. monocytogenes population from singly-spiked sprouts, the enrichment L. monocytogenes population from doubly-spiked (L. monocytogenes and Listeria innocua) sprouts, and the population differential resulting from the enrichment of doubly-spiked sprouts. Considerable L. monocytogenes inter-strain variation was observed. The mean enrichment L. monocytogenes populations for singly-spiked sprouts were 6.1 ± 1.2, 4.9 ± 1.2, and 6.9 ± 2.3 log CFU/mL for the FDA, USDA, and EN ISO 11290-1 methods, respectively. The mean L. monocytogenes populations for doubly-spiked sprouts were 4.7 ± 1.1, 5.5 ± 1.3, and 4.6 ± 1.4 log CFU/mL for the FDA, USDA, and ISO 11290–1 enrichment methods, respectively. The corresponding mean population differentials were 2.8 ± 1.1, 3.3 ± 1.3, and 3.6 ± 1.4 Δlog CFU/mL for the same three enrichment methods, respectively. The presence of L. innocua and resident microorganisms on the sprouts negatively impacted final levels of L. monocytogenes with all three enrichment methods.

Evaluation of the 3M™ Molecular Detection Assay (MDA) 2 - Listeria monocytogenes for the Detection of Listeria monocytogenes in a Variety of Foods and Select Environmental Surfaces: Collaborative Study, First Action 2016.08.

The 3M™ Molecular Detection Assay (MDA) 2 - Listeria monocytogenes uses loop-mediated isothermal amplification of unique DNA target sequences combined with bioluminescence to rapidly detect Listeria monocytogenes in a broad range of food types and on environmental surfaces. Using an unpaired study design, technicians from 13 laboratories located in the United States and Canada compared the 3M MDA 2 - Listeria monocytogenes to the U.S. Department of Agriculture Food Safety Inspection Service Microbiology Laboratory Guidebook Chapter 8.09 "Isolation and Identification of Listeria monocytogenes from Red Meat, Poultry, and Egg Products, and Environmental Samples" reference method for the detection of L. monocytogenes in deli turkey and raw chicken breast fillet. Each matrix was evaluated at three levels of contamination: an uninoculated control level (0 CFU/test portion), a low inoculum level (0.2-2 CFU/test portion), and a high inoculum level (2-5 CFU/test portion). Statistical analysis was conducted according to the probability of detection (POD) statistical model. Results obtained for the low inoculum level test portions produced a difference in the collaborating laboratory POD (dLPOD) value of 0.04 with a 95% confidence interval of (-0.08, 0.17) for deli turkey, indicating that the difference between methods was not statistically significant at the 0.05 probability level. For raw chicken breast fillet, a dLPOD value of 0.16 with a 95% confidence interval of (0.04, 0.28) indicated a statistically significant difference, with an observed higher proportion of positive results by the candidate method compared to the reference method.