Journal of food protection最新文献

The presence of Listeria monocytogenes in the dairy environment remains a food safety challenge. The source of microbial contamination may include employees and their personal protective equipment (PPE). This study investigated the effectiveness of cleaning protocols (i.e., detergents and mechanical action) and three chemical sanitizers commonly employed at dairy facilities against Listeria innocua contamination on different types of gloves, aprons, and boots. Coupons made of PPE material were inoculated with a two-strain cocktail of L. innocua suspended in either Phosphate Buffered Saline (PBS) or skim milk to determine the potential effect of organic matter. In general, peroxyacetic acid (0.20% (v/v)) was more effective at reducing Listeria counts on aprons and gloves compared to chlorine and quaternary ammonium at 200 ppm. Depending on the type of sanitizer, Listeria reductions ranged from 1.95 - 4.72 and 1.52 - 4.60 log CFU/in² on aprons and gloves, respectively. In comparison, sanitizers achieved a 0.93 - 2.32 log CFU/in² reduction on boot soles, with no significant differences observed among sanitizers. PVC (vinyl) gloves achieved lower Listeria log reductions than nitrile and latex gloves. Sanitizers were less effective on boots with wider and deeper lugs than those with shallow lugs. The presence of organic matter significantly reduced the antimicrobial efficacy of all sanitizers (<1 log CFU/in² reduction). However, the inclusion of cleaning protocols with and without mechanical action achieved a ≥3 log CFU/in² reduction in the different types of PPE. This study highlights the importance of scrubbing as an essential step to reduce Listeria on PPE.

Melamine, as a toxic compound, needs to be controlled in food, especially in dairy products. In this systematic study, quantities of melamine and cyanuric acid in various types of milk were investigated. A comprehensive database search was performed using the keywords pasteurized milk, milk, sterilized milk, melamine, and cyanuric acid without time limitation. A total of 24 articles related to melamine and cyanuric acid were thoroughly reviewed. The overall mean concentration of melamine in milk was estimated by meta-analysis to be 11.3 μg/L. Publication bias was not addressed in the associated assays; however, it was addressed as highly heterogeneous between studies. Subgroup analysis was carried out, and the milk type was a cause of heterogeneity. This systematic review investigated a range of melamine in milk products and discussed different analytical methods.

A Proficiency Test (PT) was conducted for Food Emergency Response Network (FERN) laboratories for quantitative assessment of Listeria monocytogenes (L. monocytogenes) in queso fresco cheese. The Moffett Proficiency Test Laboratory: MPTL (organizer) prepared test samples for each participating laboratory with 10 CFU/g of L. monocytogenes. Statistical analysis was conducted to analyze test sample preparation and evaluate the performance of the quantitative method by utilizing participant's data. Although individually inoculated, the samples were considered replicates based on the standard deviation values obtained from the Q/Hampel method. A similar observation was noted on pre- and post-shipment data, which permitted a combined analysis as per Q/Hampel and ISO 5725-2 methods. Based on the results, it can be summarized that MPTL prepared homogenized and stable samples for L. monocytogenes enumeration in cheese. The participant results indicated that the repeatability of standard deviation, which reflects the scatter of results within a laboratory (participant) was mainly driven by the MPN procedure. Out of forty reported results from twenty laboratories, 85% were satisfactory. A few laboratories reported different MPN results (2.5% unsatisfactory, and 12.5% warning) indicating lack of understanding in handling the MPN dilutions. Since BAM MPN based method performance data for L. monocytogenes is not widely available in the literature, more PT events like these can help generate quantitative data for the evaluation of the MPN method.

The safety of dairy products is intrinsically linked to consumer health, and the exceedance of risk indicators, such as pesticide and veterinary drug residues, constitutes one of the primary issues affecting their quality and safety. To assess the safety of dairy products, it is crucial to develop accurate and reliable analytical methods for their detection. Food safety testing involving important indicators such as pesticide residues, veterinary drug residues, mycotoxins and unapproved additives has become a pivotal requirement in the industry field. The QuEChERS (Quick、Easy、Cheap、Effective、Rugged、Safe) method is widely acknowledged as a food safety analysis method currently. This method can effectively extract a wide range of compound classes from diverse matrices in food safety testing, thereby enhancing the accuracy of detection. Additionally, when combined with chromatographic-mass spectrometry techniques, it can simultaneously analyze hundreds of target analytes, rendering it widely applicable in the quality and safety testing of dairy products. Although QuEChERS has rapidly developed in the field of dairy product quality and safety analysis due to its efficiency and speed advantages, certain shortcomings remain, presenting considerable room for improvement. This paper presents a comprehensive review of the utilization and research advancements of the QuEChERS technique in dairy products, with the aim of providing more precise, expeditious, and reliable methods for the safety assessment of dairy products.

Background: Ensuring food safety is a fundamental priority for public health. The catering sector has become prominent as a convenient and cost-effective method of food supply worldwide. Adherence to proper food hygiene practices is crucial for preventing foodborne diseases. The inspection of food items is a key component of internal controls that enables the identification of non-compliance with food hygiene standards. The present study aims to assess Attica restaurant businesses' compliance with international food hygiene standards (FAO/WHO Codex Alimentarius) and European legislation on unsafe food.

Methods: From January to July 2023, 74 randomly selected restaurants of small, medium, and large capacity in Attica were examined through inspections in terms of compliance for food hygiene standards. The inspections were based on (a) the completion of forms and (b) the collection of water and food samples for laboratory microbiological analysis. Data were collected using a predefined form, referencing the manual of Codex Alimentarius regarding food hygiene standards (CAC/RCP 1-1969/CAC/RCP 39-1993). Additionally, the assessment included the identification of unsafe food placement in accordance with Regulation EC/178/2002 on food safety, as well as Greek national legislation (European Commission, 2002; Hellenic Republic, 2006, 2014).

Results: The highest non-compliance rates are in "adequacy of facilities" (14.12%), "equipment maintenance and sanitization" (12.30%), "pest control" (12.45%), "personal hygiene" (7.58%), and "efficient separation of raw materials" (9.76%). Non-compliance rates for other food hygiene parameters (cooking practices, meal apportionment, storage, transport, reheating, etc.) were considerably lower. The inspection results showed that medium-sized restaurant businesses present the highest rate (56.41%) of total non-compliance compared to large-sized businesses (29.68%) and small-sized businesses (13.91%).

Conclusions: This study demonstrates that restaurant businesses generally adhere to food hygiene and safety standards at a satisfactory level. There is a need for restaurant operators to prioritize enhancing compliance, particularly in addressing critical issues that could potentially result in outbreaks of foodborne diseases.

Overly broad recalls following an FDA advisory occur when the source of an outbreak is originally misidentified or cannot be promptly identified. In this situation, an entire product category might be recalled (e.g., romaine lettuce), such that the recall extends to uncontaminated product lots, imposing spillover costs on entities that would otherwise be unaffected. There are, however, very few published studies that estimate the potential magnitude of these spillover costs. Using a formal structured elicitation methodology, this study develops expert estimates of the spillover costs firms typically incur in responding to an overly broad recall following an FDA product advisory. We find that the range of costs varies widely by type and size of firm, with producers incurring median costs per recall ranging from $3.0 million to $72.7 million per firm, shippers/distributors from $0.1 million to $2.3 million per firm, restaurants from $0.04 million to $1.1 million per firm, and nonrestaurant retailers from $0.1 million to $3.1 million per firm. The results of this study can help inform food policy discussions geared toward assessing the benefits of traceability in terms of avoided costs of overly broad food recalls. Industry is often reluctant to provide estimates on the costs of recalls. This study fills that void by estimating the per-firm costs incurred by food supply chain entities due to overly broad recalls.

Antibiotics are extensively used in layer flocks for the prevention of diseases and to enhance their growth and production. However, their nonprudent use is leading to the occurrence of residues in eggs. The present study aimed at the detection of tetracycline group residues in egg samples collected from layer farms located in Haryana, India, and human health risk assessment. A total of 100 pooled egg samples were analyzed using High-Performance Liquid Chromatography with Ultraviolet detector for the detection of tetracycline group residues. Out of 100 pooled samples, 13 (13%) were found to be contaminated with tetracycline residues (12 for chlortetracycline and one for tetracycline). Of these, five (38.5%) samples (one for tetracycline and four for chlortetracycline) exceeded the maximum residue limit (MRL) established by Food Safety and Standards Authority of India. The risk assessment based on the per capita availability of eggs in Haryana revealed that the current levels of residues in eggs pose no significant toxicological effects on the consumer's health. The residues exceeding MRL indicate nonprudent use of antibiotics in veterinary practices, which could lead to the emergence of antibiotic resistance. There is a need to generate awareness among farmers toward judicious antibiotic usage in layer birds and adherence to withdrawal periods to prevent the escalating problem of antibiotic resistance.

This study aims to validate sanitation standard operating procedures (SSOPs) of the precooling system in two immersion stages with different temperatures followed by dripping for 3 min. The variables evaluated were temperature, weight, microbiological quality, and safety of chicken carcasses. Groups of indicator microorganisms were quantified and the occurrence of Salmonella spp., Listeria monocytogenes, diarrheagenic Escherichia coli (non-157), and Staphylococcus aureus with enterotoxigenic potential was investigated, before and after cooling by immersion and dripping. Salmonella serovars were determined by real-time PCR. Immersion of the carcasses in water at 9.5 (±2.89) and 2.33 (±1.30) °C in the first and second stages was sufficient to considerably reduce the carcass temperature to 5.70 and 7.41 °C at the system outlet and after dripping, respectively. The weight gain was 5.5%, in accordance with Brazilian legislation (<8%). Immersion cooling significantly reduced (p < 0.05) the total counts of enterobacteria, total coliforms, and E. coli. Contamination was reduced in the carcasses, which increased the water counts in the system to 3.76 log CFU/mL for psychrotrophs. Salmonella spp. was identified in 100% of the carcasses evaluated and in the water from the first and second stages of cooling. The main serovars were S. Newport and S. Minnesota. Pathotypes of diarrheagenic E. coli, mainly atypical EPEC and STEC, and S. aureus with enterotoxigenic potential were highly prevalent in the carcasses even before entering the precooling systems by immersion, which was not sufficient to rule out the occurrence of any pathogen studied. Despite the notable SSOP effect on the quantification of microbiological indicators during immersion cooling, the high occurrence of different pathogens underlies the need to review procedures and techniques not only in slaughterhouses but also throughout the production chain, acting in an integrated manner to provide biosecurity and reduce risks to the consumption of chicken meat.

S. enterica isolates (n = 78) obtained from the vegetable supply chain (farms, distribution centers, markets) in two Cambodian provinces (Siem Reap, Battambang) were sequenced and analyzed. In silico identification of serotypes and detection of antimicrobial resistance genes was performed using SISTR and ABRicate, respectively. Isolates' relatedness was assessed based on high-quality single nucleotide polymorphisms (hqSNPs) identified within each serotype using the CFSAN SNP pipeline. Among 29 detected serotypes, Paratyphi B var. Java was most abundant (n = 14), followed by Hvittingfoss (n = 11) and Thompson (n = 7). Paratyphi B var. Java was mostly found in farms (n = 5) and markets (n = 6), Hvittingfoss within distribution centers (n = 8), and Thompson at markets (n = 4) and farms (n = 3). Among Paratyphi B var. Java isolates, one phylogenetic clade contained four closely related isolates (0-1 SNP difference), collected at markets in different provinces on different days. Another clade contained two isolates that differed by one SNP, one obtained from a Battambang farm and one from a Siem Reap distribution center, suggesting a broad spread of Paratyphi B var. Java in the Cambodian vegetable supply chain. Hvittingfoss isolates clustered in two clades; one contained five identical isolates, four of which were obtained in different months from the distribution center and a farm in Battambang, suggesting possible transmission among supply chain stages. The second clade contained three isolates from the Battambang distribution center that differed by 0-1 SNP and were isolated in October and November, indicating possible persistence. Lastly, among 78 analyzed isolates, 14 carried antimicrobial resistance genes and seven out of these 14 carried genes with predicted resistance to more than three classes of antibiotics. Overall, highly similar isolates of Salmonella were identified over time and at different supply chain stages, suggesting possible persistence and transmission of Salmonella within and between supply chain stages.

Models that predict bacterial growth in food products can help industry with decision-making with regard to microbial food spoilage. Such models have recently been developed using machine learning (ML) rather than a mechanistic understanding of bacterial growth. Thus, our aim was to compare the performance of mechanistic (M) models and the Gaussian process (GP) model (i.e., an ML approach) for predicting bacterial growth on spinach from a US-based supply chain as well as a China-based supply chain; models were developed using previously published data, as well as new data collected in this study from the China-based supply chain. For the packaged spinach collected in this study from the China-based supply chain, the mean net growth of aerobic, mesophilic bacteria over 10 days of shelf life was 1.16 log₁₀ (n = 11, local distribution) and 1.29 log₁₀ (n = 8, eCommerce distribution); bacterial growth on spinach did not differ significantly by distribution channel. The data obtained in this study, as well as previously published data on the growth of (i) individual bacterial strains (i.e., strain-level growth) and (ii) the overall bacterial population on baby spinach (i.e., population-level growth), were used to fit models. Specifically, GP models were fit to population-level growth data only, while M models were fit to strain-level and population-level growth data. The RMSE values for the M models (i.e., 0.72, 0.77 and 1.09 log₁₀ CFU/g, for three M models assessed here) and GP models (i.e., 0.68 and 0.81 log₁₀ CFU/g, for the two GP models assessed here) are similar, which suggests that both M and GP models show comparable accuracy at predicting bacterial growth on spinach.