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Koutsoumanis K, Allende A, Bolton D, Bover‐Cid S, Chemaly M, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Nonno R, Peixe L, Ru G, Simmons M, Skandamis P, Suffredini E, Fox E, Gosling R(B, Gil BM, Møretrø T, Stessl B, da Silva Felício MT, Messens W, Simon AC, Alvarez‐Ordóñez A. Persistence of microbiological hazards in food and feed production and processing environments. EFSA J 2024; 22:e8521. [PMID: 38250499 PMCID: PMC10797485 DOI: 10.2903/j.efsa.2024.8521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024] Open
Abstract
Listeria monocytogenes (in the meat, fish and seafood, dairy and fruit and vegetable sectors), Salmonella enterica (in the feed, meat, egg and low moisture food sectors) and Cronobacter sakazakii (in the low moisture food sector) were identified as the bacterial food safety hazards most relevant to public health that are associated with persistence in the food and feed processing environment (FFPE). There is a wide range of subtypes of these hazards involved in persistence in the FFPE. While some specific subtypes are more commonly reported as persistent, it is currently not possible to identify universal markers (i.e. genetic determinants) for this trait. Common risk factors for persistence in the FFPE are inadequate zoning and hygiene barriers; lack of hygienic design of equipment and machines; and inadequate cleaning and disinfection. A well-designed environmental sampling and testing programme is the most effective strategy to identify contamination sources and detect potentially persistent hazards. The establishment of hygienic barriers and measures within the food safety management system, during implementation of hazard analysis and critical control points, is key to prevent and/or control bacterial persistence in the FFPE. Once persistence is suspected in a plant, a 'seek-and-destroy' approach is frequently recommended, including intensified monitoring, the introduction of control measures and the continuation of the intensified monitoring. Successful actions triggered by persistence of L. monocytogenes are described, as well as interventions with direct bactericidal activity. These interventions could be efficient if properly validated, correctly applied and verified under industrial conditions. Perspectives are provided for performing a risk assessment for relevant combinations of hazard and food sector to assess the relative public health risk that can be associated with persistence, based on bottom-up and top-down approaches. Knowledge gaps related to bacterial food safety hazards associated with persistence in the FFPE and priorities for future research are provided.
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Quantitative Bio-Mapping of Salmonella and Indicator Organisms at Different Stages in a Commercial Pork Processing Facility. Foods 2022; 11:foods11172580. [PMID: 36076766 PMCID: PMC9455759 DOI: 10.3390/foods11172580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 08/20/2022] [Accepted: 08/24/2022] [Indexed: 11/29/2022] Open
Abstract
The purpose of this study was to develop a quantitative baseline of indicator organisms and Salmonella by bio-mapping throughout the processing chain from harvest to final product stages within a commercial conventional design pork processing establishment. Swab samples were taken on the harvest floor at different processing steps, gambrel table, after polisher, before final rinse, after the final rinse, post snap chill, and after peroxyacetic acid (PAA) application, while 2-pound product samples were collected for trim and ground samples. The samples were subjected to analysis for indicator microorganism enumeration, Aerobic Count (AC), Enterobacteriaceae (EB), and generic Escherichia coli (EC), with the BioMérieux TEMPO®. Salmonella prevalence and enumeration was evaluated using the BAX® System Real-Time Salmonella and the SalQuant™ methodology. Microbial counts were converted to Log Colony-forming units (CFU) on a per mL, per g or per sample basis, presented as LogCFU/mL, LogCFU/g and LogCFU/sample, prior to statistical analysis. All indicator microorganisms were significantly reduced at the harvest floor (p-value < 0.001), from gambrel table to after PAA cabinet location. The reduction at harvest was 2.27, 2.46 and 2.24 LogCFU/mL for AC, EB and EC, respectively. Trim sample values fluctuated based on cut, with the highest average AC count found at neck trim (2.83 LogCFU/g). Further process samples showed the highest AC count in sausage with a mean of 5.28 LogCFU/g. EB counts in sausage (3.19 LogCFU/g) showed an evident increase, compared to the reduction observed at the end of harvest and throughout trim processing. EC counts showed a similar trend to EB counts with the highest value found in sausage links (1.60 LogCFU/g). Statistical microbial process control (SPC) parameters were also developed for each of the indicator microorganisms, using the overall mean count (X=), the Lower control limit (LCL) and Upper control limit (UCL) at each sampling location. For Salmonella prevalence, a total of 125/650 samples were found positive (19%). From those positive samples, 47 samples (38%) were suitable for enumeration using the BAX® System SalQuant™, the majority detected at the gambrel table location. From those enumerable samples, 60% were estimated to be between 0.97 and 1.97 LogCFU/sample, while the rest (40%) were higher within the 2.00−4.02 LogCFU/sample range. This study provides evidence for the application of indicator and pathogen quantification methodologies for food safety management in commercial pork processing operations.
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Hdaifeh A, Khalid T, Boué G, Cummins E, Guillou S, Federighi M, Tesson V. Critical Analysis of Pork QMRA Focusing on Slaughterhouses: Lessons from the Past and Future Trends. Foods 2020; 9:E1704. [PMID: 33233782 PMCID: PMC7699970 DOI: 10.3390/foods9111704] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/09/2020] [Accepted: 11/18/2020] [Indexed: 01/27/2023] Open
Abstract
Foodborne microbial diseases have a significant impact on public health, leading to millions of human illnesses each year worldwide. Pork is one of the most consumed meat in Europe but may also be a major source of pathogens introduced all along the farm-to-fork chain. Several quantitative microbial risk assessment (QMRA) have been developed to assess human health risks associated with pork consumption and to evaluate the efficiency of different risk reduction strategies. The present critical analysis aims to review pork QMRA. An exhaustive search was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. It resulted in identification of a collection of 2489 papers including 42 on QMRA, after screening. Among them, a total of 29 studies focused on Salmonella spp. with clear concern on impacts at the slaughterhouse, modeling the spreading of contaminations and growth at critical stages along with potential reductions. Along with strict compliance with good hygiene practices, several potential risk mitigation pathways were highlighted for each slaughterhouse step. The slaughterhouse has a key role to play to ensure food safety of pork-based products but consideration of the whole farm-to-fork chain is necessary to enable better control of bacteria. This review provides an analysis of pork meat QMRA, to facilitate their reuse, and identify gaps to guide future research activities.
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Affiliation(s)
- Ammar Hdaifeh
- INRAE, Oniris, SECALIM, 44307 Nantes, France; (A.H.); (T.K.); (G.B.); (S.G.); (V.T.)
| | - Tahreem Khalid
- INRAE, Oniris, SECALIM, 44307 Nantes, France; (A.H.); (T.K.); (G.B.); (S.G.); (V.T.)
| | - Géraldine Boué
- INRAE, Oniris, SECALIM, 44307 Nantes, France; (A.H.); (T.K.); (G.B.); (S.G.); (V.T.)
| | - Enda Cummins
- Biosystems and Food Engineering, University College Dublin, Dublin 4 Belfield, Ireland;
| | - Sandrine Guillou
- INRAE, Oniris, SECALIM, 44307 Nantes, France; (A.H.); (T.K.); (G.B.); (S.G.); (V.T.)
| | - Michel Federighi
- INRAE, Oniris, SECALIM, 44307 Nantes, France; (A.H.); (T.K.); (G.B.); (S.G.); (V.T.)
| | - Vincent Tesson
- INRAE, Oniris, SECALIM, 44307 Nantes, France; (A.H.); (T.K.); (G.B.); (S.G.); (V.T.)
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Qi Y, He Y, Beuchat LR, Zhang W, Deng X. Glove-mediated transfer of Listeria monocytogenes on fresh-cut cantaloupe. Food Microbiol 2020; 88:103396. [DOI: 10.1016/j.fm.2019.103396] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 08/06/2019] [Accepted: 11/25/2019] [Indexed: 11/29/2022]
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5
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Quantitative transfer and sanitizer inactivation of Salmonella during simulated commercial dicing and conveying of tomatoes. Food Control 2020. [DOI: 10.1016/j.foodcont.2019.106762] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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An ordinal logistic regression approach to predict the variability on biofilm formation stages by five Salmonella enterica strains on polypropylene and glass surfaces as affected by pH, temperature and NaCl. Food Microbiol 2019; 83:95-103. [PMID: 31202424 DOI: 10.1016/j.fm.2019.04.012] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2019] [Revised: 03/31/2019] [Accepted: 04/25/2019] [Indexed: 12/29/2022]
Abstract
This study assessed the adhesion and formation of biofilm by five Salmonella enterica strains (S. Enteritidis 132, S. Infantis 176, S. Typhimurium 177, S. Heidelberg 281 and S. Corvallis 297) on polypropylene (PP) and glass (G) surfaces as affected by pH (4-7), NaCl concentration (0-10% w/v) and temperature (8-35 °C). Sessile counts <3 log CFU/cm2 were considered lack of adhesion (category 1), while counts ≥ 3 and < 5 log CFU/cm2 corresponded to adhesion (category 2) and counts ≥ 5 log CFU/cm2 corresponded biofilm formation (category 3). The obtained results categorized in these three responses were used to develop ordinal regression models to predict the probability of biofilm stages on PP- and G-surfaces. The experimental outcomes for lack of adhesion were >90% on PP- and G-surfaces. Generally, adhesion outcomes corresponded to approximately 36% of the total, whereas biofilm outcomes were close to 65% in both PP- and G-surfaces. The biofilm stages varied among the strains studied and with the material surface under the same experimental conditions. According to the generated ordinal models, the probability of adhesion and biofilm formation on PP-surface by the five S. enterica strains tested decreased at pH 4 or 5 in NaCl concentrations >4% and at a temperature <20 °C. On G-surface, the probability of adhesion increased pH 6 or 7, in the absence of NaCl and temperatures <20 °C, while, the probability of biofilm formation increased in the same pH, NaCl concentration up to 4% and temperatures ≥20 °C. This is the first study assessing the biofilm formation through categorical, ordinal responses and it shows that ordinal regression models can be useful to predict biofilm stages of S. enterica as a function of pH, NaCl, and temperature or their interactions.
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Jiang R, Wang X, Wang W, Liu Y, Du J, Cui Y, Zhang C, Dong Q. Modelling the cross-contamination of Listeria monocytogenes
in pork during bowl chopping. Int J Food Sci Technol 2017. [DOI: 10.1111/ijfs.13660] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ronghua Jiang
- School of Medical Instrument and Food Engineering; University of Shanghai for Science and Technology; 516 Jun Gong Rd. Shanghai 200093 China
| | - Xiang Wang
- School of Medical Instrument and Food Engineering; University of Shanghai for Science and Technology; 516 Jun Gong Rd. Shanghai 200093 China
| | - Wen Wang
- Hangzhou Center for Risk Assessment for Agricultural Products; Ministry of Agriculture; Hangzhou 310021 China
- Institute of Quality Standards for Agricultural Products; Zhejiang Academy of Agricultural Sciences; Hangzhou 310021 China
| | - Yangtai Liu
- School of Medical Instrument and Food Engineering; University of Shanghai for Science and Technology; 516 Jun Gong Rd. Shanghai 200093 China
| | - Jianping Du
- Beijing Municipal Center for Food Safety Monitoring and Risk Assessment; Beijing 100053 China
| | - Yang Cui
- Beijing Municipal Center for Food Safety Monitoring and Risk Assessment; Beijing 100053 China
| | - Chunyan Zhang
- Beijing Municipal Center for Food Safety Monitoring and Risk Assessment; Beijing 100053 China
| | - Qingli Dong
- School of Medical Instrument and Food Engineering; University of Shanghai for Science and Technology; 516 Jun Gong Rd. Shanghai 200093 China
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de Freitas Costa E, Corbellini LG, da Silva APSP, Nauta M. A Stochastic Model to Assess the Effect of Meat Inspection Practices on the Contamination of the Pig Carcasses. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2017; 37:1849-1864. [PMID: 27996166 DOI: 10.1111/risa.12753] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Revised: 10/04/2016] [Accepted: 11/07/2016] [Indexed: 06/06/2023]
Abstract
The objective of meat inspection is to promote animal and public health by preventing, detecting, and controlling hazards originating from animals. With the improvements of sanitary level in pig herds, the hazards profile has shifted and the inspection procedures no longer target major foodborne pathogens (i.e., not risk based). Additionally, carcass manipulations performed when searching for macroscopic lesions can lead to cross-contamination. We therefore developed a stochastic model to quantitatively describe cross-contamination when consecutive carcasses are submitted to classic inspection procedures. The microbial hazard used to illustrate the model was Salmonella, the data set was obtained from Brazilian slaughterhouses, and some simplifying assumptions were made. The model predicted that due to cross-contamination during inspection, the prevalence of contaminated carcass surfaces increased from 1.2% to 95.7%, whereas the mean contamination on contaminated surfaces decreased from 1 logCFU/cm² to -0.87 logCFU/cm², and the standard deviations decreased from 0.65 to 0.19. These results are explained by the fact that, due to carcass manipulations with hands, knives, and hooks, including the cutting of contaminated lymph nodes, Salmonella is transferred to previously uncontaminated carcasses, but in small quantities. These small quantities can easily go undetected during sampling. Sensitivity analyses gave insight into the model performance and showed that the touching and cutting of lymph nodes during inspection can be an important source of carcass contamination. The model can serve as a tool to support discussions on the modernization of pig carcass inspection.
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Affiliation(s)
- Eduardo de Freitas Costa
- Laboratory of Veterinary Epidemiology (Epilab), Department of Preventive Veterinary Medicine, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Luis Gustavo Corbellini
- Laboratory of Veterinary Epidemiology (Epilab), Department of Preventive Veterinary Medicine, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Ana Paula Serafini Poeta da Silva
- Laboratory of Veterinary Epidemiology (Epilab), Department of Preventive Veterinary Medicine, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Maarten Nauta
- Technical University of Denmark - National Food Institute, Søborg, Denmark
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Possas A, Carrasco E, García-Gimeno R, Valero A. Models of microbial cross-contamination dynamics. Curr Opin Food Sci 2017. [DOI: 10.1016/j.cofs.2017.01.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
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10
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Rajan K, Shi Z, Ricke SC. Current aspects ofSalmonellacontamination in the US poultry production chain and the potential application of risk strategies in understanding emerging hazards. Crit Rev Microbiol 2016; 43:370-392. [DOI: 10.1080/1040841x.2016.1223600] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Kalavathy Rajan
- Center for Food Safety, Department of Food Science, University of Arkansas, Fayetteville, AR, USA
| | - Zhaohao Shi
- Center for Food Safety, Department of Food Science, University of Arkansas, Fayetteville, AR, USA
| | - Steven C. Ricke
- Center for Food Safety, Department of Food Science, University of Arkansas, Fayetteville, AR, USA
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Wang H, Ryser ET. Quantitative transfer of Salmonella Typhimurium LT2 during mechanical slicing of tomatoes as impacted by multiple processing variables. Int J Food Microbiol 2016; 234:76-82. [DOI: 10.1016/j.ijfoodmicro.2016.06.035] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2015] [Revised: 05/30/2016] [Accepted: 06/25/2016] [Indexed: 10/21/2022]
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12
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Possas AMM, Posada-Izquierdo GD, Pérez-Rodríguez F, García-Gimeno RM. Modeling the Transfer ofSalmonellaEnteritidis during Slicing of Ready-to-Eat Turkey Products Treated with Thyme Essential Oil. J Food Sci 2016; 81:M2770-M2775. [DOI: 10.1111/1750-3841.13506] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Revised: 07/29/2016] [Accepted: 08/25/2016] [Indexed: 11/27/2022]
Affiliation(s)
- Arícia M. M. Possas
- Dept. of Food Science and Technology, Intl. Campus of Excellence in the AgriFood Sector (CeiA3); Univ. of Córdoba; C-1 14014 Córdoba Spain
| | - Guiomar D. Posada-Izquierdo
- Dept. of Food Science and Technology, Intl. Campus of Excellence in the AgriFood Sector (CeiA3); Univ. of Córdoba; C-1 14014 Córdoba Spain
| | - Fernando Pérez-Rodríguez
- Dept. of Food Science and Technology, Intl. Campus of Excellence in the AgriFood Sector (CeiA3); Univ. of Córdoba; C-1 14014 Córdoba Spain
| | - Rosa M. García-Gimeno
- Dept. of Food Science and Technology, Intl. Campus of Excellence in the AgriFood Sector (CeiA3); Univ. of Córdoba; C-1 14014 Córdoba Spain
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Evaluation of a cross contamination model describing transfer of Salmonella spp. and Listeria monocytogenes during grinding of pork and beef. Int J Food Microbiol 2016; 226:42-52. [DOI: 10.1016/j.ijfoodmicro.2016.03.016] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2015] [Revised: 12/14/2015] [Accepted: 03/13/2016] [Indexed: 11/19/2022]
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14
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Seliwiorstow T, Baré J, Van Damme I, Gisbert Algaba I, Uyttendaele M, De Zutter L. Transfer of Campylobacter from a Positive Batch to Broiler Carcasses of a Subsequently Slaughtered Negative Batch: A Quantitative Approach. J Food Prot 2016; 79:896-901. [PMID: 27296592 DOI: 10.4315/0362-028x.jfp-15-486] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The present study was conducted to quantify Campylobacter cross-contamination from a positive batch of broiler chicken carcasses to a negative batch at selected processing steps and to evaluate the duration of this cross-contamination. During each of nine visits conducted in three broiler slaughterhouses, Campylobacter levels were determined on broiler carcasses originating from Campylobacter-negative batches processed immediately after Campylobacter-positive batches. Data were collected after four steps during the slaughter process (scalding, plucking, evisceration, and washing) at 1, 10, and 20 min after the start of the slaughter of the batches. Campylobacter levels in ceca of birds from Campylobacter-positive batches ranged from 5.62 to 9.82 log CFU/g. When the preceding positive batch was colonized at a low level, no (enumerable) carcass contamination was found in a subsequent negative batch. However, when Campylobacter levels were high in the positive batch, Campylobacter was found on carcasses of the subsequent negative batch but at levels significantly lower than those found on carcasses from the preceding positive batch. The scalding and the evisceration process contributed the least (< 1.5 log CFU/g) and the most (up to 4 log CFU/ g), respectively, to the Campylobacter transmission from a positive batch to a negative batch. Additionally, the number of Campylobacter cells transferred from positive to negative batches decreased over the first 20 min of sampling time. However, the reduction was slower than previously estimated in risk assessment studies, suggesting that pathogen transfer during crosscontamination is a complex process.
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Affiliation(s)
- Tomasz Seliwiorstow
- Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium; Department of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium.
| | - Julie Baré
- Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium; Unit of Orientation and Veterinary Support, Centrum voor Onderzoek in Diergeneeskunde en Agrochemie, Centre d'Etude et de Recherches Vétérinaires et Agrochimiques, Groeselenberg 99, 1180 Ukkel, Belgium
| | - Inge Van Damme
- Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium
| | - Ignacio Gisbert Algaba
- Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium; Communicable and Infectious Diseases, Scientific Institute of Public Health, Rue Engelandstraat 642, 1180 Brussels, Belgium
| | - Mieke Uyttendaele
- Department of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium
| | - Lieven De Zutter
- Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium
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Zilelidou EA, Tsourou V, Poimenidou S, Loukou A, Skandamis PN. Modeling transfer of Escherichia coli O157:H7 and Listeria monocytogenes during preparation of fresh-cut salads: impact of cutting and shredding practices. Food Microbiol 2015; 45:254-65. [PMID: 25500391 DOI: 10.1016/j.fm.2014.06.019] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2014] [Revised: 06/15/2014] [Accepted: 06/18/2014] [Indexed: 11/16/2022]
Abstract
Cutting and shredding of leafy vegetables increases the risk of cross contamination in household settings. The distribution of Escherichia coli O157:H7 and Listeria monocytogenes transfer rates (Tr) between cutting knives and lettuce leaves was investigated and a semi-mechanistic model describing the bacterial transfer during consecutive cuts of leafy vegetables was developed. For both pathogens the distribution of log10Trs from lettuce to knife was towards low values. Conversely log10Trs from knife to lettuce ranged from -2.1 to -0.1 for E. coli O157:H7 and -2.0 to 0 for L. monocytogenes, and indicated a more variable phenomenon. Regarding consecutive cuts, a rapid initial transfer was followed by an asymptotic tail at low populations moving to lettuce or residing on knife. E. coli O157:H7 was transferred at slower rates than L. monocytogenes. These trends were sufficiently described by the transfer-model, with RMSE values of 0.426-0.613 and 0.531-0.908 for L. monocytogenes and E. coli O157:H7, respectively. The model showed good performance in validation trials but underestimated bacterial transfer during extrapolation experiments. The results of the study can provide information regarding cross contamination events in a common household. The constructed model could be a useful tool for the risk-assessment during preparation of leafy-green salads.
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Affiliation(s)
- Evangelia A Zilelidou
- Laboratory of Food Quality Control and Hygiene, Department of Food Science & Human Nutrition, Agricultural University of Athens, Iera Odos 75, 118 55 Athens, Greece
| | - Virginia Tsourou
- Laboratory of Food Quality Control and Hygiene, Department of Food Science & Human Nutrition, Agricultural University of Athens, Iera Odos 75, 118 55 Athens, Greece
| | - Sofia Poimenidou
- Laboratory of Food Quality Control and Hygiene, Department of Food Science & Human Nutrition, Agricultural University of Athens, Iera Odos 75, 118 55 Athens, Greece
| | - Anneza Loukou
- Laboratory of Food Quality Control and Hygiene, Department of Food Science & Human Nutrition, Agricultural University of Athens, Iera Odos 75, 118 55 Athens, Greece
| | - Panagiotis N Skandamis
- Laboratory of Food Quality Control and Hygiene, Department of Food Science & Human Nutrition, Agricultural University of Athens, Iera Odos 75, 118 55 Athens, Greece.
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Møller CODA, Nauta MJ, Schaffner DW, Dalgaard P, Christensen BB, Hansen TB. Risk assessment of Salmonella in Danish meatballs produced in the catering sector. Int J Food Microbiol 2014; 196:109-25. [PMID: 25540860 DOI: 10.1016/j.ijfoodmicro.2014.10.010] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Revised: 07/03/2014] [Accepted: 10/05/2014] [Indexed: 10/24/2022]
Abstract
A modular process risk model approach was used to assess health risks associated with Salmonella spp. after consumption of the Danish meatball product (frikadeller) produced with fresh pork in a catering unit. Meatball production and consumption were described as a series of processes (modules), starting from 1.3kg meat pieces through conversion to 70g meatballs, followed by a dose response model to assess the risk of illness from consumption of these meatballs. Changes in bacterial prevalence, concentration, and unit size were modelled within each module. The risk assessment was built using observational data and models that were specific for Salmonella spp. in meatballs produced in the catering sector. Danish meatballs are often pan-fried followed by baking in an oven before consumption, in order to reach the core temperature of 75°C recommended by the Danish Food Safety Authority. However, in practice this terminal heat treatment in the oven may be accidentally omitted. Eleven production scenarios were evaluated with the model, to test the impact of heat treatments and cooling rates at different room temperatures. The risk estimates revealed that a process comprising heat treatment of meatballs to core temperatures higher than 70°C, and subsequent holding at room temperatures lower than 20°C, for no longer than 3.5h, were very effective in Salmonella control. The current Danish Food Safety Authority recommendation of cooking to an internal temperature of 75°C is conservative, at least with respect to Salmonella risk. Survival and growth of Salmonella during cooling of meatballs not heat treated in oven had a significant impact on the risk estimates, and therefore, cooling should be considered a critical step during meatball processing.
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Affiliation(s)
- Cleide O de A Møller
- National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, DK-2860 Søborg, Denmark
| | - Maarten J Nauta
- National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, DK-2860 Søborg, Denmark
| | - Donald W Schaffner
- Department of Food Science, School of Environmental and Biological Science, Rutgers University, 65 Dudley Road, Food Science Building, Room 207, New Brunswick, NJ 08901-8520, USA
| | - Paw Dalgaard
- National Food Institute, Technical University of Denmark, Søltofts Plads, Bygning 221, DK-2800 Kgs. Lyngby, Denmark
| | - Bjarke B Christensen
- National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, DK-2860 Søborg, Denmark
| | - Tina B Hansen
- National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, DK-2860 Søborg, Denmark.
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17
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Shieh YC, Tortorello ML, Fleischman GJ, Li D, Schaffner DW. Tracking and modeling norovirus transmission during mechanical slicing of globe tomatoes. Int J Food Microbiol 2014; 180:13-8. [DOI: 10.1016/j.ijfoodmicro.2014.04.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2013] [Revised: 01/13/2014] [Accepted: 04/03/2014] [Indexed: 11/30/2022]
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Møller C, Ilg Y, Aabo S, Christensen B, Dalgaard P, Hansen T. Effect of natural microbiota on growth of Salmonella spp. in fresh pork – A predictive microbiology approach. Food Microbiol 2013; 34:284-95. [DOI: 10.1016/j.fm.2012.10.010] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2012] [Revised: 08/21/2012] [Accepted: 10/30/2012] [Indexed: 01/11/2023]
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Smid J, de Jonge R, Havelaar AH, Pielaat A. Variability and uncertainty analysis of the cross-contamination ratios of salmonella during pork cutting. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2013; 33:1100-1115. [PMID: 23078187 DOI: 10.1111/j.1539-6924.2012.01908.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
The transfer ratio of bacteria from one surface to another is often estimated from laboratory experiments and quantified by dividing the expected number of bacteria on the recipient surface by the expected number of bacteria on the donor surface. Yet, the expected number of bacteria on each surface is uncertain due to the limited number of colonies that are counted and/or samples that can be analyzed. The expected transfer ratio is, therefore, also uncertain and its estimate may exceed 1 if real transfer is close to 100%. In addition, the transferred fractions vary over experiments but it is unclear, using this approach, how to combine uncertainty and variability into one estimate for the transfer ratio. A Bayesian network model was proposed that allows the combination of uncertainty within one experiment and variability over multiple experiments and prevents inappropriate values for the transfer ratio. Model functionality was shown using data from a laboratory experiment in which the transfer of Salmonella was determined from contaminated pork meat to a butcher's knife, and vice versa. Recovery efficiency of bacteria from both surfaces was also determined and accounted for in the analysis. Transfer ratio probability distributions showed a large variability, with a mean value of 0.19 for the transfer of Salmonella from pork meat to the knife and 0.58 for the transfer of Salmonella from the knife to pork meat. The proposed Bayesian model can be used for analyzing data from similar study designs in which uncertainty should be combined with variability.
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Affiliation(s)
- Joost Smid
- Laboratory for Zoonoses and Environmental Microbiology-LZO, National Institute for Public Health and the Environment-RIVM, P.O. Box 1, 3720 BA Bilthoven, The Netherlands.
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