1
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Benefo EO, Karanth S, Pradhan AK. A machine learning approach to identifying Salmonella stress response genes in isolates from poultry processing. Food Res Int 2024; 175:113635. [PMID: 38128977 DOI: 10.1016/j.foodres.2023.113635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 10/21/2023] [Accepted: 10/24/2023] [Indexed: 12/23/2023]
Abstract
We explored the potential of machine learning to identify significant genes associated with Salmonella stress response during poultry processing using whole genome sequencing (WGS) data. The Salmonella isolates (n = 177) used in this study were obtained from various chicken sources (skin before chiller, chicken carcass before chiller, frozen chicken, and post-chill chicken carcass). Six machine learning algorithms (random forest, neural network, cost-sensitive learning, logit boost, and support vector machine linear and radial kernels) were trained on Salmonella WGS data, and model fit was assessed using standard evaluation metrics such as the area under the receiver operating characteristic (AUROC) curve and confusion matrix statistics. All models achieved high performances based on the AUROC metric, with logit boost showing the best performance with an AUROC score of 0.904, sensitivity of 0.889, and specificity of 0.920. The significant genes identified included ybtX, which encodes a Yersiniabactin-associated zinc transporter, and the transferase-encoding genes yccK and thiS. Additionally, genes coding for cold (cspA, cspD, and cspE) and heat shock (rpoH and rpoE) responses were identified. Other significant genes included those involved in lipopolysaccharide biosynthesis (irp1, waaD, rfc, and rfbX), DNA repair and replication (traI), biofilm formation (ccdA and fyuA), and cellular metabolism (irtA).
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Affiliation(s)
- Edmund O Benefo
- Department of Nutrition and Food Science, University of Maryland, College Park, MD 20742, USA
| | - Shraddha Karanth
- Department of Nutrition and Food Science, University of Maryland, College Park, MD 20742, USA
| | - Abani K Pradhan
- Department of Nutrition and Food Science, University of Maryland, College Park, MD 20742, USA; Center for Food Safety and Security Systems, University of Maryland, College Park, MD 20742, USA.
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2
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Gonzales-Barron U, Cadavez V, Guillier L, Sanaa M. A Critical Review of Risk Assessment Models for Listeria monocytogenes in Dairy Products. Foods 2023; 12:4436. [PMID: 38137240 PMCID: PMC10742501 DOI: 10.3390/foods12244436] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 12/06/2023] [Accepted: 12/09/2023] [Indexed: 12/24/2023] Open
Abstract
A review of the published quantitative risk assessment (QRA) models of L. monocytogenes in dairy products was undertaken in order to identify and appraise the relative effectiveness of control measures and intervention strategies implemented at primary production, processing, retail, and consumer practices. A systematic literature search retrieved 18 QRA models, most of them (9) investigated raw and pasteurized milk cheeses, with the majority covering long supply chains (4 farm-to-table and 3 processing-to-table scopes). On-farm contamination sources, either from shedding animals or from the broad environment, have been demonstrated by different QRA models to impact the risk of listeriosis, in particular for raw milk cheeses. Through scenarios and sensitivity analysis, QRA models demonstrated the importance of the modeled growth rate and lag phase duration and showed that the risk contribution of consumers' practices is greater than in retail conditions. Storage temperature was proven to be more determinant of the final risk than storage time. Despite the pathogen's known ability to reside in damp spots or niches, re-contamination and/or cross-contamination were modeled in only two QRA studies. Future QRA models in dairy products should entail the full farm-to-table scope, should represent cross-contamination and the use of novel technologies, and should estimate L. monocytogenes growth more accurately by means of better-informed kinetic parameters and realistic time-temperature trajectories.
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Affiliation(s)
- Ursula Gonzales-Barron
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal;
- Laboratório Para a Sustentabilidade e Tecnologia em Regiões de Montanha, Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - Vasco Cadavez
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal;
- Laboratório Para a Sustentabilidade e Tecnologia em Regiões de Montanha, Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - Laurent Guillier
- Risk Assessment Department, French Agency for Food, Environmental and Occupational Health & Safety (Anses), 14 Rue Pierre et Marie Curie Maisons-Alfort, 94701 Maisons-Alfort, France
| | - Moez Sanaa
- Nutrition and Food Safety Department, World Health Organization (WHO), CH-1211 Geneva, Switzerland
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Brinch ML, Hald T, Wainaina L, Merlotti A, Remondini D, Henri C, Njage PMK. Comparison of Source Attribution Methodologies for Human Campylobacteriosis. Pathogens 2023; 12:786. [PMID: 37375476 DOI: 10.3390/pathogens12060786] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/09/2023] [Accepted: 05/10/2023] [Indexed: 06/29/2023] Open
Abstract
Campylobacter spp. are the most common cause of bacterial gastrointestinal infection in humans both in Denmark and worldwide. Studies have found microbial subtyping to be a powerful tool for source attribution, but comparisons of different methodologies are limited. In this study, we compare three source attribution approaches (Machine Learning, Network Analysis, and Bayesian modeling) using three types of whole genome sequences (WGS) data inputs (cgMLST, 5-Mers and 7-Mers). We predicted and compared the sources of human campylobacteriosis cases in Denmark. Using 7mer as an input feature provided the best model performance. The network analysis algorithm had a CSC value of 78.99% and an F1-score value of 67%, while the machine-learning algorithm showed the highest accuracy (98%). The models attributed between 965 and all of the 1224 human cases to a source (network applying 5mer and machine learning applying 7mer, respectively). Chicken from Denmark was the primary source of human campylobacteriosis with an average percentage probability of attribution of 45.8% to 65.4%, representing Bayesian with 7mer and machine learning with cgMLST, respectively. Our results indicate that the different source attribution methodologies based on WGS have great potential for the surveillance and source tracking of Campylobacter. The results of such models may support decision makers to prioritize and target interventions.
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Affiliation(s)
- Maja Lykke Brinch
- Research Group for Foodborne Pathogens and Epidemiology, National Food Institute, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Tine Hald
- Research Group for Foodborne Pathogens and Epidemiology, National Food Institute, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Lynda Wainaina
- Department of Mathematics, University of Padova, 35121 Padova, Italy
| | - Alessandra Merlotti
- Department of Physics and Astronomy, University of Bologna, 40126 Bologna, Italy
| | - Daniel Remondini
- Department of Physics and Astronomy, University of Bologna, 40126 Bologna, Italy
| | - Clementine Henri
- Research Group for Foodborne Pathogens and Epidemiology, National Food Institute, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Patrick Murigu Kamau Njage
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
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Wang J, Yang Z, Lu P, Sun Y, Xue S, Tang X, Xiao H. Effects of UV-B radiation on epiphytic bacterial communities on male and female Sargassum thunbergii. Sci Rep 2023; 13:3985. [PMID: 36894683 PMCID: PMC9998616 DOI: 10.1038/s41598-022-26494-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 12/15/2022] [Indexed: 03/11/2023] Open
Abstract
The effects of increased UV-B radiation on macroalgae have been widely studied, but knowledge concerning the response of communities of algal epiphytic bacteria to increased UV-B radiation and differences between male and female algae is still lacking. Via 16S rDNA high-throughput sequencing technology, changes in the epiphytic bacterial communities on male and female S. thunbergii under increased UV-B radiation were studied in the lab. Under different UV-B radiation intensities, although the α diversity and community composition of epiphytic bacteria changed little, the β diversity indicated that the community structure of bacteria on S. thunbergii was obviously clustered, and the relative abundance of dominant bacteria and indicator species changed considerably. There were unique bacteria in each experimental group, and the bacteria whose abundance obviously changed were members of groups related to environmental resistance or adaptability. The variation in the abundance of epiphytic bacteria was different in male and female S. thunbergii, and the bacteria whose abundance greatly changed were mainly related to algal growth and metabolism. The abundance of genes with predicted functions related to metabolism, genetic information processing, environmental adaptation and infectious diseases changed with increased UV-B radiation, and those variations differed between epiphytic bacteria on male and female S. thunbergii. This study found that the algal epiphytic bacteria were influenced by the increase in UV-B radiation and underwent certain adaptations through adjustments to community structure and function, and this response was also affected by the sex of the macroalgae. These results are expected to serve as experimental basis and provide reference for further understanding of the response of algae epiphytic bacteria to enhanced UV-B radiation caused by the thinning of the ozone layer and the resulting changes in the relationship between algae and bacteria, which may change the community of the marine ecosystem and affect important marine ecological process.
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Affiliation(s)
- Jing Wang
- College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Zhibo Yang
- College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Peiyao Lu
- College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Yan Sun
- College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Song Xue
- College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Xuexi Tang
- College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China.
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266000, China.
| | - Hui Xiao
- College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China.
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266000, China.
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Lakicevic B, Jankovic V, Pietzka A, Ruppitsch W. Wholegenome sequencing as the gold standard approach for control of Listeria monocytogenes in the food chain. J Food Prot 2023; 86:100003. [PMID: 36916580 DOI: 10.1016/j.jfp.2022.10.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 10/05/2022] [Accepted: 10/19/2022] [Indexed: 12/23/2022]
Abstract
Listeria monocytogenes has been implicated in numerous outbreaks and related deaths of listeriosis. In food production, L. monocytogenes occurs in raw food material and above all, through postprocessing contamination. The use of next-generation sequencing technologies such as whole-genome sequencing (WGS) facilitates foodborne outbreak investigations, pathogen source tracking and tracing geographic distributions of different clonal complexes, routine microbiological/epidemiological surveillance of listeriosis, and quantitative microbial risk assessment. WGS can also be used to predict various genetic traits related to virulence, stress, or antimicrobial resistance, which can be of great benefit for improving food safety management as well as public health.
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Affiliation(s)
- Brankica Lakicevic
- Department for Microbiological and Molecular-biological Testing, Institute of Meat Hygiene and Technology, Belgrade, Serbia.
| | - Vesna Jankovic
- Department for Microbiological and Molecular-biological Testing, Institute of Meat Hygiene and Technology, Belgrade, Serbia
| | - Ariane Pietzka
- Institute of Medical Microbiology and Hygiene/National Reference Laboratory for Listeria Division for Public Health, Austrian Agency for Health and Food Safety, Graz, Austria
| | - Werner Ruppitsch
- Institute of Medical Microbiology and Hygiene Division for Public Health, Austrian Agency for Health and Food Safety, Vienna, Austria
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6
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Deciphering the virulence potential of Listeria monocytogenes in the Norwegian meat and salmon processing industry by combining whole genome sequencing and in vitro data. Int J Food Microbiol 2022; 383:109962. [DOI: 10.1016/j.ijfoodmicro.2022.109962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 09/28/2022] [Accepted: 09/29/2022] [Indexed: 11/05/2022]
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7
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Godínez-Oviedo A, Sampedro F, Bowman JP, Garcés-Vega FJ, Hernández-Iturriaga M. Genotypic and phenotypic quantitative microbial risk assessment model of human salmonellosis related to the consumption of chicken meat in the central region of Mexico. Food Res Int 2022; 162:111901. [DOI: 10.1016/j.foodres.2022.111901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 08/29/2022] [Accepted: 09/01/2022] [Indexed: 11/04/2022]
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8
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Applications of Advanced Data Analytic Techniques in Food Safety and Risk Assessment. Curr Opin Food Sci 2022. [DOI: 10.1016/j.cofs.2022.100937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Guillier L, Palma F, Fritsch L. Taking account of genomics in quantitative microbial risk assessment: what methods? what issues? Curr Opin Food Sci 2022. [DOI: 10.1016/j.cofs.2022.100922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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10
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Wainaina L, Merlotti A, Remondini D, Henri C, Hald T, Njage PMK. Source Attribution of Human Campylobacteriosis Using Whole-Genome Sequencing Data and Network Analysis. Pathogens 2022; 11:645. [PMID: 35745499 PMCID: PMC9229307 DOI: 10.3390/pathogens11060645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/26/2022] [Accepted: 05/28/2022] [Indexed: 02/04/2023] Open
Abstract
Campylobacter spp. are a leading and increasing cause of gastrointestinal infections worldwide. Source attribution, which apportions human infection cases to different animal species and food reservoirs, has been instrumental in control- and evidence-based intervention efforts. The rapid increase in whole-genome sequencing data provides an opportunity for higher-resolution source attribution models. Important challenges, including the high dimension and complex structure of WGS data, have inspired concerted research efforts to develop new models. We propose network analysis models as an accurate, high-resolution source attribution approach for the sources of human campylobacteriosis. A weighted network analysis approach was used in this study for source attribution comparing different WGS data inputs. The compared model inputs consisted of cgMLST and wgMLST distance matrices from 717 human and 717 animal isolates from cattle, chickens, dogs, ducks, pigs and turkeys. SNP distance matrices from 720 human and 720 animal isolates were also used. The data were collected from 2015 to 2017 in Denmark, with the animal sources consisting of domestic and imports from 7 European countries. Clusters consisted of network nodes representing respective genomes and links representing distances between genomes. Based on the results, animal sources were the main driving factor for cluster formation, followed by type of species and sampling year. The coherence source clustering (CSC) values based on animal sources were 78%, 81% and 78% for cgMLST, wgMLST and SNP, respectively. The CSC values based on Campylobacter species were 78%, 79% and 69% for cgMLST, wgMLST and SNP, respectively. Including human isolates in the network resulted in 88%, 77% and 88% of the total human isolates being clustered with the different animal sources for cgMLST, wgMLST and SNP, respectively. Between 12% and 23% of human isolates were not attributed to any animal source. Most of the human genomes were attributed to chickens from Denmark, with an average attribution percentage of 52.8%, 52.2% and 51.2% for cgMLST, wgMLST and SNP distance matrices respectively, while ducks from Denmark showed the least attribution of 0% for all three distance matrices. The best-performing model was the one using wgMLST distance matrix as input data, which had a CSC value of 81%. Results from our study show that the weighted network-based approach for source attribution is reliable and can be used as an alternative method for source attribution considering the high performance of the model. The model is also robust across the different Campylobacter species, animal sources and WGS data types used as input.
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Affiliation(s)
- Lynda Wainaina
- Department of Mathematics, University of Padova, 35121 Padova, Italy;
| | - Alessandra Merlotti
- Department of Physics and Astronomy, University of Bologna, 40126 Bologna, Italy; (A.M.); (D.R.)
| | - Daniel Remondini
- Department of Physics and Astronomy, University of Bologna, 40126 Bologna, Italy; (A.M.); (D.R.)
| | - Clementine Henri
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark;
| | - Tine Hald
- Research Group for Foodborne Pathogens and Epidemiology, National Food Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark;
| | - Patrick Murigu Kamau Njage
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark;
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11
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Lakicevic BZ, Den Besten HMW, De Biase D. Landscape of Stress Response and Virulence Genes Among Listeria monocytogenes Strains. Front Microbiol 2022; 12:738470. [PMID: 35126322 PMCID: PMC8811131 DOI: 10.3389/fmicb.2021.738470] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 11/30/2021] [Indexed: 12/23/2022] Open
Abstract
The pathogenic microorganism Listeria monocytogenes is ubiquitous and responsible for listeriosis, a disease with a high mortality rate in susceptible people. It can persist in different habitats, including the farm environment, the food production environments, and in foods. This pathogen can grow under challenging conditions, such as low pH, low temperatures, and high salt concentrations. However, L. monocytogenes has a high degree of strain divergence regarding virulence potential, environmental adaption, and stress response. This review seeks to provide the reader with an up-to-date overview of clonal and serotype-specific differences among L. monocytogenes strains. Emphasis on the genes and genomic islands responsible for virulence and resistance to environmental stresses is given to explain the complex adaptation among L. monocytogenes strains. Moreover, we highlight the use of advanced diagnostic technologies, such as whole-genome sequencing, to fine-tune quantitative microbiological risk assessment for better control of listeriosis.
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Affiliation(s)
- Brankica Z. Lakicevic
- Institute of Meat Hygiene and Technology, Belgrade, Serbia
- *Correspondence: Brankica Z. Lakicevic,
| | | | - Daniela De Biase
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome, Latina, Italy
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Bourdichon F, Betts R, Dufour C, Fanning S, Farber J, McClure P, Stavropoulou DA, Wemmenhove E, Zwietering MH, Winkler A. Processing environment monitoring in low moisture food production facilities: Are we looking for the right microorganisms? Int J Food Microbiol 2021; 356:109351. [PMID: 34500287 DOI: 10.1016/j.ijfoodmicro.2021.109351] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 07/16/2021] [Accepted: 07/28/2021] [Indexed: 11/27/2022]
Abstract
Processing environment monitoring is gaining increasing importance in the context of food safety management plans/HACCP programs, since past outbreaks have shown the relevance of the environment as contamination pathway, therefore requiring to ensure the safety of products. However, there are still many open questions and a lack of clarity on how to set up a meaningful program, which would provide early warnings of potential product contamination. Therefore, the current paper aims to summarize and evaluate existing scientific information on outbreaks, relevant pathogens in low moisture foods, and knowledge on indicators, including their contribution to a "clean" environment capable of limiting the spread of pathogens in dry production environments. This paper also outlines the essential elements of a processing environment monitoring program thereby supporting the design and implementation of better programs focusing on the relevant microorganisms. This guidance document is intended to help industry and regulators focus and set up targeted processing environment monitoring programs depending on their purpose, and therefore provide the essential elements needed to improve food safety.
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Affiliation(s)
- François Bourdichon
- Food Safety, Microbiology, Hygiene, 16 Rue Gaston de Caillavet, 75015 Paris, France; Facoltà di Scienze Agrarie, Alimentarie Ambientali, Università Cattolica del Sacro Cuore, Piacenza-Cremona, Italy.
| | - Roy Betts
- Campden BRI, Chipping Campden, Gloucestershire, United Kingdom
| | - Christophe Dufour
- Mérieux NutriSciences, 25 Boulevard de la Paix, 95891 Cergy Pontoise, France
| | - Séamus Fanning
- UCD - Centre for Food Safety, University College Dublin, Belfield, Dublin D04 N2E5, Ireland
| | - Jeffrey Farber
- Department of Food Science, University of Guelph, Guelph, Ontario, Canada
| | - Peter McClure
- Mondelēz International, Bournville Lane, Birmingham B30 2LU, United Kingdom
| | | | | | - Marcel H Zwietering
- Food Microbiology, Wageningen University, PO Box 17, 6700AA, Wageningen, The Netherlands
| | - Anett Winkler
- Cargill Germany GmbH, Cerestar str. 2, D-47809 Krefeld, Germany
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