Modelling‐based identification of factors influencing campylobacters in chicken broiler houses and on carcasses sampled after processing and chilling
Aims To identify production and processing practices that might reduce Campylobacter numbers contaminating chicken broiler carcasses. Methods and Results The numbers of campylobacters were determined on carcass neck skins after processing or in broiler house litter samples. Supplementary information...
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| Veröffentlicht in: | Journal of applied microbiology 2017-05, Vol.122 (5), p.1389-1401 |
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| creator | Hutchison, M.L. Taylor, M.J. Tchòrzewska, M.A. Ford, G. Madden, R.H. Knowles, T.G. |
| description | Aims
To identify production and processing practices that might reduce Campylobacter numbers contaminating chicken broiler carcasses.
Methods and Results
The numbers of campylobacters were determined on carcass neck skins after processing or in broiler house litter samples. Supplementary information that described farm layouts, farming conditions for individual flocks, the slaughterhouse layouts and operating conditions inside plants was collected, matched with each Campylobacter test result. Statistical models predicting the numbers of campylobacters on neck skins and in litter were constructed. Carcass microbial contamination was more strongly influenced by on‐farm production practices compared with slaughterhouse activities. We observed correlations between the chilling, washing and defeathering stages of processing and the numbers of campylobacters on carcasses. There were factors on farm that also correlated with numbers of campylobacters in litter. These included bird gender, the exclusion of dogs from houses, beetle presence in the house litter and the materials used to construct the house frame.
Conclusions
Changes in farming practices have greater potential for reducing chicken carcass microbial contamination compared with processing interventions.
Significance and Impact of the Study
Routine commercial practices were identified that were correlated with lowered numbers of campylobacters. Consequently, these practices are likely to be both cost‐effective and suitable for adoption into established farms and commercial processing. |
| doi_str_mv | 10.1111/jam.13434 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1891886418</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2058885781</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4494-8069b3656230b9bf309bf3075d02a40cd54087e2a464206f816e5ac5b8ad6bb93</originalsourceid><addsrcrecordid>eNqNkc9uFSEUxonR2Fpd-AKGxI0upgUGGGbZNNY_aeNG1wQYsFxn4Ap3Yu7OR-jO9_NJPDO3ujDRyAJO4He-cw4fQk8pOaWwzjZmOqUtb_k9dExbKRomO3Z_jXkjSMeO0KNaN4TQlgj5EB0xxYSSTByj79d58OMY06cf326tqX7AcfBpF0N0ZhdzwjngYNwul4pjCuPskwMaOzNt92O28OTXJ-xuovvsE7Ylx9EXfJPn6is2acAg40xxpi4XFTJHqGMCZOJtyc7XukguJIis3TxGD4IZq39yd56gj5evPly8aa7ev357cX7VOM573igiewsTS9YS29vQknXrxECY4cQNghPVeYglZ0QGRaUXxgmrzCCt7dsT9OKgC318mX3d6SlWBz9ikof-NVU9VUpyqv4D7TjnQpEO0Od_oJs8lwSDaEaEUkp0iv6LWmqyvuv7pcOXB8qVXGvxQW9LnEzZa0r0Yr8G-_VqP7DP7hRnO_nhN_nLbwDODsBXsGj_dyX97vz6IPkTJa67Eg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1886297999</pqid></control><display><type>article</type><title>Modelling‐based identification of factors influencing campylobacters in chicken broiler houses and on carcasses sampled after processing and chilling</title><source>Oxford University Press Journals All Titles (1996-Current)</source><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Hutchison, M.L. ; Taylor, M.J. ; Tchòrzewska, M.A. ; Ford, G. ; Madden, R.H. ; Knowles, T.G.</creator><creatorcontrib>Hutchison, M.L. ; Taylor, M.J. ; Tchòrzewska, M.A. ; Ford, G. ; Madden, R.H. ; Knowles, T.G.</creatorcontrib><description>Aims
To identify production and processing practices that might reduce Campylobacter numbers contaminating chicken broiler carcasses.
Methods and Results
The numbers of campylobacters were determined on carcass neck skins after processing or in broiler house litter samples. Supplementary information that described farm layouts, farming conditions for individual flocks, the slaughterhouse layouts and operating conditions inside plants was collected, matched with each Campylobacter test result. Statistical models predicting the numbers of campylobacters on neck skins and in litter were constructed. Carcass microbial contamination was more strongly influenced by on‐farm production practices compared with slaughterhouse activities. We observed correlations between the chilling, washing and defeathering stages of processing and the numbers of campylobacters on carcasses. There were factors on farm that also correlated with numbers of campylobacters in litter. These included bird gender, the exclusion of dogs from houses, beetle presence in the house litter and the materials used to construct the house frame.
Conclusions
Changes in farming practices have greater potential for reducing chicken carcass microbial contamination compared with processing interventions.
Significance and Impact of the Study
Routine commercial practices were identified that were correlated with lowered numbers of campylobacters. Consequently, these practices are likely to be both cost‐effective and suitable for adoption into established farms and commercial processing.</description><identifier>ISSN: 1364-5072</identifier><identifier>EISSN: 1365-2672</identifier><identifier>DOI: 10.1111/jam.13434</identifier><identifier>PMID: 28258625</identifier><identifier>CODEN: JAMIFK</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Abattoirs ; Abattoirs - standards ; Agricultural economics ; Agricultural practices ; agriculture ; Animals ; Bacterial infections ; Campylobacter ; Campylobacter - classification ; Campylobacter - genetics ; Campylobacter - isolation & purification ; Campylobacter Infections - microbiology ; Campylobacter Infections - veterinary ; campylobacters ; Carcasses ; Chickens ; Chilling ; Colony Count, Microbial ; Construction materials ; Contamination ; Cooling ; Dogs ; Farming ; Farms ; Food Contamination - analysis ; Food Microbiology ; Houses ; Intensive farming ; Internal layout ; Litter ; Mathematical models ; Meat - microbiology ; Microbial contamination ; Microbiology ; Microorganisms ; modelling ; Neck ; Poultry ; Poultry Diseases - microbiology ; Poultry housing ; processing ; Skin ; Statistical analysis ; Statistical methods ; Statistical models</subject><ispartof>Journal of applied microbiology, 2017-05, Vol.122 (5), p.1389-1401</ispartof><rights>2017 The Authors. published by John Wiley & Sons Ltd on behalf of Society for Applied Microbiology.</rights><rights>2017 The Authors. Journal of Applied Microbiology published by John Wiley & Sons Ltd on behalf of Society for Applied Microbiology.</rights><rights>Copyright © 2017 The Society for Applied Microbiology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4494-8069b3656230b9bf309bf3075d02a40cd54087e2a464206f816e5ac5b8ad6bb93</citedby><cites>FETCH-LOGICAL-c4494-8069b3656230b9bf309bf3075d02a40cd54087e2a464206f816e5ac5b8ad6bb93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fjam.13434$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fjam.13434$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28258625$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hutchison, M.L.</creatorcontrib><creatorcontrib>Taylor, M.J.</creatorcontrib><creatorcontrib>Tchòrzewska, M.A.</creatorcontrib><creatorcontrib>Ford, G.</creatorcontrib><creatorcontrib>Madden, R.H.</creatorcontrib><creatorcontrib>Knowles, T.G.</creatorcontrib><title>Modelling‐based identification of factors influencing campylobacters in chicken broiler houses and on carcasses sampled after processing and chilling</title><title>Journal of applied microbiology</title><addtitle>J Appl Microbiol</addtitle><description>Aims
To identify production and processing practices that might reduce Campylobacter numbers contaminating chicken broiler carcasses.
Methods and Results
The numbers of campylobacters were determined on carcass neck skins after processing or in broiler house litter samples. Supplementary information that described farm layouts, farming conditions for individual flocks, the slaughterhouse layouts and operating conditions inside plants was collected, matched with each Campylobacter test result. Statistical models predicting the numbers of campylobacters on neck skins and in litter were constructed. Carcass microbial contamination was more strongly influenced by on‐farm production practices compared with slaughterhouse activities. We observed correlations between the chilling, washing and defeathering stages of processing and the numbers of campylobacters on carcasses. There were factors on farm that also correlated with numbers of campylobacters in litter. These included bird gender, the exclusion of dogs from houses, beetle presence in the house litter and the materials used to construct the house frame.
Conclusions
Changes in farming practices have greater potential for reducing chicken carcass microbial contamination compared with processing interventions.
Significance and Impact of the Study
Routine commercial practices were identified that were correlated with lowered numbers of campylobacters. Consequently, these practices are likely to be both cost‐effective and suitable for adoption into established farms and commercial processing.</description><subject>Abattoirs</subject><subject>Abattoirs - standards</subject><subject>Agricultural economics</subject><subject>Agricultural practices</subject><subject>agriculture</subject><subject>Animals</subject><subject>Bacterial infections</subject><subject>Campylobacter</subject><subject>Campylobacter - classification</subject><subject>Campylobacter - genetics</subject><subject>Campylobacter - isolation & purification</subject><subject>Campylobacter Infections - microbiology</subject><subject>Campylobacter Infections - veterinary</subject><subject>campylobacters</subject><subject>Carcasses</subject><subject>Chickens</subject><subject>Chilling</subject><subject>Colony Count, Microbial</subject><subject>Construction materials</subject><subject>Contamination</subject><subject>Cooling</subject><subject>Dogs</subject><subject>Farming</subject><subject>Farms</subject><subject>Food Contamination - analysis</subject><subject>Food Microbiology</subject><subject>Houses</subject><subject>Intensive farming</subject><subject>Internal layout</subject><subject>Litter</subject><subject>Mathematical models</subject><subject>Meat - microbiology</subject><subject>Microbial contamination</subject><subject>Microbiology</subject><subject>Microorganisms</subject><subject>modelling</subject><subject>Neck</subject><subject>Poultry</subject><subject>Poultry Diseases - microbiology</subject><subject>Poultry housing</subject><subject>processing</subject><subject>Skin</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Statistical models</subject><issn>1364-5072</issn><issn>1365-2672</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>EIF</sourceid><recordid>eNqNkc9uFSEUxonR2Fpd-AKGxI0upgUGGGbZNNY_aeNG1wQYsFxn4Ap3Yu7OR-jO9_NJPDO3ujDRyAJO4He-cw4fQk8pOaWwzjZmOqUtb_k9dExbKRomO3Z_jXkjSMeO0KNaN4TQlgj5EB0xxYSSTByj79d58OMY06cf326tqX7AcfBpF0N0ZhdzwjngYNwul4pjCuPskwMaOzNt92O28OTXJ-xuovvsE7Ylx9EXfJPn6is2acAg40xxpi4XFTJHqGMCZOJtyc7XukguJIis3TxGD4IZq39yd56gj5evPly8aa7ev357cX7VOM573igiewsTS9YS29vQknXrxECY4cQNghPVeYglZ0QGRaUXxgmrzCCt7dsT9OKgC318mX3d6SlWBz9ikof-NVU9VUpyqv4D7TjnQpEO0Od_oJs8lwSDaEaEUkp0iv6LWmqyvuv7pcOXB8qVXGvxQW9LnEzZa0r0Yr8G-_VqP7DP7hRnO_nhN_nLbwDODsBXsGj_dyX97vz6IPkTJa67Eg</recordid><startdate>201705</startdate><enddate>201705</enddate><creator>Hutchison, M.L.</creator><creator>Taylor, M.J.</creator><creator>Tchòrzewska, M.A.</creator><creator>Ford, G.</creator><creator>Madden, R.H.</creator><creator>Knowles, T.G.</creator><general>Oxford University Press</general><scope>24P</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7QO</scope><scope>7T7</scope><scope>7TM</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>201705</creationdate><title>Modelling‐based identification of factors influencing campylobacters in chicken broiler houses and on carcasses sampled after processing and chilling</title><author>Hutchison, M.L. ; Taylor, M.J. ; Tchòrzewska, M.A. ; Ford, G. ; Madden, R.H. ; Knowles, T.G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4494-8069b3656230b9bf309bf3075d02a40cd54087e2a464206f816e5ac5b8ad6bb93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Abattoirs</topic><topic>Abattoirs - standards</topic><topic>Agricultural economics</topic><topic>Agricultural practices</topic><topic>agriculture</topic><topic>Animals</topic><topic>Bacterial infections</topic><topic>Campylobacter</topic><topic>Campylobacter - classification</topic><topic>Campylobacter - genetics</topic><topic>Campylobacter - isolation & purification</topic><topic>Campylobacter Infections - microbiology</topic><topic>Campylobacter Infections - veterinary</topic><topic>campylobacters</topic><topic>Carcasses</topic><topic>Chickens</topic><topic>Chilling</topic><topic>Colony Count, Microbial</topic><topic>Construction materials</topic><topic>Contamination</topic><topic>Cooling</topic><topic>Dogs</topic><topic>Farming</topic><topic>Farms</topic><topic>Food Contamination - analysis</topic><topic>Food Microbiology</topic><topic>Houses</topic><topic>Intensive farming</topic><topic>Internal layout</topic><topic>Litter</topic><topic>Mathematical models</topic><topic>Meat - microbiology</topic><topic>Microbial contamination</topic><topic>Microbiology</topic><topic>Microorganisms</topic><topic>modelling</topic><topic>Neck</topic><topic>Poultry</topic><topic>Poultry Diseases - microbiology</topic><topic>Poultry housing</topic><topic>processing</topic><topic>Skin</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Statistical models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hutchison, M.L.</creatorcontrib><creatorcontrib>Taylor, M.J.</creatorcontrib><creatorcontrib>Tchòrzewska, M.A.</creatorcontrib><creatorcontrib>Ford, G.</creatorcontrib><creatorcontrib>Madden, R.H.</creatorcontrib><creatorcontrib>Knowles, T.G.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of applied microbiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hutchison, M.L.</au><au>Taylor, M.J.</au><au>Tchòrzewska, M.A.</au><au>Ford, G.</au><au>Madden, R.H.</au><au>Knowles, T.G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modelling‐based identification of factors influencing campylobacters in chicken broiler houses and on carcasses sampled after processing and chilling</atitle><jtitle>Journal of applied microbiology</jtitle><addtitle>J Appl Microbiol</addtitle><date>2017-05</date><risdate>2017</risdate><volume>122</volume><issue>5</issue><spage>1389</spage><epage>1401</epage><pages>1389-1401</pages><issn>1364-5072</issn><eissn>1365-2672</eissn><coden>JAMIFK</coden><abstract>Aims
To identify production and processing practices that might reduce Campylobacter numbers contaminating chicken broiler carcasses.
Methods and Results
The numbers of campylobacters were determined on carcass neck skins after processing or in broiler house litter samples. Supplementary information that described farm layouts, farming conditions for individual flocks, the slaughterhouse layouts and operating conditions inside plants was collected, matched with each Campylobacter test result. Statistical models predicting the numbers of campylobacters on neck skins and in litter were constructed. Carcass microbial contamination was more strongly influenced by on‐farm production practices compared with slaughterhouse activities. We observed correlations between the chilling, washing and defeathering stages of processing and the numbers of campylobacters on carcasses. There were factors on farm that also correlated with numbers of campylobacters in litter. These included bird gender, the exclusion of dogs from houses, beetle presence in the house litter and the materials used to construct the house frame.
Conclusions
Changes in farming practices have greater potential for reducing chicken carcass microbial contamination compared with processing interventions.
Significance and Impact of the Study
Routine commercial practices were identified that were correlated with lowered numbers of campylobacters. Consequently, these practices are likely to be both cost‐effective and suitable for adoption into established farms and commercial processing.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>28258625</pmid><doi>10.1111/jam.13434</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of applied microbiology, 2017-05, Vol.122 (5), p.1389-1401 |
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| source | Oxford University Press Journals All Titles (1996-Current); MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Abattoirs Abattoirs - standards Agricultural economics Agricultural practices agriculture Animals Bacterial infections Campylobacter Campylobacter - classification Campylobacter - genetics Campylobacter - isolation & purification Campylobacter Infections - microbiology Campylobacter Infections - veterinary campylobacters Carcasses Chickens Chilling Colony Count, Microbial Construction materials Contamination Cooling Dogs Farming Farms Food Contamination - analysis Food Microbiology Houses Intensive farming Internal layout Litter Mathematical models Meat - microbiology Microbial contamination Microbiology Microorganisms modelling Neck Poultry Poultry Diseases - microbiology Poultry housing processing Skin Statistical analysis Statistical methods Statistical models |
| title | Modelling‐based identification of factors influencing campylobacters in chicken broiler houses and on carcasses sampled after processing and chilling |
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