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Using farm management practices to predict Campylobacter prevalence in pastured poultry farms

Contamination of poultry products by Campylobacter is often associated with farm management practices and processing plant practices. A longitudinal study was conducted on 11 pastured poultry farms in southeastern United States from 2014 to 2017. In this study, farm practices and processing variable...

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Autores principales: Xu, Xinran, Rothrock, Michael J., Mohan, Anand, Kumar, Govindaraj Dev, Mishra, Abhinav
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8131732/
https://www.ncbi.nlm.nih.gov/pubmed/33975043
http://dx.doi.org/10.1016/j.psj.2021.101122
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author Xu, Xinran
Rothrock, Michael J.
Mohan, Anand
Kumar, Govindaraj Dev
Mishra, Abhinav
author_facet Xu, Xinran
Rothrock, Michael J.
Mohan, Anand
Kumar, Govindaraj Dev
Mishra, Abhinav
author_sort Xu, Xinran
collection PubMed
description Contamination of poultry products by Campylobacter is often associated with farm management practices and processing plant practices. A longitudinal study was conducted on 11 pastured poultry farms in southeastern United States from 2014 to 2017. In this study, farm practices and processing variables were used as predictors for a random forest (RF) model to predict Campylobacter prevalence in pastured poultry farms and processing environments. Individual RF models were constructed for fecal, soil and whole carcass rinse after processing (WCR-P) samples. The performance of models was evaluated by the area under curve (AUC) from the receiver operating characteristics curve. The AUC values were 0.902, 0.894, and 0.864 for fecal, soil, and WCR-P models, respectively. Relative importance plots were generated to predict the most important variable in each RF model. Animal source of feces was identified as the most important variable in fecal model and the soy content of the brood feed was the most important variable for soil model. For WCR-P model, the average flock age showed the strongest impact on RF model. These RF models can help pastured poultry growers with food safety control strategies to reduce Campylobacter prevalence in pastured poultry farms.
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spelling pubmed-81317322021-05-21 Using farm management practices to predict Campylobacter prevalence in pastured poultry farms Xu, Xinran Rothrock, Michael J. Mohan, Anand Kumar, Govindaraj Dev Mishra, Abhinav Poult Sci MICROBIOLOGY AND FOOD SAFETY Contamination of poultry products by Campylobacter is often associated with farm management practices and processing plant practices. A longitudinal study was conducted on 11 pastured poultry farms in southeastern United States from 2014 to 2017. In this study, farm practices and processing variables were used as predictors for a random forest (RF) model to predict Campylobacter prevalence in pastured poultry farms and processing environments. Individual RF models were constructed for fecal, soil and whole carcass rinse after processing (WCR-P) samples. The performance of models was evaluated by the area under curve (AUC) from the receiver operating characteristics curve. The AUC values were 0.902, 0.894, and 0.864 for fecal, soil, and WCR-P models, respectively. Relative importance plots were generated to predict the most important variable in each RF model. Animal source of feces was identified as the most important variable in fecal model and the soy content of the brood feed was the most important variable for soil model. For WCR-P model, the average flock age showed the strongest impact on RF model. These RF models can help pastured poultry growers with food safety control strategies to reduce Campylobacter prevalence in pastured poultry farms. Elsevier 2021-03-11 /pmc/articles/PMC8131732/ /pubmed/33975043 http://dx.doi.org/10.1016/j.psj.2021.101122 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle MICROBIOLOGY AND FOOD SAFETY
Xu, Xinran
Rothrock, Michael J.
Mohan, Anand
Kumar, Govindaraj Dev
Mishra, Abhinav
Using farm management practices to predict Campylobacter prevalence in pastured poultry farms
title Using farm management practices to predict Campylobacter prevalence in pastured poultry farms
title_full Using farm management practices to predict Campylobacter prevalence in pastured poultry farms
title_fullStr Using farm management practices to predict Campylobacter prevalence in pastured poultry farms
title_full_unstemmed Using farm management practices to predict Campylobacter prevalence in pastured poultry farms
title_short Using farm management practices to predict Campylobacter prevalence in pastured poultry farms
title_sort using farm management practices to predict campylobacter prevalence in pastured poultry farms
topic MICROBIOLOGY AND FOOD SAFETY
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8131732/
https://www.ncbi.nlm.nih.gov/pubmed/33975043
http://dx.doi.org/10.1016/j.psj.2021.101122
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