Monitoring of Pig Slaughter Stages and Correlation in the Prevalence of Pathogens and Levels of Microorganisms That Indicate Microbiological Quality and Hygiene Using a Predictive Model
Pig production is relevant to the Brazilian economy. Different stages of the raising and slaughtering process influence the microbiological quality of pig products and by-products. Microbiological analysis and hazard analysis and critical control points (HACCPs) are tools for monitoring microbiologi...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-01-01
|
| Series: | Journal of Food Protection |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0362028X22030150 |
| _version_ | 1797774609610702848 |
|---|---|
| author | Elton Rodrigo Cê Audecir Giombelli Jalusa Deon Kich Karla Suzana Moresco Andresa Miranda Mayka Reghiany Pedrão Gracielle Johann Andréa Cátia Leal Badaró Elisabete Hiromi Hashimoto Alessandra Machado-Lunkes |
| author_facet | Elton Rodrigo Cê Audecir Giombelli Jalusa Deon Kich Karla Suzana Moresco Andresa Miranda Mayka Reghiany Pedrão Gracielle Johann Andréa Cátia Leal Badaró Elisabete Hiromi Hashimoto Alessandra Machado-Lunkes |
| author_sort | Elton Rodrigo Cê |
| collection | DOAJ |
| description | Pig production is relevant to the Brazilian economy. Different stages of the raising and slaughtering process influence the microbiological quality of pig products and by-products. Microbiological analysis and hazard analysis and critical control points (HACCPs) are tools for monitoring microbiological quality indicator microorganisms. The construction of predictive models can assist the process of monitoring the microbiological quality of pig products. This study aimed to map the slaughter stages and develop a model to predict the absence or presence of Salmonella based on the process variables (distance from the farm to the slaughterhouse and aerobic mesophilic) and analyze their influence on contamination indicator microorganisms. A total of 810 samples were collected at nine stages of the slaughter process (bleeding, scalding, dehairing, singeing, washing, evisceration, inspection, final washing, and chilling). The binary class predictive model was used as a microbiological quality predictor at the slaughter stages. Salmonella was identified at all process stages, with lower contamination levels at the scalding and chilling stages, whereas the highest levels were found at the dehairing and bleeding stages. The predictive model revealed an accuracy of about 85% for Salmonella being a tool to monitor the microbiological quality of pig slaughter. |
| first_indexed | 2024-03-12T22:23:21Z |
| format | Article |
| id | doaj.art-511a757982c0427fa9793d349f784aed |
| institution | Directory Open Access Journal |
| issn | 0362-028X |
| language | English |
| last_indexed | 2024-03-12T22:23:21Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Food Protection |
| spelling | doaj.art-511a757982c0427fa9793d349f784aed2023-07-23T04:53:39ZengElsevierJournal of Food Protection0362-028X2023-01-01861100034Monitoring of Pig Slaughter Stages and Correlation in the Prevalence of Pathogens and Levels of Microorganisms That Indicate Microbiological Quality and Hygiene Using a Predictive ModelElton Rodrigo Cê0Audecir Giombelli1Jalusa Deon Kich2Karla Suzana Moresco3Andresa Miranda4Mayka Reghiany Pedrão5Gracielle Johann6Andréa Cátia Leal Badaró7Elisabete Hiromi Hashimoto8Alessandra Machado-Lunkes9Graduate Program of Food Technology, Federal University of Technology-Parana, Francisco Beltrão-PR, Londrina-PR, BrazilSchool of Pharmacy, Federal University of Minas Gerais, Belo Horizonte-MG, BrazilBrazilian Agricultural Research Corporation (EMBRAPA), Concórdia-SC, BrazilGraduate Program of Food Technology, Federal University of Technology-Parana, Francisco Beltrão-PR, Londrina-PR, Brazil; Federal University of Fronteira Sul, Realeza-PR, BrazilGraduate Program of Food Technology, Federal University of Technology-Parana, Francisco Beltrão-PR, Londrina-PR, BrazilGraduate Program of Food Technology, Federal University of Technology-Parana, Francisco Beltrão-PR, Londrina-PR, BrazilGraduate Program of Food Technology, Federal University of Technology-Parana, Francisco Beltrão-PR, Londrina-PR, BrazilDepartment of Agricultural Sciences, Federal University of Technology-Parana, Francisco Beltrão-PR, BrazilGraduate Program of Food Technology, Federal University of Technology-Parana, Francisco Beltrão-PR, Londrina-PR, BrazilGraduate Program of Food Technology, Federal University of Technology-Parana, Francisco Beltrão-PR, Londrina-PR, Brazil; Corresponding author.Pig production is relevant to the Brazilian economy. Different stages of the raising and slaughtering process influence the microbiological quality of pig products and by-products. Microbiological analysis and hazard analysis and critical control points (HACCPs) are tools for monitoring microbiological quality indicator microorganisms. The construction of predictive models can assist the process of monitoring the microbiological quality of pig products. This study aimed to map the slaughter stages and develop a model to predict the absence or presence of Salmonella based on the process variables (distance from the farm to the slaughterhouse and aerobic mesophilic) and analyze their influence on contamination indicator microorganisms. A total of 810 samples were collected at nine stages of the slaughter process (bleeding, scalding, dehairing, singeing, washing, evisceration, inspection, final washing, and chilling). The binary class predictive model was used as a microbiological quality predictor at the slaughter stages. Salmonella was identified at all process stages, with lower contamination levels at the scalding and chilling stages, whereas the highest levels were found at the dehairing and bleeding stages. The predictive model revealed an accuracy of about 85% for Salmonella being a tool to monitor the microbiological quality of pig slaughter.http://www.sciencedirect.com/science/article/pii/S0362028X22030150Aerobic mesophilesEnterobacteriaceaeEscherichia coliSalmonella |
| spellingShingle | Elton Rodrigo Cê Audecir Giombelli Jalusa Deon Kich Karla Suzana Moresco Andresa Miranda Mayka Reghiany Pedrão Gracielle Johann Andréa Cátia Leal Badaró Elisabete Hiromi Hashimoto Alessandra Machado-Lunkes Monitoring of Pig Slaughter Stages and Correlation in the Prevalence of Pathogens and Levels of Microorganisms That Indicate Microbiological Quality and Hygiene Using a Predictive Model Journal of Food Protection Aerobic mesophiles Enterobacteriaceae Escherichia coli Salmonella |
| title | Monitoring of Pig Slaughter Stages and Correlation in the Prevalence of Pathogens and Levels of Microorganisms That Indicate Microbiological Quality and Hygiene Using a Predictive Model |
| title_full | Monitoring of Pig Slaughter Stages and Correlation in the Prevalence of Pathogens and Levels of Microorganisms That Indicate Microbiological Quality and Hygiene Using a Predictive Model |
| title_fullStr | Monitoring of Pig Slaughter Stages and Correlation in the Prevalence of Pathogens and Levels of Microorganisms That Indicate Microbiological Quality and Hygiene Using a Predictive Model |
| title_full_unstemmed | Monitoring of Pig Slaughter Stages and Correlation in the Prevalence of Pathogens and Levels of Microorganisms That Indicate Microbiological Quality and Hygiene Using a Predictive Model |
| title_short | Monitoring of Pig Slaughter Stages and Correlation in the Prevalence of Pathogens and Levels of Microorganisms That Indicate Microbiological Quality and Hygiene Using a Predictive Model |
| title_sort | monitoring of pig slaughter stages and correlation in the prevalence of pathogens and levels of microorganisms that indicate microbiological quality and hygiene using a predictive model |
| topic | Aerobic mesophiles Enterobacteriaceae Escherichia coli Salmonella |
| url | http://www.sciencedirect.com/science/article/pii/S0362028X22030150 |
| work_keys_str_mv | AT eltonrodrigoce monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel AT audecirgiombelli monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel AT jalusadeonkich monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel AT karlasuzanamoresco monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel AT andresamiranda monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel AT maykareghianypedrao monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel AT graciellejohann monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel AT andreacatialealbadaro monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel AT elisabetehiromihashimoto monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel AT alessandramachadolunkes monitoringofpigslaughterstagesandcorrelationintheprevalenceofpathogensandlevelsofmicroorganismsthatindicatemicrobiologicalqualityandhygieneusingapredictivemodel |