The Experts below are selected from a list of 111 Experts worldwide ranked by ideXlab platform
Sue C. Tongue - One of the best experts on this subject based on the ideXlab platform.
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Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for low and high discrepancy batches, with significance levels.
2016Co-Authors: Carla Correia-gomes, Richard P. Smith, Jude I. Eze, Madeleine K. Henry, George J. Gunn, Susanna Williamson, Sue C. TongueAbstract:Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for low and high discrepancy batches, with significance levels.
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Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for each of the week field trials and all data of the field trials, with significance levels.
2016Co-Authors: Carla Correia-gomes, Richard P. Smith, Jude I. Eze, Madeleine K. Henry, George J. Gunn, Susanna Williamson, Sue C. TongueAbstract:Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for each of the week field trials and all data of the field trials, with significance levels.
Carla Correia-gomes - One of the best experts on this subject based on the ideXlab platform.
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Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for low and high discrepancy batches, with significance levels.
2016Co-Authors: Carla Correia-gomes, Richard P. Smith, Jude I. Eze, Madeleine K. Henry, George J. Gunn, Susanna Williamson, Sue C. TongueAbstract:Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for low and high discrepancy batches, with significance levels.
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Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for each of the week field trials and all data of the field trials, with significance levels.
2016Co-Authors: Carla Correia-gomes, Richard P. Smith, Jude I. Eze, Madeleine K. Henry, George J. Gunn, Susanna Williamson, Sue C. TongueAbstract:Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for each of the week field trials and all data of the field trials, with significance levels.
Ilias Kyriazakis - One of the best experts on this subject based on the ideXlab platform.
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connecting different data sources to assess the interconnections between biosecurity health welfare and performance in commercial pig farms in great britain
Frontiers in Veterinary Science, 2018Co-Authors: Fanny Pandolfi, Sandra A. Edwards, Dominiek Maes, Ilias KyriazakisAbstract:This study aimed to provide an overview of the interconnections between biosecurity, health, welfare, and performance in commercial pig farms in Great Britain. We collected on-farm data about the level of biosecurity and animal performance in 40 fattening pig farms and 28 breeding pig farms between 2015 and 2016. We identified interconnections between these data, slaughterhouse health indicators, and welfare indicator records in fattening pig farms. After achieving the connections between databases, a secondary data analysis was performed to assess the interconnections between biosecurity, health, welfare, and performance using correlation analysis, principal component analysis, and hierarchical clustering. Although we could connect the different data sources the final sample size was limited, suggesting room for improvement in database connection to conduct secondary data analyses. The farm biosecurity scores ranged from 40 to 90 out of 100, with internal biosecurity scores being lower than external biosecurity scores. Our analysis suggested several interconnections between health, welfare, and performance. The initial correlation analysis showed that the prevalence of lameness and severe tail lesions was associated with the prevalence of enzootic pneumonia-like lesions and Pyaemia, and the prevalence of severe body marks was associated with several disease indicators, including peritonitis and milk spots (r > 0.3; P 0.3; P 0.3; P < 0.05). Farms from cluster 3 had higher biosecurity, higher ADG, and lower prevalence for some disease and welfare indicators. The study suggests a smaller impact of biosecurity on issues such as mortality, prevalence of lameness, and pig requiring hospitalization. The correlations and the identified clusters suggested the importance of animal welfare for the pig industry.
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connecting different data sources to assess the interconnections between biosecurity health welfare and performance in commercial pig farms in great britain
Frontiers in Veterinary Science, 2018Co-Authors: Fanny Pandolfi, Sandra A. Edwards, Dominiek Maes, Ilias KyriazakisAbstract:This study aimed to provide an overview of the inter-connections between biosecurity, health, welfare and performance in commercial pig farms in Great Britain. We collected on-farm data about the level of biosecurity and animal performance in 40 fattening pig farms and 28 breeding pig farms between 2015 and 2016. We identified inter-connections between these data, slaughterhouse health indicators and welfare indicator records in fattening pig farms. After achieving the connections between databases, a secondary data analysis was performed to assess the inter-connections between biosecurity, health, welfare and performance using correlation analysis, principal component analysis and hierarchical clustering. Although we could connect the different data sources the final sample size was limited, suggesting room for improvement in database connection to conduct secondary data analyses. The farm biosecurity scores ranged from 40-90 out of 100, with internal biosecurity scores being lower than external biosecurity scores. Our analysis suggested several interconnections between health, welfare and performance. The initial correlation analysis showed that the prevalence of lameness and severe tail lesions was associated with the prevalence of enzootic pneumonia-like lesions and Pyaemia, and the prevalence of severe body marks was associated with several disease indicators, including peritonitis and milk spots (r>0.3; P0.3; P0.3; P<0.05). Farms from cluster 3 had higher biosecurity, higher ADG and lower prevalence for some disease and welfare indicators. The study suggests a smaller impact of biosecurity on issues like mortality, prevalence of lameness and pig requiring hospitalization. The correlations and the identified clusters suggested the importance of animal welfare for the pig industry.
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data_sheet_1.PDF
2018Co-Authors: Fanny Pandolfi, Sandra A. Edwards, Dominiek Maes, Ilias KyriazakisAbstract:This study aimed to provide an overview of the interconnections between biosecurity, health, welfare, and performance in commercial pig farms in Great Britain. We collected on-farm data about the level of biosecurity and animal performance in 40 fattening pig farms and 28 breeding pig farms between 2015 and 2016. We identified interconnections between these data, slaughterhouse health indicators, and welfare indicator records in fattening pig farms. After achieving the connections between databases, a secondary data analysis was performed to assess the interconnections between biosecurity, health, welfare, and performance using correlation analysis, principal component analysis, and hierarchical clustering. Although we could connect the different data sources the final sample size was limited, suggesting room for improvement in database connection to conduct secondary data analyses. The farm biosecurity scores ranged from 40 to 90 out of 100, with internal biosecurity scores being lower than external biosecurity scores. Our analysis suggested several interconnections between health, welfare, and performance. The initial correlation analysis showed that the prevalence of lameness and severe tail lesions was associated with the prevalence of enzootic pneumonia-like lesions and Pyaemia, and the prevalence of severe body marks was associated with several disease indicators, including peritonitis and milk spots (r > 0.3; P 0.3; P 0.3; P
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Connecting Different Data Sources to Assess the Interconnections between Biosecurity, Health, Welfare, and Performance in Commercial Pig Farms in Great Britain
Frontiers Media S.A., 2018Co-Authors: Fanny Pandolfi, Sandra A. Edwards, Dominiek Maes, Ilias KyriazakisAbstract:This study aimed to provide an overview of the interconnections between biosecurity, health, welfare, and performance in commercial pig farms in Great Britain. We collected on-farm data about the level of biosecurity and animal performance in 40 fattening pig farms and 28 breeding pig farms between 2015 and 2016. We identified interconnections between these data, slaughterhouse health indicators, and welfare indicator records in fattening pig farms. After achieving the connections between databases, a secondary data analysis was performed to assess the interconnections between biosecurity, health, welfare, and performance using correlation analysis, principal component analysis, and hierarchical clustering. Although we could connect the different data sources the final sample size was limited, suggesting room for improvement in database connection to conduct secondary data analyses. The farm biosecurity scores ranged from 40 to 90 out of 100, with internal biosecurity scores being lower than external biosecurity scores. Our analysis suggested several interconnections between health, welfare, and performance. The initial correlation analysis showed that the prevalence of lameness and severe tail lesions was associated with the prevalence of enzootic pneumonia-like lesions and Pyaemia, and the prevalence of severe body marks was associated with several disease indicators, including peritonitis and milk spots (r > 0.3; P < 0.05). Higher average daily weight gain (ADG) was associated with lower prevalence of pleurisy (r > 0.3; P < 0.05), but no connection was identified between mortality and health indicators. A subsequent cluster analysis enabled identification of patterns which considered concurrently indicators of health, welfare, and performance. Farms from cluster 1 had lower biosecurity scores, lower ADG, and higher prevalence of several disease and welfare indicators. Farms from cluster 2 had higher biosecurity scores than cluster 1, but a higher prevalence of pigs requiring hospitalization and lameness which confirmed the correlation between biosecurity and the prevalence of pigs requiring hospitalization (r > 0.3; P < 0.05). Farms from cluster 3 had higher biosecurity, higher ADG, and lower prevalence for some disease and welfare indicators. The study suggests a smaller impact of biosecurity on issues such as mortality, prevalence of lameness, and pig requiring hospitalization. The correlations and the identified clusters suggested the importance of animal welfare for the pig industry
Susanna Williamson - One of the best experts on this subject based on the ideXlab platform.
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Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for low and high discrepancy batches, with significance levels.
2016Co-Authors: Carla Correia-gomes, Richard P. Smith, Jude I. Eze, Madeleine K. Henry, George J. Gunn, Susanna Williamson, Sue C. TongueAbstract:Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for low and high discrepancy batches, with significance levels.
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Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for each of the week field trials and all data of the field trials, with significance levels.
2016Co-Authors: Carla Correia-gomes, Richard P. Smith, Jude I. Eze, Madeleine K. Henry, George J. Gunn, Susanna Williamson, Sue C. TongueAbstract:Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for each of the week field trials and all data of the field trials, with significance levels.
George J. Gunn - One of the best experts on this subject based on the ideXlab platform.
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Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for low and high discrepancy batches, with significance levels.
2016Co-Authors: Carla Correia-gomes, Richard P. Smith, Jude I. Eze, Madeleine K. Henry, George J. Gunn, Susanna Williamson, Sue C. TongueAbstract:Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for low and high discrepancy batches, with significance levels.
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Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for each of the week field trials and all data of the field trials, with significance levels.
2016Co-Authors: Carla Correia-gomes, Richard P. Smith, Jude I. Eze, Madeleine K. Henry, George J. Gunn, Susanna Williamson, Sue C. TongueAbstract:Summary of the correlation/agreement results between the two datasets (BPHS, FSA) for pericarditis, pleurisy, pneumonia, milk spots, tail bite, Pyaemia, peritonitis and abscesses in the lung for each of the week field trials and all data of the field trials, with significance levels.
