Using data mining to identify factors that influence the degree of leg injuries in broilers
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000400003 |
Resumo: | Locomotor problems prevent the bird to move freely, jeopardizing the welfare and productivity, besides generating injuries on the legs of chickens. The objective of this study was to evaluate the influence of age, use of vitamin D, the asymmetry of limbs and gait score, the degree of leg injuries in broilers, using data mining. The analysis was performed on a data set obtained from a field experiment in which it was used two groups of birds with 30 birds each, a control group and one treated with vitamin D. It was evaluated the gait score, the asymmetry between the right and left toes, and the degree of leg injuries. The Weka ® software was used in data mining. In particular, C4.5 algorithm (also known as J48 in Weka environment) was used for the generation of a decision tree. The results showed that age is the factor that most influences the degree of leg injuries and that the data from assessments of gait score were not reliable to estimate leg weakness in broilers. |
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Engenharia Agrícola |
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Using data mining to identify factors that influence the degree of leg injuries in broilersdecision treepoultrygait scoreLocomotor problems prevent the bird to move freely, jeopardizing the welfare and productivity, besides generating injuries on the legs of chickens. The objective of this study was to evaluate the influence of age, use of vitamin D, the asymmetry of limbs and gait score, the degree of leg injuries in broilers, using data mining. The analysis was performed on a data set obtained from a field experiment in which it was used two groups of birds with 30 birds each, a control group and one treated with vitamin D. It was evaluated the gait score, the asymmetry between the right and left toes, and the degree of leg injuries. The Weka ® software was used in data mining. In particular, C4.5 algorithm (also known as J48 in Weka environment) was used for the generation of a decision tree. The results showed that age is the factor that most influences the degree of leg injuries and that the data from assessments of gait score were not reliable to estimate leg weakness in broilers.Associação Brasileira de Engenharia Agrícola2012-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000400003Engenharia Agrícola v.32 n.4 2012reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/S0100-69162012000400003info:eu-repo/semantics/openAccessCordeiro,Alexandra F. da S.Baracho,Marta dos S.Nääs,Irenilza de A.Nascimento,Guilherme R. doeng2012-09-26T00:00:00Zoai:scielo:S0100-69162012000400003Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2012-09-26T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
Using data mining to identify factors that influence the degree of leg injuries in broilers |
title |
Using data mining to identify factors that influence the degree of leg injuries in broilers |
spellingShingle |
Using data mining to identify factors that influence the degree of leg injuries in broilers Cordeiro,Alexandra F. da S. decision tree poultry gait score |
title_short |
Using data mining to identify factors that influence the degree of leg injuries in broilers |
title_full |
Using data mining to identify factors that influence the degree of leg injuries in broilers |
title_fullStr |
Using data mining to identify factors that influence the degree of leg injuries in broilers |
title_full_unstemmed |
Using data mining to identify factors that influence the degree of leg injuries in broilers |
title_sort |
Using data mining to identify factors that influence the degree of leg injuries in broilers |
author |
Cordeiro,Alexandra F. da S. |
author_facet |
Cordeiro,Alexandra F. da S. Baracho,Marta dos S. Nääs,Irenilza de A. Nascimento,Guilherme R. do |
author_role |
author |
author2 |
Baracho,Marta dos S. Nääs,Irenilza de A. Nascimento,Guilherme R. do |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Cordeiro,Alexandra F. da S. Baracho,Marta dos S. Nääs,Irenilza de A. Nascimento,Guilherme R. do |
dc.subject.por.fl_str_mv |
decision tree poultry gait score |
topic |
decision tree poultry gait score |
description |
Locomotor problems prevent the bird to move freely, jeopardizing the welfare and productivity, besides generating injuries on the legs of chickens. The objective of this study was to evaluate the influence of age, use of vitamin D, the asymmetry of limbs and gait score, the degree of leg injuries in broilers, using data mining. The analysis was performed on a data set obtained from a field experiment in which it was used two groups of birds with 30 birds each, a control group and one treated with vitamin D. It was evaluated the gait score, the asymmetry between the right and left toes, and the degree of leg injuries. The Weka ® software was used in data mining. In particular, C4.5 algorithm (also known as J48 in Weka environment) was used for the generation of a decision tree. The results showed that age is the factor that most influences the degree of leg injuries and that the data from assessments of gait score were not reliable to estimate leg weakness in broilers. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-08-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000400003 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000400003 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0100-69162012000400003 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
dc.source.none.fl_str_mv |
Engenharia Agrícola v.32 n.4 2012 reponame:Engenharia Agrícola instname:Associação Brasileira de Engenharia Agrícola (SBEA) instacron:SBEA |
instname_str |
Associação Brasileira de Engenharia Agrícola (SBEA) |
instacron_str |
SBEA |
institution |
SBEA |
reponame_str |
Engenharia Agrícola |
collection |
Engenharia Agrícola |
repository.name.fl_str_mv |
Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA) |
repository.mail.fl_str_mv |
revistasbea@sbea.org.br||sbea@sbea.org.br |
_version_ |
1752126271022694400 |