Understanding vocalization might help to assess stressful conditions in piglets
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://www.mdpi.com/2076-2615/3/3/923 http://repositorio.ufla.br/jspui/handle/1/11684 |
Resumo: | Assessing pigs’ welfare is one of the most challenging subjects in intensive pig farming. Animal vocalization analysis is a noninvasive procedure and may be used as a tool for assessing animal welfare status. The objective of this research was to identify stress conditions in piglets reared in farrowing pens through their vocalization. Vocal signals were collected from 40 animals under the following situations: normal (baseline), feeling cold, in pain, and feeling hunger. A unidirectional microphone positioned about 15 cm from the animals’ mouth was used for recording the acoustic signals. The microphone was connected to a digital recorder, where the signals were digitized at the 44,100 Hz frequency. The collected sounds were edited and analyzed. The J48 decision tree algorithm available at the Weka® data mining software was used for stress classification. It was possible to categorize diverse conditions from the piglets’ vocalization during the farrowing phase (pain, cold and hunger), with an accuracy rate of 81.12%. Results indicated that vocalization might be an effective welfare indicator, and it could be applied for assessing distress from pain, cold and hunger in farrowing piglets. |
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Understanding vocalization might help to assess stressful conditions in pigletsAnimal welfarePig farmingSound signalsClassification algorithmAssessing pigs’ welfare is one of the most challenging subjects in intensive pig farming. Animal vocalization analysis is a noninvasive procedure and may be used as a tool for assessing animal welfare status. The objective of this research was to identify stress conditions in piglets reared in farrowing pens through their vocalization. Vocal signals were collected from 40 animals under the following situations: normal (baseline), feeling cold, in pain, and feeling hunger. A unidirectional microphone positioned about 15 cm from the animals’ mouth was used for recording the acoustic signals. The microphone was connected to a digital recorder, where the signals were digitized at the 44,100 Hz frequency. The collected sounds were edited and analyzed. The J48 decision tree algorithm available at the Weka® data mining software was used for stress classification. It was possible to categorize diverse conditions from the piglets’ vocalization during the farrowing phase (pain, cold and hunger), with an accuracy rate of 81.12%. Results indicated that vocalization might be an effective welfare indicator, and it could be applied for assessing distress from pain, cold and hunger in farrowing piglets.2016-08-24T21:08:46Z2016-08-24T21:08:46Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleCORDEIRO, A. F. da S. et al. Understanding vocalization might help to assess stressful conditions in piglets. Animals, [S.l.], v. 3, n. 3, p. 923-934, 2013.http://www.mdpi.com/2076-2615/3/3/923http://repositorio.ufla.br/jspui/handle/1/11684Animalsreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLACordeiro, Alexandra Ferreira da SilvaNaas, Irenilza de AlencarOliveira, Stanley R. M.Violaro, FabioAlmeida, Andréia C. M. deNeves, Diego Pereirainfo:eu-repo/semantics/openAccesspor2023-05-03T11:26:49Zoai:localhost:1/11684Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-03T11:26:49Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Understanding vocalization might help to assess stressful conditions in piglets |
title |
Understanding vocalization might help to assess stressful conditions in piglets |
spellingShingle |
Understanding vocalization might help to assess stressful conditions in piglets Cordeiro, Alexandra Ferreira da Silva Animal welfare Pig farming Sound signals Classification algorithm |
title_short |
Understanding vocalization might help to assess stressful conditions in piglets |
title_full |
Understanding vocalization might help to assess stressful conditions in piglets |
title_fullStr |
Understanding vocalization might help to assess stressful conditions in piglets |
title_full_unstemmed |
Understanding vocalization might help to assess stressful conditions in piglets |
title_sort |
Understanding vocalization might help to assess stressful conditions in piglets |
author |
Cordeiro, Alexandra Ferreira da Silva |
author_facet |
Cordeiro, Alexandra Ferreira da Silva Naas, Irenilza de Alencar Oliveira, Stanley R. M. Violaro, Fabio Almeida, Andréia C. M. de Neves, Diego Pereira |
author_role |
author |
author2 |
Naas, Irenilza de Alencar Oliveira, Stanley R. M. Violaro, Fabio Almeida, Andréia C. M. de Neves, Diego Pereira |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Cordeiro, Alexandra Ferreira da Silva Naas, Irenilza de Alencar Oliveira, Stanley R. M. Violaro, Fabio Almeida, Andréia C. M. de Neves, Diego Pereira |
dc.subject.por.fl_str_mv |
Animal welfare Pig farming Sound signals Classification algorithm |
topic |
Animal welfare Pig farming Sound signals Classification algorithm |
description |
Assessing pigs’ welfare is one of the most challenging subjects in intensive pig farming. Animal vocalization analysis is a noninvasive procedure and may be used as a tool for assessing animal welfare status. The objective of this research was to identify stress conditions in piglets reared in farrowing pens through their vocalization. Vocal signals were collected from 40 animals under the following situations: normal (baseline), feeling cold, in pain, and feeling hunger. A unidirectional microphone positioned about 15 cm from the animals’ mouth was used for recording the acoustic signals. The microphone was connected to a digital recorder, where the signals were digitized at the 44,100 Hz frequency. The collected sounds were edited and analyzed. The J48 decision tree algorithm available at the Weka® data mining software was used for stress classification. It was possible to categorize diverse conditions from the piglets’ vocalization during the farrowing phase (pain, cold and hunger), with an accuracy rate of 81.12%. Results indicated that vocalization might be an effective welfare indicator, and it could be applied for assessing distress from pain, cold and hunger in farrowing piglets. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 2016-08-24T21:08:46Z 2016-08-24T21:08:46Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
CORDEIRO, A. F. da S. et al. Understanding vocalization might help to assess stressful conditions in piglets. Animals, [S.l.], v. 3, n. 3, p. 923-934, 2013. http://www.mdpi.com/2076-2615/3/3/923 http://repositorio.ufla.br/jspui/handle/1/11684 |
identifier_str_mv |
CORDEIRO, A. F. da S. et al. Understanding vocalization might help to assess stressful conditions in piglets. Animals, [S.l.], v. 3, n. 3, p. 923-934, 2013. |
url |
http://www.mdpi.com/2076-2615/3/3/923 http://repositorio.ufla.br/jspui/handle/1/11684 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Animals reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1807835167779192832 |