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| 12. |  | GOMES, M. A. F.; PEREIRA, L. C.; SILVA, A. K. L.; PEREIRA, A. S.; TOSTO, S. G.; SOUSA JUNIOR, P. M. DE. Aspectos qualitativos da água do Rio Pindaré na Amazônia Maranhense. Revista Terceira Margem Amazônia, v. 8, n. 19, p. 253-269, 2023.| Biblioteca(s): Embrapa Meio Ambiente; Embrapa Territorial. |
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| Registros recuperados : 30 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
12/09/2013 |
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Data da última atualização: |
04/02/2014 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 5 |
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Autoria: |
CORDEIRO, A. F. da S.; NÄÄS, I. de A.; OLIVEIRA, S. R. de M.; VIOLARO, F.; NEVES, D. P. |
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Afiliação: |
ALEXANDRA FERREIRA DA SILVA CORDEIRO, Unicamp; IRENILZA DE ALENCAR NÄÄS, UNICAMP; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; FABIO VIOLARO, Unicamp; DIEGO PEREIRA NEVES, Unicamp. |
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Título: |
Understanding vocalization might help to assess stressful conditions in piglets. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Animals, v. 3, n. 3, p. 923-934, 2013. |
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DOI: |
10.3390/ani3030923 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: 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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Palavras-Chave: |
Algoritmo. |
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Thesagro: |
Suíno; Suinocultura. |
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Thesaurus NAL: |
Algorithms; Mathematical models; Piglets; Swine; Young animals. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/89323/1/animals-03-00923.pdf
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Marc: |
LEADER 01975naa a2200277 a 4500
001 1966129
005 2014-02-04
008 2013 bl uuuu u00u1 u #d
024 7 $a10.3390/ani3030923$2DOI
100 1 $aCORDEIRO, A. F. da S.
245 $aUnderstanding vocalization might help to assess stressful conditions in piglets.$h[electronic resource]
260 $c2013
520 $aAbstract: 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.
650 $aAlgorithms
650 $aMathematical models
650 $aPiglets
650 $aSwine
650 $aYoung animals
650 $aSuíno
650 $aSuinocultura
653 $aAlgoritmo
700 1 $aNÄÄS, I. de A.
700 1 $aOLIVEIRA, S. R. de M.
700 1 $aVIOLARO, F.
700 1 $aNEVES, D. P.
773 $tAnimals$gv. 3, n. 3, p. 923-934, 2013.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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