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11. | | VALE, M. M.; MOURA, D. J. de; NÄÄS, I. de A.; OLIVEIRA, S. R. de M.; RODRIGUES, L. H. A. Data mining to estimate broiler mortality when exposed to heat wave. Scientia Agricola, Piracicaba, v. 65, n. 3, p. 223-229, May/June 2008. Biblioteca(s): Embrapa Agricultura Digital. |
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14. | | CORDEIRO, A. F. da S.; NÄÄS, I. de A.; OLIVEIRA, S. R. de M.; VIOLARO, F.; ALMEIDA, A. C. M. de Almeida. Efficiency of distinct data mining algorithms for classifying stress level in piglets from their vocalization. Engenharia Agrícola, Jaboticabal, v. 32, n. 2, p. 208-216, Mar./Apr. 2012. Biblioteca(s): Embrapa Agricultura Digital. |
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15. | | ROMANINI, C. E. B.; OLIVEIRA, S. R. de M.; RODRIGUES, L. H. A.; GIGLI, A. C. de S.; BARACHO, M. dos S.; NÄÄS, I. de A. Análise de processo de incubação de ovos de matrizes pesadas usando mineração de dados. In: CONFERÊNCIA APINCO' DE CIÊNCIA E TECNOLOGIA AVÍCOLA, 2008, Santos. Trabalhos expostos... Santos: Facta, 2008. Não paginado. Suplemento 10 Rev. Bras. de Ciência Avícola, 2008. Biblioteca(s): Embrapa Agricultura Digital. |
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16. | | BRANCO, T.; MOURA, D. J. de; NÄÄS, I. de A.; LIMA, N. D. da S.; KLEIN, D. R.; OLIVEIRA, S. R. de M. The sequential behavior pattern analysis of broiler chickens exposed to heat stress. AgriEngineering, v. 3, n. 3, p. 447-457, Sept. 2021. Biblioteca(s): Embrapa Agricultura Digital. |
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Registros recuperados : 17 | |
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Registro Completo
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
12/09/2013 |
Data da última atualização: |
04/02/2014 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 5 |
Autoria: |
CORDEIRO, A. F. da S.; NÄÄS, I. de A.; OLIVEIRA, S. R. de M.; VIOLARO, F.; NEVES, D. P. |
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. |
Título: |
Understanding vocalization might help to assess stressful conditions in piglets. |
Ano de publicação: |
2013 |
Fonte/Imprenta: |
Animals, v. 3, n. 3, p. 923-934, 2013. |
DOI: |
10.3390/ani3030923 |
Idioma: |
Inglês |
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. |
Palavras-Chave: |
Algoritmo. |
Thesagro: |
Suíno; Suinocultura. |
Thesaurus NAL: |
Algorithms; Mathematical models; Piglets; Swine; Young animals. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/89323/1/animals-03-00923.pdf
|
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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Embrapa Agricultura Digital (CNPTIA) |
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