Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography
Autor(a) principal: | |
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Data de Publicação: | 2016 |
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=S0100-69162016000100001 |
Resumo: | ABSTRACT The objective of this study was to evaluate the thermoregulatory response of dairy buffaloes in pre-milking and post-milking. To identify animal thermoregulatory capacity, skin surface temperatures were taken by an infrared thermometer (SST), a thermographic camera (MTBP) as well as respiratory rate records (RR). Black Globe and Humidity Index (BGHI), radiating thermal load (RTL) and enthalpy (H) were used to characterize the thermal environment. Artificial Neural Networks analyzed those indices as well as animal physiological data, using a single layer trained with the least mean square (LMS) algorithm. The results indicated that pre-milking and post-milking environments reached BGHI, RR, SST and MTBP values above thermal neutrality zone for buffaloes. In addition, limits of surface skin temperatures were mostly influenced by changing ambient conditions to the detriment of respiratory rates. It follows that buffaloes are sensitive to environmental changes and their skin temperatures are the best indicators of thermal comfort in relation to respiratory rate. |
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Engenharia Agrícola |
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Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermographybuffaloheat stressrespiratory ratesurface temperatureABSTRACT The objective of this study was to evaluate the thermoregulatory response of dairy buffaloes in pre-milking and post-milking. To identify animal thermoregulatory capacity, skin surface temperatures were taken by an infrared thermometer (SST), a thermographic camera (MTBP) as well as respiratory rate records (RR). Black Globe and Humidity Index (BGHI), radiating thermal load (RTL) and enthalpy (H) were used to characterize the thermal environment. Artificial Neural Networks analyzed those indices as well as animal physiological data, using a single layer trained with the least mean square (LMS) algorithm. The results indicated that pre-milking and post-milking environments reached BGHI, RR, SST and MTBP values above thermal neutrality zone for buffaloes. In addition, limits of surface skin temperatures were mostly influenced by changing ambient conditions to the detriment of respiratory rates. It follows that buffaloes are sensitive to environmental changes and their skin temperatures are the best indicators of thermal comfort in relation to respiratory rate.Associação Brasileira de Engenharia Agrícola2016-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162016000100001Engenharia Agrícola v.36 n.1 2016reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-Eng.Agric.v36n1p1-12/2016info:eu-repo/semantics/openAccessSevegnani,Kelly BFernandes,Danielle P. BSilva,Silvia H. Modenese-Gorla daeng2016-04-20T00:00:00Zoai:scielo:S0100-69162016000100001Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2016-04-20T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography |
title |
Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography |
spellingShingle |
Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography Sevegnani,Kelly B buffalo heat stress respiratory rate surface temperature |
title_short |
Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography |
title_full |
Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography |
title_fullStr |
Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography |
title_full_unstemmed |
Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography |
title_sort |
Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography |
author |
Sevegnani,Kelly B |
author_facet |
Sevegnani,Kelly B Fernandes,Danielle P. B Silva,Silvia H. Modenese-Gorla da |
author_role |
author |
author2 |
Fernandes,Danielle P. B Silva,Silvia H. Modenese-Gorla da |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Sevegnani,Kelly B Fernandes,Danielle P. B Silva,Silvia H. Modenese-Gorla da |
dc.subject.por.fl_str_mv |
buffalo heat stress respiratory rate surface temperature |
topic |
buffalo heat stress respiratory rate surface temperature |
description |
ABSTRACT The objective of this study was to evaluate the thermoregulatory response of dairy buffaloes in pre-milking and post-milking. To identify animal thermoregulatory capacity, skin surface temperatures were taken by an infrared thermometer (SST), a thermographic camera (MTBP) as well as respiratory rate records (RR). Black Globe and Humidity Index (BGHI), radiating thermal load (RTL) and enthalpy (H) were used to characterize the thermal environment. Artificial Neural Networks analyzed those indices as well as animal physiological data, using a single layer trained with the least mean square (LMS) algorithm. The results indicated that pre-milking and post-milking environments reached BGHI, RR, SST and MTBP values above thermal neutrality zone for buffaloes. In addition, limits of surface skin temperatures were mostly influenced by changing ambient conditions to the detriment of respiratory rates. It follows that buffaloes are sensitive to environmental changes and their skin temperatures are the best indicators of thermal comfort in relation to respiratory rate. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-02-01 |
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=S0100-69162016000100001 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162016000100001 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-Eng.Agric.v36n1p1-12/2016 |
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.36 n.1 2016 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_ |
1752126272460292096 |