Your browser doesn't support javascript.

Portal de Pesquisa da BVS Veterinária

Informação e Conhecimento para a Saúde

Home > Pesquisa > ()
Imprimir Exportar

Formato de exportação:

Exportar

Exportar:

Email
Adicionar mais destinatários

Enviar resultado
| |

Estimation of thermal comfort indexes for production animals using multiple linear regression modelsˆien

Sarnighausen, Valéria Cristina Rodriguesˆ1Universidade Estadual Paulistaˆ2Faculdade de Ciências Agronômicasˆ3Departamento de Bioprocessos e BiotecnologiaˆcBotucatuˆpBrasil.
J. Anim. Behav. Biometeorol.; 7(2): 73-77, Apr. 2019. tab, graf
Artigo em Inglês | VETINDEX | ID: vti-17586

Resumo

Enthalpy, physical quantity indicating the amount of thermal energy in the medium, is used by many researchers as an indicator of thermal comfort for humans and production animals. This physical quantity has as input variables the dry bulb temperature, the relative humidity of the air and the local barometric pressure. According to consolidated information of temperature and relative humidity related to the animal homeostasis, it was possible to establish enthalpy ranges for thermal comfort of swine, poultry and cattle, considering the local barometric pressure and its variations, which is not easily accessible in situations of field. Thus, the present study aimed to use multiple linear regression models to estimate enthalpy values by means of easily accessible variables (dry and wet bulb temperatures and relative humidity) which can be obtained by means of psychrometers or even by means of low-cost sensors, currently accessible. Meteorological data from three cities of the Brazilian territory, each representing an animal production system (poultry, swine and cattle) were accessed from the National Institute of Meteorology (INMET) database. According to the analysis of the prediction quality verification indices, the obtained models are efficient in predicting enthalpy values with the use of dry bulb temperature and relative humidity.(AU)
Biblioteca responsável: BR68.1