Estimating mortality in laying hens as the environmental temperature increases

Layer mortality due to heat stress is an important economic loss for the producer. The aim of this study was to determine the mortality pattern of layers reared in the region of Bastos, SP, Brazil, according to external environment and bird age. Data mining technique were used based on monthly morta...

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Bibliographic Details
Main Authors: DF Pereira, MM do Vale, BR Zevolli, DD Salgado
Format: Article
Language:English
Published: Fundação APINCO de Ciência e Tecnologia Avícolas 2010-12-01
Series:Brazilian Journal of Poultry Science
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2010000400008
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spelling doaj-fece8fbdf5c34aaeb49b70e45db3e7f42020-11-24T23:58:15ZengFundação APINCO de Ciência e Tecnologia AvícolasBrazilian Journal of Poultry Science1516-635X1806-90612010-12-0112426527110.1590/S1516-635X2010000400008Estimating mortality in laying hens as the environmental temperature increasesDF PereiraMM do ValeBR ZevolliDD SalgadoLayer mortality due to heat stress is an important economic loss for the producer. The aim of this study was to determine the mortality pattern of layers reared in the region of Bastos, SP, Brazil, according to external environment and bird age. Data mining technique were used based on monthly mortality records of hens in production, 135 poultry houses, from January 2004 to August 2008. The external environment was characterized according maximum and minimum temperatures, obtained monthly at the meteorological station CATI in the city of Tupã, SP, Brazil. Mortality was classified as normal (£ 1.2%) or high (> 1.2%), considering the mortality limits mentioned in literature. Data mining technique produced a decision tree with nine levels and 23 leaves, with 62.6% of overall accuracy. The hit rate for the High class was 64.1% and 59.9% for Normal class. The decision tree allowed finding a pattern in the mortality data, generating a model for estimating mortality based on the thermal environment and bird age.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2010000400008Data mininglayer productionmortalitythermal comfort
collection DOAJ
language English
format Article
sources DOAJ
author DF Pereira
MM do Vale
BR Zevolli
DD Salgado
spellingShingle DF Pereira
MM do Vale
BR Zevolli
DD Salgado
Estimating mortality in laying hens as the environmental temperature increases
Brazilian Journal of Poultry Science
Data mining
layer production
mortality
thermal comfort
author_facet DF Pereira
MM do Vale
BR Zevolli
DD Salgado
author_sort DF Pereira
title Estimating mortality in laying hens as the environmental temperature increases
title_short Estimating mortality in laying hens as the environmental temperature increases
title_full Estimating mortality in laying hens as the environmental temperature increases
title_fullStr Estimating mortality in laying hens as the environmental temperature increases
title_full_unstemmed Estimating mortality in laying hens as the environmental temperature increases
title_sort estimating mortality in laying hens as the environmental temperature increases
publisher Fundação APINCO de Ciência e Tecnologia Avícolas
series Brazilian Journal of Poultry Science
issn 1516-635X
1806-9061
publishDate 2010-12-01
description Layer mortality due to heat stress is an important economic loss for the producer. The aim of this study was to determine the mortality pattern of layers reared in the region of Bastos, SP, Brazil, according to external environment and bird age. Data mining technique were used based on monthly mortality records of hens in production, 135 poultry houses, from January 2004 to August 2008. The external environment was characterized according maximum and minimum temperatures, obtained monthly at the meteorological station CATI in the city of Tupã, SP, Brazil. Mortality was classified as normal (£ 1.2%) or high (> 1.2%), considering the mortality limits mentioned in literature. Data mining technique produced a decision tree with nine levels and 23 leaves, with 62.6% of overall accuracy. The hit rate for the High class was 64.1% and 59.9% for Normal class. The decision tree allowed finding a pattern in the mortality data, generating a model for estimating mortality based on the thermal environment and bird age.
topic Data mining
layer production
mortality
thermal comfort
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2010000400008
work_keys_str_mv AT dfpereira estimatingmortalityinlayinghensastheenvironmentaltemperatureincreases
AT mmdovale estimatingmortalityinlayinghensastheenvironmentaltemperatureincreases
AT brzevolli estimatingmortalityinlayinghensastheenvironmentaltemperatureincreases
AT ddsalgado estimatingmortalityinlayinghensastheenvironmentaltemperatureincreases
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