Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens
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Publication Date: | 2021 |
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Format: | Article |
Language: | por |
Source: | Research, Society and Development |
Download full: | https://rsdjournal.org/index.php/rsd/article/view/13974 |
Summary: | Laying poultry is constantly evolving, with the use of technologies that help the producer to obtain better productivity and, allied to this, the commitment to the welfare of the birds. One of the environmental factors that directly affect these issues is the heat stress that can affect birds due to hot flashes. To mitigate these negative effects, bioclimatic monitoring is carried out, this survey can be used for analyzes that will provide a better view, as is the case with data mining that generates decision trees. Therefore, the objective of this study was to develop decision trees using the data mining tool, as a subsidy for warning systems from the Black Globe Temperature and Humidity Index (BGTHI), mitigating the damage that can be caused by climatic extremes in the production and quality of laying eggs. For this purpose, a data set of three aviaries located in the city of Bastos-SP, collected in the summer season of 2013/2014, was used. These data were selected and organized in Excel® spreadsheets and the BGTHI was calculated, classifying them in comfort bands, after being processed with the Weka® software with J48 algorithm (C4.5) performing data mining. The decision trees generated for each aviary showed a similar behavior, with two branches classified as comfortable or warm, and the BGTHI value was very close, differing only in decimal places. For aviaries A1 and A2 excellent Kappa coefficients were obtained, whereas in A3 this coefficient did not obtain a good classification. |
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Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hensUso de árboles de decisión del Índice De Temperatura Del Globo Negro y Humedad para mitigar el estrés por calor em gallinas ponedoras ligerasUso de árvores de decisão a partir do Índice de Temperatura de Globo e Umidade para mitigar estresse calórico em poedeiras levesAvicultura de PosturaExtremos ClimáticosMineração de DadosProdução de OvosSustainability.Laying Poultry FarmingClimatic ExtremesData MiningEgg ProductionSustentabilidade.Avicultura PonedoraExtremos ClimáticosProcesamiento de DatosProducción de HuevosSustentabilidad.Laying poultry is constantly evolving, with the use of technologies that help the producer to obtain better productivity and, allied to this, the commitment to the welfare of the birds. One of the environmental factors that directly affect these issues is the heat stress that can affect birds due to hot flashes. To mitigate these negative effects, bioclimatic monitoring is carried out, this survey can be used for analyzes that will provide a better view, as is the case with data mining that generates decision trees. Therefore, the objective of this study was to develop decision trees using the data mining tool, as a subsidy for warning systems from the Black Globe Temperature and Humidity Index (BGTHI), mitigating the damage that can be caused by climatic extremes in the production and quality of laying eggs. For this purpose, a data set of three aviaries located in the city of Bastos-SP, collected in the summer season of 2013/2014, was used. These data were selected and organized in Excel® spreadsheets and the BGTHI was calculated, classifying them in comfort bands, after being processed with the Weka® software with J48 algorithm (C4.5) performing data mining. The decision trees generated for each aviary showed a similar behavior, with two branches classified as comfortable or warm, and the BGTHI value was very close, differing only in decimal places. For aviaries A1 and A2 excellent Kappa coefficients were obtained, whereas in A3 this coefficient did not obtain a good classification.La puesta de aves de corral está en constante evolución, con el uso de tecnologías que ayudan al productor a obtener una mejor productividad y, aliado a ello, el compromiso con el bienestar de las aves. Uno de los factores ambientales que afectan directamente estos problemas es el estrés por calor que puede afectar a las aves debido a los sofocos. Para mitigar estos efectos negativos, se realiza un monitoreo bioclimático, esta encuesta se puede utilizar para análisis que brinden una mejor visión, como es el caso de la minería de datos que genera árboles de decisión. Por lo tanto, el objetivo de este estudio fue desarrollar árboles de decisión utilizando la herramienta de minería de datos, como un subsidio a los sistemas de alerta del Índice de Globo de Temperatura y Humedad (IGTH), mitigando el daño que pueden causar los extremos climáticos en la producción y calidad. de poner huevos. Para ello se utilizó un conjunto de datos de tres aviarios ubicados en la ciudad de Bastos-SP, recolectados en la temporada de verano de 2013/2014, estos datos fueron seleccionados y organizados en planillas Excel® y se calculó el IGTH clasificándolos en bandas de confort, luego de ser procesado con el software Weka® con algoritmo J48 (C4.5) realizando minería de datos. Los árboles de decisión generados para cada aviario mostraron un comportamiento similar, con dos ramas clasificadas como cómodas o cálidas, y el valor de IGTH fue muy cercano, difiriendo solo en decimales. Para los aviarios A1 y A2 se obtuvieron excelentes coeficientes Kappa, mientras que en A3 este coeficiente no obtuvo una buena clasificación.A avicultura de postura se encontra em constante evolução, com uso de tecnologias que ajudam o produtor a obter melhores produtividades e, aliado a isso, o comprometimento com o bem-estar das aves. Um dos fatores ambientais que afetam diretamente essas questões é o estresse calórico que pode afetar as aves devido a ondas de calor. Para a mitigação desses efeitos negativos é realizado o monitoramento bioclimático, esse levantamento pode ser destinado a análises que fornecerão uma melhor visualização, como é o caso da mineração de dados que gera árvores de decisão. Sendo assim, o objetivo desse estudo foi desenvolver árvores de decisão com o uso da ferramenta de mineração de dados, como subsídio para sistemas de alerta a partir do Índice de Temperatura de Globo e Umidade (ITGU), mitigando os danos que podem ser causados por extremos climáticos na produção e qualidade de ovos de poedeiras. Para tal, foi utilizado um conjunto de dados de três aviários localizados na cidade de Bastos-SP, coletados na estação do verão de 2013/2014, esses dados foram selecionados e organizados em planilhas Excel® e calculado o ITGU, classificando em faixas de conforto, após processados com o software Weka® com algoritmo J48 (C4.5) realizando a mineração dos dados. As árvores de decisão geradas para cada um dos aviários demonstraram um comportamento parecido, com dois ramos classificando em confortável ou quente, sendo que, o valor de ITGU foi muito próximo se diferindo apenas nas casas decimais. Para os aviários A1 e A2 foram obtidos coeficientes Kappa excelentes, já no A3 este coeficiente não obteve uma boa classificação.Research, Society and Development2021-04-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1397410.33448/rsd-v10i4.13974Research, Society and Development; Vol. 10 No. 4; e21410413974Research, Society and Development; Vol. 10 Núm. 4; e21410413974Research, Society and Development; v. 10 n. 4; e214104139742525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/13974/12602Copyright (c) 2021 Maria Elena Silva Montanhani; Érik dos Santos Harada; Mario Mollo Neto; Silvia Regina Lucas de Souza; Ricardo da Fonseca; Leda Gobbo de Freitas Buenohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessMontanhani, Maria Elena Silva Harada, Érik dos Santos Mollo Neto, MarioSouza, Silvia Regina Lucas de Fonseca, Ricardo da Bueno, Leda Gobbo de Freitas 2021-04-25T11:21:26Zoai:ojs.pkp.sfu.ca:article/13974Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:35:12.189890Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens Uso de árboles de decisión del Índice De Temperatura Del Globo Negro y Humedad para mitigar el estrés por calor em gallinas ponedoras ligeras Uso de árvores de decisão a partir do Índice de Temperatura de Globo e Umidade para mitigar estresse calórico em poedeiras leves |
title |
Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens |
spellingShingle |
Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens Montanhani, Maria Elena Silva Avicultura de Postura Extremos Climáticos Mineração de Dados Produção de Ovos Sustainability. Laying Poultry Farming Climatic Extremes Data Mining Egg Production Sustentabilidade. Avicultura Ponedora Extremos Climáticos Procesamiento de Datos Producción de Huevos Sustentabilidad. |
title_short |
Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens |
title_full |
Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens |
title_fullStr |
Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens |
title_full_unstemmed |
Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens |
title_sort |
Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens |
author |
Montanhani, Maria Elena Silva |
author_facet |
Montanhani, Maria Elena Silva Harada, Érik dos Santos Mollo Neto, Mario Souza, Silvia Regina Lucas de Fonseca, Ricardo da Bueno, Leda Gobbo de Freitas |
author_role |
author |
author2 |
Harada, Érik dos Santos Mollo Neto, Mario Souza, Silvia Regina Lucas de Fonseca, Ricardo da Bueno, Leda Gobbo de Freitas |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Montanhani, Maria Elena Silva Harada, Érik dos Santos Mollo Neto, Mario Souza, Silvia Regina Lucas de Fonseca, Ricardo da Bueno, Leda Gobbo de Freitas |
dc.subject.por.fl_str_mv |
Avicultura de Postura Extremos Climáticos Mineração de Dados Produção de Ovos Sustainability. Laying Poultry Farming Climatic Extremes Data Mining Egg Production Sustentabilidade. Avicultura Ponedora Extremos Climáticos Procesamiento de Datos Producción de Huevos Sustentabilidad. |
topic |
Avicultura de Postura Extremos Climáticos Mineração de Dados Produção de Ovos Sustainability. Laying Poultry Farming Climatic Extremes Data Mining Egg Production Sustentabilidade. Avicultura Ponedora Extremos Climáticos Procesamiento de Datos Producción de Huevos Sustentabilidad. |
description |
Laying poultry is constantly evolving, with the use of technologies that help the producer to obtain better productivity and, allied to this, the commitment to the welfare of the birds. One of the environmental factors that directly affect these issues is the heat stress that can affect birds due to hot flashes. To mitigate these negative effects, bioclimatic monitoring is carried out, this survey can be used for analyzes that will provide a better view, as is the case with data mining that generates decision trees. Therefore, the objective of this study was to develop decision trees using the data mining tool, as a subsidy for warning systems from the Black Globe Temperature and Humidity Index (BGTHI), mitigating the damage that can be caused by climatic extremes in the production and quality of laying eggs. For this purpose, a data set of three aviaries located in the city of Bastos-SP, collected in the summer season of 2013/2014, was used. These data were selected and organized in Excel® spreadsheets and the BGTHI was calculated, classifying them in comfort bands, after being processed with the Weka® software with J48 algorithm (C4.5) performing data mining. The decision trees generated for each aviary showed a similar behavior, with two branches classified as comfortable or warm, and the BGTHI value was very close, differing only in decimal places. For aviaries A1 and A2 excellent Kappa coefficients were obtained, whereas in A3 this coefficient did not obtain a good classification. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-04-08 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/13974 10.33448/rsd-v10i4.13974 |
url |
https://rsdjournal.org/index.php/rsd/article/view/13974 |
identifier_str_mv |
10.33448/rsd-v10i4.13974 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/13974/12602 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 10 No. 4; e21410413974 Research, Society and Development; Vol. 10 Núm. 4; e21410413974 Research, Society and Development; v. 10 n. 4; e21410413974 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1831934880831766528 |