Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept

Detalhes bibliográficos
Autor(a) principal: Massari, Juliana Maria
Data de Publicação: 2022
Outros Autores: de Moura, Daniella Jorge, Nääs, Irenilza de Alencar, Pereira, Danilo Florentino [UNESP], Branco, Tatiane
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3390/ani12070846
http://hdl.handle.net/11449/230639
Resumo: Computer-vision systems for herd detection and monitoring are increasingly present in precision livestock. This technology provides insights into how environmental variations affect the group’s movement pattern. We hypothesize that the cluster and unrest indexes based on computer vision (CV) can simultaneously assess the movement variation of reared broilers under different environmental conditions. The present study is a proof of principle and was carried out with twenty broilers (commercial strain Cobb®), housed in a controlled-environment chamber. The birds were divided into two groups, one housed in an enriched environment and the control. Both groups were subjected to thermal comfort conditions and heat stress. Image analysis of individual or group behavior is the basis for generating animal-monitoring indexes, capable of creating real-time alert systems, predicting welfare, health, environment, and production status. The results obtained in the experiment in a controlled environment allowed the validation of the simultaneous application of cluster and unrest indexes by monitoring the movement of the group of broilers under different environmental conditions. Observational results also suggest that research in more significant pro-portions should be carried out to evaluate the potential positive impact of environmental enrichment in poultry production. The complexity of the environment is a factor to be considered in creating alert systems for detecting heat stress in broiler production. In large groups, birds’ movement and grouping patterns may differ; therefore, the CV system and indices will need to be recalibrated.
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spelling Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Conceptanimal behavioranimal welfareimage analysisprecision livestockwalking abilityComputer-vision systems for herd detection and monitoring are increasingly present in precision livestock. This technology provides insights into how environmental variations affect the group’s movement pattern. We hypothesize that the cluster and unrest indexes based on computer vision (CV) can simultaneously assess the movement variation of reared broilers under different environmental conditions. The present study is a proof of principle and was carried out with twenty broilers (commercial strain Cobb®), housed in a controlled-environment chamber. The birds were divided into two groups, one housed in an enriched environment and the control. Both groups were subjected to thermal comfort conditions and heat stress. Image analysis of individual or group behavior is the basis for generating animal-monitoring indexes, capable of creating real-time alert systems, predicting welfare, health, environment, and production status. The results obtained in the experiment in a controlled environment allowed the validation of the simultaneous application of cluster and unrest indexes by monitoring the movement of the group of broilers under different environmental conditions. Observational results also suggest that research in more significant pro-portions should be carried out to evaluate the potential positive impact of environmental enrichment in poultry production. The complexity of the environment is a factor to be considered in creating alert systems for detecting heat stress in broiler production. In large groups, birds’ movement and grouping patterns may differ; therefore, the CV system and indices will need to be recalibrated.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)College of Agricultural Engineering State University of Campinas, 501 Candido Rondon Avenue, CampinasGraduate Program in Production Engineering Universidade Paulista, 1212 Dr. Bacelar Street,Department of Management Development and Technology School of Science and Engineering São Paulo State University, 780 Domingos da Costa Lopes Avenue, TupãDepartment of Management Development and Technology School of Science and Engineering São Paulo State University, 780 Domingos da Costa Lopes Avenue, TupãCNPq: 304085/2021-9CNPq: 308177/2021-7Universidade Estadual de Campinas (UNICAMP)Universidade PaulistaUniversidade Estadual Paulista (UNESP)Massari, Juliana Mariade Moura, Daniella JorgeNääs, Irenilza de AlencarPereira, Danilo Florentino [UNESP]Branco, Tatiane2022-04-29T08:41:20Z2022-04-29T08:41:20Z2022-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/ani12070846Animals, v. 12, n. 7, 2022.2076-2615http://hdl.handle.net/11449/23063910.3390/ani120708462-s2.0-85127168623Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAnimalsinfo:eu-repo/semantics/openAccess2022-04-29T08:41:20Zoai:repositorio.unesp.br:11449/230639Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-29T08:41:20Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept
title Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept
spellingShingle Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept
Massari, Juliana Maria
animal behavior
animal welfare
image analysis
precision livestock
walking ability
title_short Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept
title_full Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept
title_fullStr Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept
title_full_unstemmed Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept
title_sort Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept
author Massari, Juliana Maria
author_facet Massari, Juliana Maria
de Moura, Daniella Jorge
Nääs, Irenilza de Alencar
Pereira, Danilo Florentino [UNESP]
Branco, Tatiane
author_role author
author2 de Moura, Daniella Jorge
Nääs, Irenilza de Alencar
Pereira, Danilo Florentino [UNESP]
Branco, Tatiane
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual de Campinas (UNICAMP)
Universidade Paulista
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Massari, Juliana Maria
de Moura, Daniella Jorge
Nääs, Irenilza de Alencar
Pereira, Danilo Florentino [UNESP]
Branco, Tatiane
dc.subject.por.fl_str_mv animal behavior
animal welfare
image analysis
precision livestock
walking ability
topic animal behavior
animal welfare
image analysis
precision livestock
walking ability
description Computer-vision systems for herd detection and monitoring are increasingly present in precision livestock. This technology provides insights into how environmental variations affect the group’s movement pattern. We hypothesize that the cluster and unrest indexes based on computer vision (CV) can simultaneously assess the movement variation of reared broilers under different environmental conditions. The present study is a proof of principle and was carried out with twenty broilers (commercial strain Cobb®), housed in a controlled-environment chamber. The birds were divided into two groups, one housed in an enriched environment and the control. Both groups were subjected to thermal comfort conditions and heat stress. Image analysis of individual or group behavior is the basis for generating animal-monitoring indexes, capable of creating real-time alert systems, predicting welfare, health, environment, and production status. The results obtained in the experiment in a controlled environment allowed the validation of the simultaneous application of cluster and unrest indexes by monitoring the movement of the group of broilers under different environmental conditions. Observational results also suggest that research in more significant pro-portions should be carried out to evaluate the potential positive impact of environmental enrichment in poultry production. The complexity of the environment is a factor to be considered in creating alert systems for detecting heat stress in broiler production. In large groups, birds’ movement and grouping patterns may differ; therefore, the CV system and indices will need to be recalibrated.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-29T08:41:20Z
2022-04-29T08:41:20Z
2022-04-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.3390/ani12070846
Animals, v. 12, n. 7, 2022.
2076-2615
http://hdl.handle.net/11449/230639
10.3390/ani12070846
2-s2.0-85127168623
url http://dx.doi.org/10.3390/ani12070846
http://hdl.handle.net/11449/230639
identifier_str_mv Animals, v. 12, n. 7, 2022.
2076-2615
10.3390/ani12070846
2-s2.0-85127168623
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Animals
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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