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

SIMPLE SUMMARY: We tested two computer-vision-based indexes to analyze the rearing-environment enrichment on broiler movement as a function of comfort temperature and heat stress. The results indicated that the simultaneous application of cluster and unrest indexes could monitor the movement of the...

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Autores principales: Massari, Juliana Maria, de Moura, Daniella Jorge, de Alencar Nääs, Irenilza, Pereira, Danilo Florentino, Branco, Tatiane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8996930/
https://www.ncbi.nlm.nih.gov/pubmed/35405837
http://dx.doi.org/10.3390/ani12070846
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author Massari, Juliana Maria
de Moura, Daniella Jorge
de Alencar Nääs, Irenilza
Pereira, Danilo Florentino
Branco, Tatiane
author_facet Massari, Juliana Maria
de Moura, Daniella Jorge
de Alencar Nääs, Irenilza
Pereira, Danilo Florentino
Branco, Tatiane
author_sort Massari, Juliana Maria
collection PubMed
description SIMPLE SUMMARY: We tested two computer-vision-based indexes to analyze the rearing-environment enrichment on broiler movement as a function of comfort temperature and heat stress. The results indicated that the simultaneous application of cluster and unrest indexes could monitor the movement of the group of broilers under different environmental conditions. Future monitoring and alert systems based on computer vision should consider the complexity of the environment for detecting heat stress in broiler production. ABSTRACT: 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 proportions 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 pubmed-89969302022-04-12 Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept Massari, Juliana Maria de Moura, Daniella Jorge de Alencar Nääs, Irenilza Pereira, Danilo Florentino Branco, Tatiane Animals (Basel) Article SIMPLE SUMMARY: We tested two computer-vision-based indexes to analyze the rearing-environment enrichment on broiler movement as a function of comfort temperature and heat stress. The results indicated that the simultaneous application of cluster and unrest indexes could monitor the movement of the group of broilers under different environmental conditions. Future monitoring and alert systems based on computer vision should consider the complexity of the environment for detecting heat stress in broiler production. ABSTRACT: 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 proportions 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. MDPI 2022-03-28 /pmc/articles/PMC8996930/ /pubmed/35405837 http://dx.doi.org/10.3390/ani12070846 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Massari, Juliana Maria
de Moura, Daniella Jorge
de Alencar Nääs, Irenilza
Pereira, Danilo Florentino
Branco, Tatiane
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
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_short 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8996930/
https://www.ncbi.nlm.nih.gov/pubmed/35405837
http://dx.doi.org/10.3390/ani12070846
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