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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8996930 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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