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Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups

We sought to objectively quantify and compare the recorded movement and location patterns of laying hens within a commercial system. Using a custom tracking system, we monitored the location within five zones of a commercial aviary for 13 hens within a flock of 225 animals for a contiguous period of...

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Autores principales: Rufener, C., Berezowski, J., Maximiano Sousa, F., Abreu, Y., Asher, L., Toscano, M. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6098140/
https://www.ncbi.nlm.nih.gov/pubmed/30120253
http://dx.doi.org/10.1038/s41598-018-29962-x
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author Rufener, C.
Berezowski, J.
Maximiano Sousa, F.
Abreu, Y.
Asher, L.
Toscano, M. J.
author_facet Rufener, C.
Berezowski, J.
Maximiano Sousa, F.
Abreu, Y.
Asher, L.
Toscano, M. J.
author_sort Rufener, C.
collection PubMed
description We sought to objectively quantify and compare the recorded movement and location patterns of laying hens within a commercial system. Using a custom tracking system, we monitored the location within five zones of a commercial aviary for 13 hens within a flock of 225 animals for a contiguous period of 11 days. Most hens manifested a hen-specific pattern that was (visually) highly consistent across days, though, within that consistency, manifested stark differences between hens. Three different methods were used to classify individual daily datasets into groups based on their similarity: (i) Linear Discriminant Analysis based on six summary variables (transitions into each zone) and total transitions; (ii) Hierarchical Clustering, a naïve clustering analysis technique, applied to summary variables and iii) Hierarchical Clustering applied to dissimilarity matrices produced by Dynamic Time Warping. The three methods correctly classified more than 85% of the hen days and provided a unique means to assess behaviour of a system indicating a considerable degree of complexity and structure. We believe the current effort is the first to document these location and movement patterns within a large, complex commercial system with a large potential to influence the assessment of animal welfare, health, and productivity.
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spelling pubmed-60981402018-08-23 Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups Rufener, C. Berezowski, J. Maximiano Sousa, F. Abreu, Y. Asher, L. Toscano, M. J. Sci Rep Article We sought to objectively quantify and compare the recorded movement and location patterns of laying hens within a commercial system. Using a custom tracking system, we monitored the location within five zones of a commercial aviary for 13 hens within a flock of 225 animals for a contiguous period of 11 days. Most hens manifested a hen-specific pattern that was (visually) highly consistent across days, though, within that consistency, manifested stark differences between hens. Three different methods were used to classify individual daily datasets into groups based on their similarity: (i) Linear Discriminant Analysis based on six summary variables (transitions into each zone) and total transitions; (ii) Hierarchical Clustering, a naïve clustering analysis technique, applied to summary variables and iii) Hierarchical Clustering applied to dissimilarity matrices produced by Dynamic Time Warping. The three methods correctly classified more than 85% of the hen days and provided a unique means to assess behaviour of a system indicating a considerable degree of complexity and structure. We believe the current effort is the first to document these location and movement patterns within a large, complex commercial system with a large potential to influence the assessment of animal welfare, health, and productivity. Nature Publishing Group UK 2018-08-17 /pmc/articles/PMC6098140/ /pubmed/30120253 http://dx.doi.org/10.1038/s41598-018-29962-x Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Rufener, C.
Berezowski, J.
Maximiano Sousa, F.
Abreu, Y.
Asher, L.
Toscano, M. J.
Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups
title Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups
title_full Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups
title_fullStr Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups
title_full_unstemmed Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups
title_short Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups
title_sort finding hens in a haystack: consistency of movement patterns within and across individual laying hens maintained in large groups
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6098140/
https://www.ncbi.nlm.nih.gov/pubmed/30120253
http://dx.doi.org/10.1038/s41598-018-29962-x
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