Characterising Free-Range Layer Flocks Using Unsupervised Cluster Analysis.

aviary eggs individual pasture poultry radio frequency identification (RFID) spatial technology time budget variation welfare

Journal

Animals : an open access journal from MDPI
ISSN: 2076-2615
Titre abrégé: Animals (Basel)
Pays: Switzerland
ID NLM: 101635614

Informations de publication

Date de publication:
15 May 2020
Historique:
received: 15 04 2020
revised: 06 05 2020
accepted: 13 05 2020
entrez: 21 5 2020
pubmed: 21 5 2020
medline: 21 5 2020
Statut: epublish

Résumé

This study aimed to identify sub-populations of free-range laying hens and describe the pattern of their resource usage, which can affect hen performance and welfare. In three commercial flocks, 3125 Lohmann Brown hens were equipped with radio-frequency identification (RFID) transponder leg bands and placed with their flock companions, resulting in a total of 40,000 hens/flock. Hens were monitored for their use of the aviary system, including feeder lines, nest boxes, and the outdoor range. K-means and agglomerative cluster analysis, optimized with the Calinski-Harabasz Criterion, was performed and identified three clusters. Individual variation in time duration was observed in all the clusters with the highest individual differences observed on the upper feeder (140 ± 1.02%) and the range (176 ± 1.03%). Hens of cluster 1 spent the least amount time on the range and the most time on the feed chain located at the upper aviary tier (

Identifiants

pubmed: 32429144
pii: ani10050855
doi: 10.3390/ani10050855
pmc: PMC7278471
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Australian Eggs
ID : 1UN151

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

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Auteurs

Terence Zimazile Sibanda (TZ)

School of Environmental and Rural Science, Faculty of Science, Agriculture, Business and Law, University of New England, Armidale, NSW 2351, Australia.

Mitchell Welch (M)

Precision Agriculture Research Group, Faculty of Science, Agriculture, Business and Law, School of Science and Technology, University of New England, Armidale, NSW 2351, Australia.

Derek Schneider (D)

Precision Agriculture Research Group, Faculty of Science, Agriculture, Business and Law, School of Science and Technology, University of New England, Armidale, NSW 2351, Australia.

Manisha Kolakshyapati (M)

School of Environmental and Rural Science, Faculty of Science, Agriculture, Business and Law, University of New England, Armidale, NSW 2351, Australia.

Isabelle Ruhnke (I)

School of Environmental and Rural Science, Faculty of Science, Agriculture, Business and Law, University of New England, Armidale, NSW 2351, Australia.

Classifications MeSH