Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis

Detalhes bibliográficos
Autor(a) principal: Ferraz, Patrícia Ferreira Ponciano
Data de Publicação: 2020
Outros Autores: Ferraz, Gabriel Araújo e Silva, Leso, Lorenzo, Klopcic, Marija, Rossi, Giuseppe, Barbari, Matteo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/42544
Resumo: The bedding materials used in dairy cow housing systems are extremely important for animal welfare and performance. A wide range of materials can be used as bedding for dairy cattle, but their physical properties must be analysed to evaluate their potential. In the present study, the physical properties of various bedding materials for dairy cattle were investigated, and different fuzzy clustering algorithms were employed to cluster these materials based on their physical properties. A total of 51 different bedding materials from various places in Europe were collected and tested. Physical analyses were carried out for the following parameters: bulk density (BD), water holding capacity (WHC), air-filled porosity (AFP), global density (GD), container capacity (CC), total effective porosity (TEP), saturated humidity (SH), humidity (H), and average particle size (APS). These data were analysed by principal components analysis (PCA) to reduce the amount of data and, subsequently, by fuzzy clustering analysis. Three clustering algorithms were tested: k-means (KM), fuzzy c-means (FCM) and Gustafson–Kessel (GK) algorithms. Furthermore, different numbers of clusters (2−8) were evaluated and subsequently compared using five validation indexes. The GK clustering algorithm with eight clusters fit better regarding the division of materials according to their properties. From this clustering analysis, it was possible to understand how the physical properties of the bedding materials may influence their behaviour. Among the materials that fit better as bedding materials for dairy cows, Posidonia oceanica (Cluster 6) can be considered an alternative material.
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spelling Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysisAlternative bedding materialCattle housing systemsClustering algorithmWater holding capacitySistemas de alojamento de gadoAlgoritmo de clusteringCapacidade de armazenamento de águaAnimal welfareBem estar animalThe bedding materials used in dairy cow housing systems are extremely important for animal welfare and performance. A wide range of materials can be used as bedding for dairy cattle, but their physical properties must be analysed to evaluate their potential. In the present study, the physical properties of various bedding materials for dairy cattle were investigated, and different fuzzy clustering algorithms were employed to cluster these materials based on their physical properties. A total of 51 different bedding materials from various places in Europe were collected and tested. Physical analyses were carried out for the following parameters: bulk density (BD), water holding capacity (WHC), air-filled porosity (AFP), global density (GD), container capacity (CC), total effective porosity (TEP), saturated humidity (SH), humidity (H), and average particle size (APS). These data were analysed by principal components analysis (PCA) to reduce the amount of data and, subsequently, by fuzzy clustering analysis. Three clustering algorithms were tested: k-means (KM), fuzzy c-means (FCM) and Gustafson–Kessel (GK) algorithms. Furthermore, different numbers of clusters (2−8) were evaluated and subsequently compared using five validation indexes. The GK clustering algorithm with eight clusters fit better regarding the division of materials according to their properties. From this clustering analysis, it was possible to understand how the physical properties of the bedding materials may influence their behaviour. Among the materials that fit better as bedding materials for dairy cows, Posidonia oceanica (Cluster 6) can be considered an alternative material.MDPI2020-08-21T16:35:32Z2020-08-21T16:35:32Z2020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfFERRAZ, P. F. P. et al. Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis. Animals, [S. l.], v. 10, n. 2, p. 1-14, 2020. DOI: https://doi.org/10.3390/ani10020351.http://repositorio.ufla.br/jspui/handle/1/42544Animalsreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessFerraz, Patrícia Ferreira PoncianoFerraz, Gabriel Araújo e SilvaLeso, LorenzoKlopcic, MarijaRossi, GiuseppeBarbari, Matteoeng2023-05-02T18:15:18Zoai:localhost:1/42544Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-02T18:15:18Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis
title Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis
spellingShingle Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis
Ferraz, Patrícia Ferreira Ponciano
Alternative bedding material
Cattle housing systems
Clustering algorithm
Water holding capacity
Sistemas de alojamento de gado
Algoritmo de clustering
Capacidade de armazenamento de água
Animal welfare
Bem estar animal
title_short Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis
title_full Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis
title_fullStr Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis
title_full_unstemmed Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis
title_sort Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis
author Ferraz, Patrícia Ferreira Ponciano
author_facet Ferraz, Patrícia Ferreira Ponciano
Ferraz, Gabriel Araújo e Silva
Leso, Lorenzo
Klopcic, Marija
Rossi, Giuseppe
Barbari, Matteo
author_role author
author2 Ferraz, Gabriel Araújo e Silva
Leso, Lorenzo
Klopcic, Marija
Rossi, Giuseppe
Barbari, Matteo
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Ferraz, Patrícia Ferreira Ponciano
Ferraz, Gabriel Araújo e Silva
Leso, Lorenzo
Klopcic, Marija
Rossi, Giuseppe
Barbari, Matteo
dc.subject.por.fl_str_mv Alternative bedding material
Cattle housing systems
Clustering algorithm
Water holding capacity
Sistemas de alojamento de gado
Algoritmo de clustering
Capacidade de armazenamento de água
Animal welfare
Bem estar animal
topic Alternative bedding material
Cattle housing systems
Clustering algorithm
Water holding capacity
Sistemas de alojamento de gado
Algoritmo de clustering
Capacidade de armazenamento de água
Animal welfare
Bem estar animal
description The bedding materials used in dairy cow housing systems are extremely important for animal welfare and performance. A wide range of materials can be used as bedding for dairy cattle, but their physical properties must be analysed to evaluate their potential. In the present study, the physical properties of various bedding materials for dairy cattle were investigated, and different fuzzy clustering algorithms were employed to cluster these materials based on their physical properties. A total of 51 different bedding materials from various places in Europe were collected and tested. Physical analyses were carried out for the following parameters: bulk density (BD), water holding capacity (WHC), air-filled porosity (AFP), global density (GD), container capacity (CC), total effective porosity (TEP), saturated humidity (SH), humidity (H), and average particle size (APS). These data were analysed by principal components analysis (PCA) to reduce the amount of data and, subsequently, by fuzzy clustering analysis. Three clustering algorithms were tested: k-means (KM), fuzzy c-means (FCM) and Gustafson–Kessel (GK) algorithms. Furthermore, different numbers of clusters (2−8) were evaluated and subsequently compared using five validation indexes. The GK clustering algorithm with eight clusters fit better regarding the division of materials according to their properties. From this clustering analysis, it was possible to understand how the physical properties of the bedding materials may influence their behaviour. Among the materials that fit better as bedding materials for dairy cows, Posidonia oceanica (Cluster 6) can be considered an alternative material.
publishDate 2020
dc.date.none.fl_str_mv 2020-08-21T16:35:32Z
2020-08-21T16:35:32Z
2020
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 FERRAZ, P. F. P. et al. Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis. Animals, [S. l.], v. 10, n. 2, p. 1-14, 2020. DOI: https://doi.org/10.3390/ani10020351.
http://repositorio.ufla.br/jspui/handle/1/42544
identifier_str_mv FERRAZ, P. F. P. et al. Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis. Animals, [S. l.], v. 10, n. 2, p. 1-14, 2020. DOI: https://doi.org/10.3390/ani10020351.
url http://repositorio.ufla.br/jspui/handle/1/42544
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Animals
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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