Evaluation of the physical properties of bedding materials for dairy cattle using fuzzy clustering analysis
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
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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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 |
_version_ |
1807835221678096384 |