Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level

Autores
Rearte, Ramiro; Lorenti, Santiago Nicolás; Dominguez, Germán; Sota, Rodolfo Luzbel de la; Lacau-Mengido, Isabel María; Giuliodori, Mauricio Javier
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A retrospective longitudinal study assessing the explanatory and predictive capacity of body condition score (BCS) in dairy cows on disease risk at the individual and herd level was carried out. Data from two commercial grazing herds from the Argentinean Pampa were gathered (Herd A = 2100 and herd B = 2600 milking cows per year) for 4 years. Logistic models were used to assess the association of BCS indicators with the odds for anestrus at the cow and herd level. Population attributable fraction (AFP) was estimated to assess the anestrus rate due to BCS indicators. We found that anestrus risk decreased in cows calving with BCS >= 3 and losing <= 0.5 (OR: 0.07–0.41), and that anestrus rate decreased in cohorts with a high frequency of cows with proper BCS (OR: 0.22–0.45). Despite aggregated data having a good explanatory power, their predictive capacity for anestrus rate at the herd level is poor (AUC: 0.574–0.679). The AFP varied along the study in both herds and tended to decrease every time the anestrous rate peaked. We conclude that threshold-based models with BCS indicators as predictors are useful to understand disease risk (e.g., anestrus), but conversely, they are useless to predict such multicausal disease events at the herd level.
Facultad de Ciencias Veterinarias
Consejo Nacional de Investigaciones Científicas y Técnicas
Materia
Ciencias Veterinarias
body condition scoring
anestrus rate
monitoring risk factors
dairy herd
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/159475

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network_name_str SEDICI (UNLP)
spelling Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd LevelRearte, RamiroLorenti, Santiago NicolásDominguez, GermánSota, Rodolfo Luzbel de laLacau-Mengido, Isabel MaríaGiuliodori, Mauricio JavierCiencias Veterinariasbody condition scoringanestrus ratemonitoring risk factorsdairy herdA retrospective longitudinal study assessing the explanatory and predictive capacity of body condition score (BCS) in dairy cows on disease risk at the individual and herd level was carried out. Data from two commercial grazing herds from the Argentinean Pampa were gathered (Herd A = 2100 and herd B = 2600 milking cows per year) for 4 years. Logistic models were used to assess the association of BCS indicators with the odds for anestrus at the cow and herd level. Population attributable fraction (AFP) was estimated to assess the anestrus rate due to BCS indicators. We found that anestrus risk decreased in cows calving with BCS &gt;= 3 and losing &lt;= 0.5 (OR: 0.07–0.41), and that anestrus rate decreased in cohorts with a high frequency of cows with proper BCS (OR: 0.22–0.45). Despite aggregated data having a good explanatory power, their predictive capacity for anestrus rate at the herd level is poor (AUC: 0.574–0.679). The AFP varied along the study in both herds and tended to decrease every time the anestrous rate peaked. We conclude that threshold-based models with BCS indicators as predictors are useful to understand disease risk (e.g., anestrus), but conversely, they are useless to predict such multicausal disease events at the herd level.Facultad de Ciencias VeterinariasConsejo Nacional de Investigaciones Científicas y Técnicas2023-10-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/159475enginfo:eu-repo/semantics/altIdentifier/issn/2076-2615info:eu-repo/semantics/altIdentifier/doi/10.3390/ani13193114info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-11-12T11:06:01Zoai:sedici.unlp.edu.ar:10915/159475Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-11-12 11:06:01.398SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level
title Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level
spellingShingle Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level
Rearte, Ramiro
Ciencias Veterinarias
body condition scoring
anestrus rate
monitoring risk factors
dairy herd
title_short Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level
title_full Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level
title_fullStr Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level
title_full_unstemmed Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level
title_sort Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level
dc.creator.none.fl_str_mv Rearte, Ramiro
Lorenti, Santiago Nicolás
Dominguez, Germán
Sota, Rodolfo Luzbel de la
Lacau-Mengido, Isabel María
Giuliodori, Mauricio Javier
author Rearte, Ramiro
author_facet Rearte, Ramiro
Lorenti, Santiago Nicolás
Dominguez, Germán
Sota, Rodolfo Luzbel de la
Lacau-Mengido, Isabel María
Giuliodori, Mauricio Javier
author_role author
author2 Lorenti, Santiago Nicolás
Dominguez, Germán
Sota, Rodolfo Luzbel de la
Lacau-Mengido, Isabel María
Giuliodori, Mauricio Javier
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Veterinarias
body condition scoring
anestrus rate
monitoring risk factors
dairy herd
topic Ciencias Veterinarias
body condition scoring
anestrus rate
monitoring risk factors
dairy herd
dc.description.none.fl_txt_mv A retrospective longitudinal study assessing the explanatory and predictive capacity of body condition score (BCS) in dairy cows on disease risk at the individual and herd level was carried out. Data from two commercial grazing herds from the Argentinean Pampa were gathered (Herd A = 2100 and herd B = 2600 milking cows per year) for 4 years. Logistic models were used to assess the association of BCS indicators with the odds for anestrus at the cow and herd level. Population attributable fraction (AFP) was estimated to assess the anestrus rate due to BCS indicators. We found that anestrus risk decreased in cows calving with BCS &gt;= 3 and losing &lt;= 0.5 (OR: 0.07–0.41), and that anestrus rate decreased in cohorts with a high frequency of cows with proper BCS (OR: 0.22–0.45). Despite aggregated data having a good explanatory power, their predictive capacity for anestrus rate at the herd level is poor (AUC: 0.574–0.679). The AFP varied along the study in both herds and tended to decrease every time the anestrous rate peaked. We conclude that threshold-based models with BCS indicators as predictors are useful to understand disease risk (e.g., anestrus), but conversely, they are useless to predict such multicausal disease events at the herd level.
Facultad de Ciencias Veterinarias
Consejo Nacional de Investigaciones Científicas y Técnicas
description A retrospective longitudinal study assessing the explanatory and predictive capacity of body condition score (BCS) in dairy cows on disease risk at the individual and herd level was carried out. Data from two commercial grazing herds from the Argentinean Pampa were gathered (Herd A = 2100 and herd B = 2600 milking cows per year) for 4 years. Logistic models were used to assess the association of BCS indicators with the odds for anestrus at the cow and herd level. Population attributable fraction (AFP) was estimated to assess the anestrus rate due to BCS indicators. We found that anestrus risk decreased in cows calving with BCS &gt;= 3 and losing &lt;= 0.5 (OR: 0.07–0.41), and that anestrus rate decreased in cohorts with a high frequency of cows with proper BCS (OR: 0.22–0.45). Despite aggregated data having a good explanatory power, their predictive capacity for anestrus rate at the herd level is poor (AUC: 0.574–0.679). The AFP varied along the study in both herds and tended to decrease every time the anestrous rate peaked. We conclude that threshold-based models with BCS indicators as predictors are useful to understand disease risk (e.g., anestrus), but conversely, they are useless to predict such multicausal disease events at the herd level.
publishDate 2023
dc.date.none.fl_str_mv 2023-10-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/159475
url http://sedici.unlp.edu.ar/handle/10915/159475
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/2076-2615
info:eu-repo/semantics/altIdentifier/doi/10.3390/ani13193114
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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