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

Autores
Rearte, Ramiro; Lorenti, Santiago Nicolas; Dominguez, German; de la Sota, Rodolfo Luzbel; Lacau, 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.
Fil: Rearte, Ramiro. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Teriogenología. Cátedra de Reproducción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lorenti, Santiago Nicolas. No especifíca;
Fil: Dominguez, German. No especifíca;
Fil: de la Sota, Rodolfo Luzbel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Teriogenología. Cátedra de Reproducción Animal; Argentina
Fil: Lacau, Isabel María. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Giuliodori, Mauricio Javier. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Departamento de Ciencias Básicas. Cátedra de Fisiología; Argentina
Materia
ANESTRUS RATE
BODY CONDITION SCORING
DAIRY HERD
MONITORING RISK FACTORS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/223495
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/223495
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd LevelRearte, RamiroLorenti, Santiago NicolasDominguez, Germande la Sota, Rodolfo LuzbelLacau, Isabel MaríaGiuliodori, Mauricio JavierANESTRUS RATEBODY CONDITION SCORINGDAIRY HERDMONITORING RISK FACTORShttps://purl.org/becyt/ford/4.3https://purl.org/becyt/ford/4A 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.Fil: Rearte, Ramiro. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Teriogenología. Cátedra de Reproducción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lorenti, Santiago Nicolas. No especifíca;Fil: Dominguez, German. No especifíca;Fil: de la Sota, Rodolfo Luzbel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Teriogenología. Cátedra de Reproducción Animal; ArgentinaFil: Lacau, Isabel María. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Giuliodori, Mauricio Javier. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Departamento de Ciencias Básicas. Cátedra de Fisiología; ArgentinaMultidisciplinary Digital Publishing Institute2023-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/223495Rearte, Ramiro; Lorenti, Santiago Nicolas; Dominguez, German; de la Sota, Rodolfo Luzbel; Lacau, Isabel María; et al.; Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level; Multidisciplinary Digital Publishing Institute; Animals; 13; 19; 10-2023; 1-112076-2615CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3390/ani13193114info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-12T10:00:38Zoai:ri.conicet.gov.ar:11336/223495instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-11-12 10:00:38.991CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
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
ANESTRUS RATE
BODY CONDITION SCORING
DAIRY HERD
MONITORING RISK FACTORS
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 Nicolas
Dominguez, German
de la Sota, Rodolfo Luzbel
Lacau, Isabel María
Giuliodori, Mauricio Javier
author Rearte, Ramiro
author_facet Rearte, Ramiro
Lorenti, Santiago Nicolas
Dominguez, German
de la Sota, Rodolfo Luzbel
Lacau, Isabel María
Giuliodori, Mauricio Javier
author_role author
author2 Lorenti, Santiago Nicolas
Dominguez, German
de la Sota, Rodolfo Luzbel
Lacau, Isabel María
Giuliodori, Mauricio Javier
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv ANESTRUS RATE
BODY CONDITION SCORING
DAIRY HERD
MONITORING RISK FACTORS
topic ANESTRUS RATE
BODY CONDITION SCORING
DAIRY HERD
MONITORING RISK FACTORS
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.3
https://purl.org/becyt/ford/4
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 ≥ 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.
Fil: Rearte, Ramiro. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Teriogenología. Cátedra de Reproducción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lorenti, Santiago Nicolas. No especifíca;
Fil: Dominguez, German. No especifíca;
Fil: de la Sota, Rodolfo Luzbel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Teriogenología. Cátedra de Reproducción Animal; Argentina
Fil: Lacau, Isabel María. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Giuliodori, Mauricio Javier. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Departamento de Ciencias Básicas. Cátedra de Fisiología; Argentina
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 ≥ 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.
publishDate 2023
dc.date.none.fl_str_mv 2023-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11336/223495
Rearte, Ramiro; Lorenti, Santiago Nicolas; Dominguez, German; de la Sota, Rodolfo Luzbel; Lacau, Isabel María; et al.; Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level; Multidisciplinary Digital Publishing Institute; Animals; 13; 19; 10-2023; 1-11
2076-2615
CONICET Digital
CONICET
url http://hdl.handle.net/11336/223495
identifier_str_mv Rearte, Ramiro; Lorenti, Santiago Nicolas; Dominguez, German; de la Sota, Rodolfo Luzbel; Lacau, Isabel María; et al.; Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level; Multidisciplinary Digital Publishing Institute; Animals; 13; 19; 10-2023; 1-11
2076-2615
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3390/ani13193114
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1848598490938081280
score 13.24909

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