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

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...

ver descrição completa

Detalhes bibliográficos
Autores: Rearte, Ramiro, Lorenti, Santiago Nicolas, Dominguez, German, de la Sota, Rodolfo Luzbel, Lacau, Isabel María, Giuliodori, Mauricio Javier
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:Argentina
Recursos:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/223495
Acesso em linha:http://hdl.handle.net/11336/223495
Access Level:acceso abierto
Palavra-chave:ANESTRUS RATE
BODY CONDITION SCORING
DAIRY HERD
MONITORING RISK FACTORS
https://purl.org/becyt/ford/4.3
https://purl.org/becyt/ford/4
Descrição
Resumo: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.