Metabolic and endocrine variations during peripartum and early lactation in lowland tropical dairy systems

• Autores: Campos-Gaona, Rómulo, Correo-Orozco, Adriana, Vélez-Terranova, Mauricio
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad Nacional Mayor de San Marcos
• Repositorio: Revistas - Universidad Nacional Mayor de San Marcos
• Lenguaje: español
• OAI Identifier: oai:revistasinvestigacion.unmsm.edu.pe:article/27607
• Enlace del recurso: https://revistasinvestigacion.unmsm.edu.pe/index.php/veterinaria/article/view/27607
• Nivel de acceso: acceso abierto
• Materia: dairy cows; homeostasis; mathematics models; metabolism; peripartum; transition period; bovinos lecheros; modelos matemáticos; metabolismo; periparto; periodo de transición

The aim of this study was to characterize the metabolic status of specialized and dual-purpose dairy cows under lowland tropical dairy systems in Colombia, by evaluating body condition, serum concentrations of metabolites and hormones, in the transition period and up to 105 days post-partum, through multivariate analysis techniques. To understand the joint variation of hormones and metabolites evaluated during the experimental phase, the 21 variables under study (haemoglobin, haematocrit, NEFA, BHB, glucose, cholesterol, triglycerides, urea, protein, albumin, globulin, AST, ALT, GGT, body condition, T3, cortisol, insulin, leptin, prolactin, GH), were analysed from a multivariate approach. A cluster analysis and principal component analysis (PCA) were performed to reduce the dimensionality of the information, and to identify the representative variables to explain the variation in the data. It was possible to establish the grouping of the evaluated periods into three clusters, by unifying periods with similar metabolic and hormonal behaviours, with an expected biological sense during and after parturition. The work allowed to know the serum concentrations of metabolites and hormones in the peripartum and first phase of lactation of dairy cows in tropical conditions and their grouping by PCA facilitated the generation of a multivariate evaluation index in the puerperium.