Metabolic level recognition of progesterone in dairy Holstein cows using probabilistic models

  • Ludmila N. Turino Laboratorio de Química Fina. INTEC, CONICET-UNL, Predio CCT-CONICET Santa Fe. Ruta Nacional 168, Km 472, 3000 Santa Fe
  • Mariano D. Cristaldi INGAR, CONICET-UTN, Avellaneda 3657, 3000 Santa Fe
  • Rodolfo N. Mariano Laboratorio de Química Fina. INTEC, CONICET-UNL, Predio CCT-CONICET Santa Fe. Ruta Nacional 168, Km 472, 3000 Santa Fe
  • Sonia Boimvaser Laboratorio de Química Fina. INTEC, CONICET-UNL, Predio CCT-CONICET Santa Fe. Ruta Nacional 168, Km 472, 3000 Santa Fe
  • Daniel E. Scandolo INTA. EEA Rafaela. Ruta 34, Km 227, 2300 Rafaela
Keywords: progesterone pharmacokinetic, Hill equation, metabolism, milk yield, Bayesian modeling

Abstract

Administration of exogenous progesterone is widely used in hormonal protocols for estrous (re)synchronization of dairy cattle without regarding pharmacological issues for dose calculation. This happens because it is difficult to estimate the metabolic level of progesterone for each individual cow before administration. In the present contribution, progesterone pharmacokinetics has been determined in lactating Holstein cows with different milk production yields. A Bayesian approach has been implemented to build two probabilistic progesterone pharmacokinetic models for high and low yield dairy cows. Such models are based on a one-compartment Hill structure. Posterior probabilistic models have been structurally set up and parametric probability density functions have been empirically estimated. Moreover, a global sensitivity analysis has been done to know sensitivity profile of each model. Finally, posterior probabilistic models have adequately recognized cow’s progesterone metabolic level in a validation set when Kullback-Leibler based indices were used. These results suggest that milk yield may be a good index for estimating pharmacokinetic level of progesterone.

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Published
2014-05-13
How to Cite
TurinoL. N., CristaldiM. D., MarianoR. N., BoimvaserS., & ScandoloD. E. (2014). Metabolic level recognition of progesterone in dairy Holstein cows using probabilistic models. Spanish Journal of Agricultural Research, 12(2), 396-404. https://doi.org/10.5424/sjar/2014122-5271
Section
Animal breeding, genetics and reproduction