Combining different functions to describe milk, fat, and protein yield in goats using Bayesian multiple-trait random regression models.

@article{Oliveira2016CombiningDF,
  title={Combining different functions to describe milk, fat, and protein yield in goats using Bayesian multiple-trait random regression models.},
  author={Hugo R. Oliveira and Fabyano F. Silva and O H G B D Siqueira and Nei O. Souza and Vinicius Silva Junqueira and Marcos Resende and Rusbel Raul Aspilcueta Borquis and Marcelo Teixeira Rodrigues},
  journal={Journal of animal science},
  year={2016},
  volume={94 5},
  pages={1865-74}
}
We proposed multiple-trait random regression models (MTRRM) combining different functions to describe milk yield (MY) and fat (FP) and protein (PP) percentage in dairy goat genetic evaluation by using Bayesian inference. A total of 3,856 MY, FP, and PP test-day records, measured between 2000 and 2014, from 535 first lactations of Saanen and Alpine goats, including their cross, were used in this study. The initial analyses were performed using the following single-trait random regression models… CONTINUE READING