ASAS–NANP symposium: Mathematical modeling in animal nutrition: Integrating insight and uncertainty: Bayesian modeling for data-rich livestock systems

Ira L Parsons, Hector M Menendez, Gordon E Carstens, Jameson R Brennan

Open source

DOI: 10.1093/jas/skag307
Published: 2026
Container: Journal of Animal Science
Publisher: Oxford University Press (OUP)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1093/jas/skag307,
  title = {ASAS–NANP symposium: Mathematical modeling in animal nutrition: Integrating insight and uncertainty: Bayesian modeling for data-rich livestock systems},
  author = {Ira L Parsons and Hector M Menendez and Gordon E Carstens and Jameson R Brennan},
  year = {2026},
  journal = {Journal of Animal Science},
  doi = {10.1093/jas/skag307},
  url = {https://doi.org/10.1093/jas/skag307}
}

RIS

TY  - JOUR
TI  - ASAS–NANP symposium: Mathematical modeling in animal nutrition: Integrating insight and uncertainty: Bayesian modeling for data-rich livestock systems
AU  - Ira L Parsons
AU  - Hector M Menendez
AU  - Gordon E Carstens
AU  - Jameson R Brennan
PY  - 2026
JO  - Journal of Animal Science
DO  - 10.1093/jas/skag307
UR  - https://doi.org/10.1093/jas/skag307
ER  -

APA

Parsons, I. L., Menendez, H. M., Carstens, G. E., & Brennan, J. R. (2026). ASAS–NANP symposium: Mathematical modeling in animal nutrition: Integrating insight and uncertainty: Bayesian modeling for data-rich livestock systems. Journal of Animal Science. https://doi.org/10.1093/jas/skag307

Source records

crossref · retrieved 2026-11-10T15:02:29.204Z