Evidence map›Paper›PMID 39765537›Full record

ReviewAnimals : an open access journal from MDPI2024

Exploring Feed Efficiency in Beef Cattle: From Data Collection to Genetic and Nutritional Modeling.

Ayooluwa O Ojo, Henrique A Mulim, Gabriel S Campos, Vinícius Silva Junqueira, Ronald P Lemenager, Jon Patrick Schoonmaker, Hinayah Rojas Oliveira

Abstract readReview
In one paragraph

Review in Animals : an open access journal from MDPI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Yellow Passion Fruit Seed Meal (Animals : an open access journal from MDPI · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ayooluwa O OjoDepartment of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.ORCID 0009-0002-9559-5731
Henrique A MulimDepartment of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.ORCID 0000-0001-8798-8899
Gabriel S CamposDepartment of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.ORCID 0000-0002-7459-824X
Vinícius Silva JunqueiraR&D Department, Bayer Crop Science, Uberlândia 38400-299, Minas Gerais, Brazil.ORCID 0000-0001-7883-1902
Ronald P LemenagerDepartment of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.
Jon Patrick SchoonmakerDepartment of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.
Hinayah Rojas OliveiraDepartment of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.ORCID 0000-0002-0355-8902

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing feed efficiency in beef cattle is critical for meeting the growing global demand for beef while managing rising feed costs and environmental impacts. Challenges in recording feed intake and combining genomic and nutritional models hinder improvements in feed efficiency for sustainable beef production. This review examines the progression from traditional data collection methods to modern genetic and nutritional approaches that enhance feed efficiency. We first discuss the technological advancements that allow precise measurement of individual feed intake and efficiency, providing valuable insights for research and industry. The role of genomic selection in identifying and breeding feed-efficient animals is then explored, emphasizing the benefits of combining data from multiple populations to enhance genomic prediction accuracy. Additionally, the paper highlights the importance of nutritional models that could be used synergistically with genomic selection. Together, these tools allow for optimized feed management in diverse production systems. Combining these approaches also provides a roadmap for reducing input costs and promoting a more sustainable beef industry.

Indexed as

feed intakegenomicsprecision livestock farmingresource managementsustainability

Identifiers

PMID39765537
PMCPMC11672590

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.