Evidence map›Paper›PMID 41732022›Full record

ArticleJournal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie2026

Contribution of Fat Adjustment to Residual Feed Intake Estimation in Beef Cattle.

Larissa Bordin Temp, Letícia Pereira, Marcos Jun-Iti Yokoo, Cintia Righetti Marcondes, Roberto D Sainz, Fernando Bussiman, Jorge Hidalgo, Daniela Lourenco, Fernando Baldi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Larissa Bordin TempDepartamento de Zootecnia, Universidade Estadual Paulista (UNESP), Jaboticabal, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-1003-7977
Letícia PereiraSustainable Livestock Research Center, Animal Science Institute, São José do Rio Preto, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-4450-3470
Marcos Jun-Iti YokooEmbrapa Pecuária Sudeste, São Carlos, São Paulo, Brazil.
Cintia Righetti MarcondesEmbrapa Pecuária Sudeste, São Carlos, São Paulo, Brazil.
Roberto D SainzDepartment of Animal Science, University of California, Davis, California, USA.
Fernando BussimanDepartment of Animal and Dairy Science, University of Georgia, Athens, Georgia, USA.ORCID https://orcid.org/0000-0001-5417-5816
Jorge HidalgoDepartment of Animal and Dairy Science, University of Georgia, Athens, Georgia, USA.ORCID https://orcid.org/0000-0002-0783-381X
Daniela LourencoDepartment of Animal and Dairy Science, University of Georgia, Athens, Georgia, USA.
Fernando BaldiDepartamento de Zootecnia, Universidade de São Paulo, Pirassununga, São Paulo, Brazil.

Funding

Fundação de Amparo à Pesquisa do Estado de São Paulo 2024/17795-0
6 · The paper itself

Abstract

Including fat thickness as a covariate in the regression model used to calculate residual feed intake (RFI) could help preserve carcass quality traits, such as marbling, flavour and juiciness, by accounting for variation in fat deposition. This study aimed to: (1) investigate the benefits of adjusting RFI for rump fat thickness (RFT); (2) estimate variance components and genetic correlations between RFI-calculated with (RFI

Indexed as

Adipose TissueEatingRed MeatAnimal FeedAnimalsBreedingCattleFemaleGenotypeMalePhenotypeBos indicusfeed efficiencygenetic correlationrump fat thickness

Identifiers

PMID41732022
PMCPMC13247628

What OpenQuestion 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 OpenQuestion graph.