Evidence map›Paper›PMID 42058107›Full record

ArticleFrontiers in genetics2026

Different feed efficiency modeling approaches for the prediction of genomic breeding values in lactating dairy cows.

A Chegini, E Negussie, T Kokkonen, M H Lidauer

Abstract read
In one paragraph

Article in Frontiers in genetics, 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

4 authors.

A CheginiNatural Resources Institute Finland (Luke), Jokioinen, Finland.
E NegussieNatural Resources Institute Finland (Luke), Jokioinen, Finland.
T KokkonenDepartment of Agricultural Sciences, University of Helsinki, Helsinki, Finland.
M H LidauerNatural Resources Institute Finland (Luke), Jokioinen, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Feed is the main cost of production in dairy farming. Any improvement in feed efficiency (FE) would increase marginal profit and sustainability and mitigate the environmental impact of dairy farming. In this study, we applied single-step genomic best linear unbiased prediction to different feed-efficiency metrics using records collected from Nordic Red dairy cattle (RDC). The main objective was to compare different metrics in terms of their effectiveness in selecting more feed-efficient animals. Weekly observations (n = 22,071) of dry-matter intake records from 791 RDC cows collected from 1998 to 2021 were used in this study. The pedigree consisted of 5,604 individuals, of which 1,489 animals were genotyped. Different modeling approaches, including conventional residual feed intake (RFI), regression on expected feed intake (ReFI), two multi-trait residual feed efficiency indices (RFI

Indexed as

feed efficiencyprediction accuracyregression on expected feed intakeresidual feed intakesingle-step genomic best linear unbiased prediction

Identifiers

PMID42058107
PMCPMC13124123

What OpenQuestion holds

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Registered trials

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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.