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Record W4407914409 · doi:10.3390/ani15050664

RETRACTED: Malted Barley as a Potential Feed Supplementation for the Reduction of Enteric Methane Emissions, Rumen Digestibility, and Microbiome Community Changes in Laboratory Conditions

2025· article· en· W4407914409 on OpenAlexaboutno aff
Byeng R. Min, Yutaka Uyeno, Hossam Ismael, Hany Abdo, Santosh Chaudhary, Mariline Hilaire, Vivian Kanyi

Post-publication record

NatureRetraction
ReasonConcerns/Issues about Data;Investigation by Journal/Publisher;Lack of Approval from Third Party;Removed;
Date2/24/2026 0:00
Flagged by OpenAlex?Yes

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenueAnimals · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsRumenMethane emissionsMicrobiomeAnimal scienceBiologyMethaneFood scienceFermentationEcologyBioinformatics

Abstract

fetched live from OpenAlex

Three sets of in vitro rumen fermentation experiments were conducted to determine the effects of diets that included malted barley (MB) and basal diets (grain- and forage-based) on the in vitro gas production, greenhouse gas (GHG) emissions, rumen fermentation profiles, and microbiome changes in the rumen when supplemented with feedlot or dairy rations. The first experiment (Exp. 1) was conducted to evaluate the effects of various levels of MB (0% [referred to as a control], 10%, 20%, and 30%, as-fed basis) supplemented with a grain-based diet in a feedlot ration (2.5 g/bottle) after 48 h ruminal incubation on the in vitro gas production, GHG emissions, and rumen fermentation rate. The second two sets of in vitro experiments (Exp. 2a, b) were conducted to determine (1) the effects of linear dose levels of malted barley (MB; 0%, 10%, 20%, 30%, and 40% as-fed) with two different basal diets (grain-based and forage-based) and (2) the effects of different sources of MB (control, Korean, Canadian, and the USA; 30% MB, as-fed) in a dairy ration after 24 h incubation on in vitro gas production, rumen fermentation profiles, GHG emissions (methane [CH4] and nitrous oxide [N2O]), in vitro dry matter disappearance rate (IVDMD), and microbiome changes. Commercially available α-amylase (0.2 g/100 mL) was used as a sub-control in Exp. 2a. Using gas chromatography, all gases were collected using an ANKOM Gas Production system and analyzed for CH4 and N2O. In Exp. 1, total gas production, cumulative gas, and GHG productions (CH4, N2O) linearly decreased (p ≤ 0.05) with increasing MB supplementation. In Exp. 2a, cumulative in vitro gas, total gas production, and rumen fermentation profiles (e.g., total VFA, acetate, butyrate, iso-butyrate, valerate, and iso-valerate) linearly decreased (p < 0.05–0.01) with increasing MB supplementation, with diet–treatment interactions (p < 0.001). In addition, CH4 and N2O production (mL/g DM) linearly and quadratically decreased (p < 0.01) with increasing MB supplementation across the diets. However, IVDMD linearly and/or quadratically increased (p < 0.01) with increasing MB, with diet–treatment interactions (p < 0.001). The average populations of Bacteroidetes, Proteobacteria, and Spirochaetes were significantly decreased (p < 0.01–0.001) for MB treatment groups compared to the control group. Therefore, it may be possible to suppress methane production directly and indirectly by adding MB and α-amylase by modifying ruminal fermentation profiles.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.999
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.299
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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