Evidence map›Paper›PMID 36268991›Full record

ArticleJournal of animal science2022

Phenotypic relationship and repeatability of methane emissions and performance traits in beef cattle using a GreenFeed system.

Clodagh V Ryan, Thierry Pabiou, Deirdre C Purfield, Stephen Conroy, Stuart F Kirwan, John J Crowley, Craig P Murphy, Ross D Evans

Open access · hybridAbstract read
In one paragraph

Article in Journal of animal science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
5.4field-weighted citation impact, top 4% of its field
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

17 citing papers in PubMed, 26 citations in OpenAlex.

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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

8 authors at 3 institutions in 2 countries.

Clodagh V RyanIrish Cattle Breeding Federation, Ballincollig, Co. Cork, Ireland.ORCID 0000-0003-2788-2210
Thierry PabiouIrish Cattle Breeding Federation, Ballincollig, Co. Cork, Ireland.
Deirdre C PurfieldDepartment of Biological Sciences, Munster Technological University, Bishopstown, Co. Cork, Ireland.
Stephen ConroyIrish Cattle Breeding Federation, Ballincollig, Co. Cork, Ireland.
Stuart F KirwanAnimal Bioscience Research Centre, Teagasc Grange, Dunsany, Co. Meath, Ireland.
John J CrowleyAbacusBio Ltd., Dunedin 9016, New Zealand.
Craig P MurphyDepartment of Biological Sciences, Munster Technological University, Bishopstown, Co. Cork, Ireland.ORCID 0000-0002-6064-2211
Ross D EvansIrish Cattle Breeding Federation, Ballincollig, Co. Cork, Ireland.
Munster Technological University · IETeagasc - The Irish Agriculture and Food Development Authority · IEUniversity of Alberta · CA

Funding

Department of Agriculture, Food and the Marine STILMULUS fund project "GreenBreed" 17/S/235FACCE ERA-GAS "RumenPredict" 16/RD/ERAGAS/1RUMENPREDICT-ROI2017Horizon 2020 "MASTER" 818368Irish Research Council Employment-Based Postgraduate Programme EBPPG/2020/44
6 · The paper itself

Abstract

Rumen methanogenesis results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits. Methane and carbon dioxide (CO2) data recorded via multiple GreenFeed Emission Monitoring (GEM), systems as well as feed intake, live weight, ultrasound scanning data, and slaughter data were available on 1,099 animals destined for beef production, of which 648 were steers, 361 were heifers, and 90 were bulls. Phenotypic relationships between GEM emission measurements with feed intake, weight traits, muscle ultrasound data, and carcass traits were estimated. Utilization of GEM systems, daily patterns of methane output, and repeatability of GEM system measurements across averaging periods were also assessed. Methane concentrations varied with visit number, duration, and time of day of visit to the GEM system. Mean CH4 and CO2 varied between sex, with mean CH4 of 256.1 g/day ± 64.23 for steers, 234.7 g/day ± 59.46 for heifers, and 156.9 g/day ± 55.98 for young bulls. A 10-d average period of GEM system measurements were required for steers and heifers to achieve a minimum repeatability of 0.60; however, higher levels of repeatability were observed in animals that attended the GEM system more frequently. In contrast, CO2 emissions reached repeatability estimates >0.6 for steers and heifers in all averaging periods greater than 2-d, suggesting that cattle have a moderately consistent CO2 emission pattern across time periods. Animals with heavier bodyweights were observed to have higher levels of CH4 (correlation = 0.30) and CO2 production (correlation = 0.61), and when assessing direct methane, higher levels of dry matter intake were associated with higher methane output (correlation = 0.31). Results suggest that reducing CH4 can have a negative impact on growth and body composition of cattle. Methane ratio traits, such as methane yield and intensity were also evaluated, and while easy to understand and compare across populations, ratio traits are undesirable in animal breeding, due to the unpredictable level of response. Methane adjusted for dry matter intake and liveweight (Residual CH4) should be considered as an alternative emission trait when selecting for reduced emissions within breeding goals.

Indexed as

Greenhouse GasesMethaneAnimal FeedAnimalsCattleDietEatingFemaleMaleRumenGreenhouse GasesMethanebeef cattlecorrelationGreenFeedgreenhouse gasmethanerepeatability

Identifiers

PMID36268991
PMCPMC9733524
OpenAlexW4306989185

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.