Evidence map›Paper›PMID 40685255›Full record

ArticleJournal of animal science2025

Unraveling factors influencing the variability and repeatability of greenhouse gases measured through an automated head chamber system in grazing cattle in commercial conditions.

Pablo Guarnido-Lopez, Hector Manuel Menendez, Aletta Husmann, Ira Parsons, Andrew Antaya, Jameson Brennan, Luis Orlindo Tedeschi

Abstract read
In one paragraph

Article in Journal of animal science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Pablo Guarnido-LopezDepartment of Animal Science, Texas A&M University, College Station, TX 77843.ORCID 0000-0002-5013-0888
Hector Manuel MenendezDepartment of Animal Science, South Dakota State University, Rapid City, SD 57702.ORCID 0000-0001-9092-7237
Aletta HusmannDepartment of Animal Science, South Dakota State University, Rapid City, SD 57702.
Ira ParsonsDepartment of Animal Science, South Dakota State University, Rapid City, SD 57702.ORCID 0000-0001-8813-4190
Andrew AntayaDepartment of Animal Science, South Dakota State University, Rapid City, SD 57702.
Jameson BrennanDepartment of Animal Science, South Dakota State University, Rapid City, SD 57702.
Luis Orlindo TedeschiDepartment of Animal Science, Texas A&M University, College Station, TX 77843.

Funding

USDA-AFRI IDEAS NR233A750004G018
6 · The paper itself

Abstract

Global concern about the environmental impact of livestock production has been increasing over the past decade; consequently, research has focused on mitigating these emissions. Among all devices deployed to access greenhouse gases (GHG), the GreenFeed (GF) system is the most used for grazing systems. Nonetheless, the primary issue about GF use is its higher variability and the low repeatability (R) of GHG measurements in grazing individuals compared to other methods. Thus, this work aimed to assess both environmental and animal factors, as well as the variability of the GF itself, to explain GHG variability in cattle. These evaluations are usually conducted under experimental conditions, but in this work, both the variability and R values of CH4 were analyzed under commercial settings. Three and two GF units were deployed simultaneously in a dry lot and then in a grazing pasture, respectively, on a commercial cattle ranch. To evaluate the variability and R values of GHG, the GF collected enteric emissions, wind speed, wind direction, temperature, and animal data from 175 and 169 Angus heifers in dry lot and pasture settings, respectively. Variance component analyses were used to evaluate the influence of these factors on the GHG measurements. Results showed a coefficient of variation (CV) of CH4 and CO2 measured through the GF of 32% and 20%, respectively. Of the total CH4 variation in grazing conditions, 2.73% was explained by environmental factors and 38.3% was explained by animal factors, including feeding behavior (4.58%), between-animal variation (16.4%), date of the visit (12.5%), hour of the visits (3.05%), visits' duration (1.78%), and number of visits/day (1.25%). In contrast, in the dry lot, environmental and animal factors explained 7.49% and 8.58% of the CH4 variation, respectively. Finally, the GF equipment itself explained 0.15% and 2.06% of the variation of the CH4 in the grazing and dry lot conditions, respectively. The R values, measured as the animal variance divided by the sum of animal and error variances, increased linearly (0.094 to 0.23) in the dry lot, while in the grazing settings, it decreased linearly (0.098 to 0.056) from days 1 to 21. This study identified the most influential factors contributing to the variability of GHG emissions and the low R values of CH4 in commercial grazing cattle production, paving the way for enhanced future use of GF devices for reporting GHG emissions in grazing systems.

Indexed as

Air PollutantsAnimal HusbandryCarbon DioxideEnvironmental MonitoringGreenhouse GasesMethaneAnimalsCattleFemaleReproducibility of ResultsAir PollutantsCarbon DioxideGreenhouse GasesMethanebeefenteric emissionsevaluationgrazingruminant

Identifiers

PMID40685255
PMCPMC12314600

What Socratic holds

Textmetadata
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.