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Record W170280638 · doi:10.2527/2004.82113346x

Methane emissions from beef cattle: Effects of monensin, sunflower oil, enzymes, yeast, and fumaric acid1

2004· article· en· W170280638 on OpenAlexaffabout
S. M. McGinn, K. A. Beauchemin, Trevor Coates, D. Colombatto

Bibliographic record

VenueJournal of Animal Science · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsMonensinAnimal scienceBeef cattleChemistryMethaneFumaric acidCarbon dioxideTotal mixed rationGreenhouse gasSunflower oilLatin squareFood scienceDistillers grainsFermentationBiologyRumenBiochemistry

Abstract

fetched live from OpenAlex

Methane emitted from the livestock sector contributes to greenhouse gas (GHG) emissions. Understanding the effects of diet on enteric methane production can help refine GHG emission inventories and identify viable GHG reduction strategies. Our study focused on measuring methane and carbon dioxide emissions, total-tract digestibility, and ruminal fermentation in growing beef cattle fed a diet supplemented with various additives or ingredients. Two experiments, each designed as a 4 x 4 Latin square with 21-d periods, were conducted using 16 Holstein steers (initial BW 311.6 +/- 12.3 kg). In Exp. 1, treatments were control (no additive), monensin (Rumensin, Elanco Animal Health, Indianapolis, IN; 33 mg/kg DM), sunflower oil (400 g/d, approximately 5% of DMI), and proteolytic enzyme (Protex 6-L, Genencor Int., Inc., CA; 1 mL/kg DM). In Exp. 2, treatments were control (no additive), Procreatin-7 yeast (Prince Agri Products, Inc., Quincy, IL; 4 g/d), Levucell SC yeast (Lallemand, Inc., Rexdale, Ontario, Canada; 1 g/d), and fumaric acid (Bartek Ingredients Inc., Stoney Creek, Ontario, Canada; 80 g/d). The basal diet consisted of 75% barley silage, 19% steam-rolled barley grain, and 6% supplement (DM basis). Four large chambers (two animals per chamber) were equipped with lasers and infrared gas analyzers to measure methane and carbon dioxide, respectively, for 3 d each period. Total-tract digestibility was determined using chromic oxide. Approximately 6.5% of the GE consumed was lost in the form of methane emissions from animals fed the control diet. In Exp. 1, sunflower oil decreased methane emissions by 22% (P = 0.001) compared with the control, whereas monensin (P = 0.44) and enzyme had no effect (P = 0.82). However, oil decreased (P = 0.03) the total-tract digestibility of NDF by 20%. When CH(4) emissions were corrected for differences in energy intake, the loss of GE to methane was decreased by 21% (P = 0.002) using oil and by 9% (P = 0.09) using monensin. In Exp. 2, Procreatin-7 yeast (P = 0.72), Levucell SC yeast (P = 0.28), and fumaric acid (P = 0.21) had no effect on methane emissions, although emissions as a percentage of GE intake were 3% (non-significant, P = 0.39) less for steers fed Procreatin-7 yeast compared with the control. This study demonstrates that sunflower oil, ionophores, and possibly some yeast products can be used to decrease the GE lost as methane from cattle, but fiber digestibility is impaired with oil supplementation.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

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

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 head0.014
GPT teacher head0.243
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations475
Published2004
Admission routes2
Has abstractyes

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