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Record W3109462323 · doi:10.1093/jas/skaa278.241

175 Effect of age at calving on greenhouse gas emissions from simulated beef farms grazing four stockpiled forage species in late fall/early winter

2020· article· en· W3109462323 on OpenAlexaffabout
Megan E Donnelly, Kim Ominski, E. J. McGeough, K. M. Wittenberg, Getahun Legesse

Bibliographic record

VenueJournal of Animal Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIce calvingGrazingForageGreenhouse gasAnimal scienceHerdAgronomyEnvironmental scienceBeef cattleWeaningBiologyLactationEcology

Abstract

fetched live from OpenAlex

Abstract The impact of age at first calving (2 versus 3 yrs) and type of forage species grazed in late fall/early winter on lifetime greenhouse gas (GHG) emissions from a cow-calf herd over an 8 or 9 yr period was examined. Farm simulations, based in Manitoba, Canada, were assessed using the Holos model to determine whole-farm GHG emissions for each scenario. The baseline herd consisted of 170 cows, 6 bulls, and their progeny which were sold at weaning, apart from herd replacements. Each simulation began with 207 newborn, female calves, with GHG emissions measured annually. From October to December, 1 of 4 stockpiled forages/forage mixtures were grazed: i) standing corn (COR), ii) tall fescue/meadow bromegrass (TFM), iii) orchardgrass/alfalfa (OGA), and iv) tall fescue/alfalfa/cicer milkvetch (TAC). All other feeding phase diets did not differ across all scenarios. Herd GHG emissions (Mg CO2e) were lower with heifers calving at 2 yrs (3,938 ± 71 Mg CO2e) versus 3 yrs (4,634 ± 72 Mg CO2e). Enteric methane (CH4) was the largest source of GHG emissions accounting for 66% of the total in both the 2- and 3-yr scenarios. Average enteric CH4 values were 3,820±61, 4,251 ± 68, 4,887±79, and 4,220 ± 68 Mg CO2e for simulations grazing COR, TFM, OGA, and TAC, respectively and were inversely related to total digestible nutrient (TDN) content of the forage mixtures with 72, 54, 45 and 55% TDN. Emissions were highest from OGA, the lowest quality forage, in both calving scenarios. Nitrous oxide emissions from livestock manure were the second highest contributing source, representing 15% of total emissions. Reducing age at first calving (2 versus 3 yrs) and providing higher energy forage in late fall/early winter reduced cow-calf GHG emissions. The adoption of management strategies such as reducing age at first calving and improving forage quality for extended grazing may reduce emissions from the cow-calf sector.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.314

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.240
Teacher spread0.225 · 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 designSimulation or modeling
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

Citations1
Published2020
Admission routes2
Has abstractyes

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