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Record W1990147743 · doi:10.3168/jds.2014-8348

Short communication: Use of a portable, automated, open-circuit gas quantification system and the sulfur hexafluoride tracer technique for measuring enteric methane emissions in Holstein cows fed ad libitum or restricted

2015· article· en· W1990147743 on OpenAlexaff
Christopher D. Dorich, R. K. Varner, A.B.D. Pereira, R. Martineau, K.J. Soder, A.F. Brito

Bibliographic record

VenueJournal of Dairy Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersNational Institute of Food and AgricultureAgricultural Research ServiceUniversidade Estadual de Santa CruzNew Hampshire Agricultural Experiment StationUniversidade Federal de ViçosaU.S. Department of Agriculture
KeywordsBarnAnimal scienceDry matterMilkingSilageChemistrySulfur hexafluorideFood scienceBiology

Abstract

fetched live from OpenAlex

The objective of this study was to measure enteric CH4 emissions using a new portable automated open-circuit gas quantification system (GQS) and the sulfur hexafluoride tracer technique (SF6) in midlactation Holstein cows housed in a tiestall barn. Sixteen cows averaging 176 ± 34 d in milk, 40.7 ± 6.1 kg of milk yield, and 685 ± 49 kg of body weight were randomly assigned to 1 out of 2 treatments according to a crossover design. Treatments were (1) ad libitum (adjusted daily to yield 10% orts) and (2) restricted feed intake [set to restrict feed by 10% of baseline dry matter intake (DMI)]. Each experimental period lasted 22d, with 14 d for treatment adaptation and 8d for data and sample collection. A common diet was fed to the cows as a total mixed ration and contained 40.4% corn silage, 11.2% grass-legume haylage, and 48.4% concentrate on a dry matter basis. Spot 5-min measurements using the GQS were taken twice daily with a 12-h interval between sampling and sampling times advanced 2h daily to account for diurnal variation in CH4 emissions. Canisters for the SF6 method were sampled twice daily before milking with 4 local background gas canisters inside the barn analyzed for background gas concentrations. Enteric CH4 emissions were not affected by treatments and averaged 472 and 458 g/d (standard error of the mean = 18 g/d) for ad libitum and restricted intake treatments, respectively (data not shown). The GQS appears to be a reliable method because of the relatively low coefficients of variation (ranging from 14.1 to 22.4%) for CH4 emissions and a moderate relationship (coefficient of determination = 0.42) between CH4 emissions and DMI. The SF6 resulted in large coefficients of variation (ranging from 16.0 to 111%) for CH4 emissions and a poor relationship (coefficient of determination = 0.17) between CH4 emissions and DMI, likely because of limited barn ventilation and high background gas concentration. Research with improved barn ventilation systems or outdoors is warranted to further assess the GQS and SF6 methodologies.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.154
GPT teacher head0.316
Teacher spread0.162 · 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

Citations40
Published2015
Admission routes1
Has abstractyes

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