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Record W2252936167 · doi:10.1071/an15509

Relationships between milk fatty acid profiles and enteric methane production in dairy cattle fed grass- or grass silage-based diets

2016· article· en· W2252936167 on OpenAlexaff
J. Dijkstra, Sanne van Gastelen, E.C. Antunes-Fernandes, D. Warner, B. Hatew, G. Klop, S.C. Podesta, Henk J. van Lingen, Kasper Hettinga, A. Bannink

Bibliographic record

VenueAnimal Production Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSilageDry matterChemistryFatty acidAnimal scienceDairy cattleFood scienceMethaneAgronomyBiologyBiochemistry

Abstract

fetched live from OpenAlex

We quantified relationships between methane production and milk fatty acid (FA) profile in dairy cattle fed grass- or grass silage-based diets, and determined whether recent prediction equations for methane, based on a wide variety of diets, are applicable to grass- and grass silage-based diets. Data from three studies were used, encompassing four grass herbage and 14 grass silage treatments and 132 individual cow observations. Methane production was measured using respiration chambers and milk fatty acids (FAs) analysed using gas chromatography. The proportion of grass or grass silage (dry matter (DM) basis) was 0.80 ± 0.037. Methane yield averaged 22.3 ± 2.10 g/kg DM intake (DMI) and 14.2 ± 2.90 g/kg fat- and protein-corrected milk (FPCM). Mixed model univariate regression including a random study effect on intercept was applied to predict methane yield, with individual milk FA concentrations (g/100 g FA) as fixed effects. Of the 42 milk FAs identified, no single FA had a strong positive correlation (r; strong correlation defined as |r| = 0.50) with methane yield (g/kg DMI), and cis-12 C18:1 and cis-9,12,15 C18:3 had a strong negative correlation with methane yield (g/kg DMI). C14:0 iso, C15:0, C15:0 iso, C15:0 anteiso, C16:0, C20:0, cis-11,14 C20:2, cis-5,8,11,14 C20:4, C22:0, cis-7,10,13,16,19 C22:5 and C24:0 had a strong positive correlation with methane yield (g/kg FPCM), and trans-15+cis-11 C18:1, cis-9 C18:1, and cis-11 C20:1 had a strong negative correlation with methane yield (g/kg FPCM). Observed methane yield was compared with methane yield predicted by the equations of van Lingen et al. (2014; Journal of Dairy Science97, 7115–7132). These equations did not accurately predict methane yield as grams per kilogram DMI (concordance correlation coefficient (CCC) = 0.13) or as grams per kilogram FPCM (CCC = 0.22), in particular related to large differences in standard deviation between predicted and observed values. In conclusion, quantitative relationships between milk FA profile and methane yield in cattle fed grass- or grass silage-based diets differ from those determined for other types of diets.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.079
GPT teacher head0.286
Teacher spread0.207 · 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 designObservational
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

Citations19
Published2016
Admission routes1
Has abstractyes

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