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Record W3134068954 · doi:10.3168/jds.2020-18853

Corn silage-based diet supplemented with increasing amounts of linseed oil: Effects on methane production, rumen fermentation, nutrient digestibility, nitrogen utilization, and milk production of dairy cows

2021· article· en· W3134068954 on OpenAlexaff
F. Hassanat, C. Benchaar

Bibliographic record

VenueJournal of Dairy Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSilageRumenDry matterLatin squareSoybean mealForagePopulationHayBiologyPropionateDigestion (alchemy)NutrientFermentationDairy cattleAnimal scienceFood scienceNeutral Detergent FiberChemistryAgronomyBiochemistryRaw material

Abstract

fetched live from OpenAlex

In this study, we assessed the effects of increasing amounts of linseed oil (LSO) in corn silage-based diets on enteric CH 4 production, rumen fermentation characteristics, protozoal population, nutrient digestibility, N utilization, and milk production. For this purpose, 12 multiparous lactating Holstein cows (84 ± 28 d in milk; mean ± SD) fitted with ruminal cannula were used in a replicated 4 × 4 Latin square design (35-d period). The cows were fed ad libitum a total mixed ration without supplementation (control) or supplemented [on a dry matter (DM) basis] with LSO at 2% (LSO2), 3% (LSO3) or 4% (LSO4). The forage:concentrate ratio was 61:39 (on DM basis) and was similar among the experimental diets. The forage portion consisted of corn silage (58% diet DM) and timothy hay (3% diet DM). The proportions of soybean meal, corn grain and soybean hulls decreased as the amount of LSO in the diet increased. Daily methane production (g/d) decreased quadratically as the amount of LSO increased in the diet. Increasing LSO dietary supplementation caused a linear decrease in CH 4 emissions expressed on either DM intake (DMI) basis (−9, −20, and −28%, for LSO2, LSO3, and LSO4, respectively) or gross energy intake basis (−12, −22, and −31%, for LSO2, LSO3, and LSO4, respectively). At 2 and 3% LSO, the decrease in enteric CH 4 emissions occurred without negatively affecting DMI or apparent total-tract digestibility of fiber and without changing protozoa numbers. However, these 2 diets caused a shift in volatile fatty acids pattern toward less acetate and more propionate. The effect of the LSO4 diet on enteric CH 4 emissions was associated with a decrease in DMI, fiber apparent-total-tract digestibility, protozoa numbers (total and genera), and an increase in propionate proportion at the expense of acetate and butyrate proportions. Methane emission intensity [g of CH 4 /kg of energy-corrected milk (ECM)] decreased linearly (up to 28% decrease) with increasing LSO level in the diet. Milk fat yield decreased linearly (up to 19% decrease) with increasing inclusion of LSO in the diet. Milk protein yield increased at 2% or 3% LSO and decreased to the same level as that of the nonsupplemented diet at 4% LSO (quadratic effect). Yield of ECM was unchanged by LSO2 and LSO3 treatments but decreased (−2.8 kg/d) upon supplementation with 4% LSO (quadratic effect). Efficiency of milk production (kg ECM/kg DMI) was unaffected by the 3 levels of LSO. Ruminal NH 3 concentration was quadratically affected by LSO supplementation; decreasing only at the highest level of LSO supplementation. The amount (g/d) of N excreted in feces and urine decreased linearly and quadratically, respectively, as the amount of LSO increased in the diet, mainly because of the reduction in N intake. Efficiency of dietary N used for milk N secretion increased linearly with increasing LSO supplementation in the diet. We conclude that supplementing corn silage-based diets with 2 or 3% of LSO can reduce enteric CH 4 emissions up by to 20% without impairing animal productivity (i.e., ECM yield and feed efficiency).

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)0.000
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.268
Teacher spread0.242 · 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

Citations33
Published2021
Admission routes1
Has abstractyes

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