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Record W2810372577 · doi:10.3168/jds.2017-14203

Effect of fibrolytic enzymes on lactational performance, feeding behavior, and digestibility in high-producing dairy cows fed a barley silage–based diet

2018· article· en· W2810372577 on OpenAlexafffundabout
Basim Refat, David A. Christensen, J. J. McKinnon, Wenzhu Yang, Aaron D. Beattie, Tim A. McAllister, J.-S. Eun, Gamal Abdel‐Rahman, Peiqiang Yu

Bibliographic record

VenueJournal of Dairy Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Saskatchewan
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaWestern Grains Research FoundationMinistry of Agriculture - Saskatchewan
KeywordsSilageDry matterLatin squareAnimal scienceTotal mixed rationXylanaseBiologyDairy cattleCellulaseDigestion (alchemy)LactationFood scienceChemistryRumenIce calvingFermentationEnzymeBiochemistry

Abstract

fetched live from OpenAlex

The objectives of this study were to evaluate the effects of pretreating dairy cow rations with a fibrolytic enzyme derived from Trichoderma reesei (FETR; mixture of xylanase and cellulase; AB Vista, Wiltshire, UK) on lactation performance, digestibility, and feeding behavior in response to feeding a barley silage-based diet. Before starting the dairy trial, in vitro incubations were conducted to determine whether the addition of FETR would have an effect on these animal performance characteristics when applied to a barley silage-based diet for dairy cows. The dairy trial was performed using 8 Holstein dairy cows. The cows were blocked by parity and assigned randomly to 1 of 4 treatments: 0, 0.5, 0.75, and 1 mL of FETR/kg of dry matter (DM) diet in a replicated Latin square design. The pretreatment was applied to the complete diet during the mixing process. The experimental period continued for 22 d, with each experimental period consisting of a 16-d adaptation period and a 6-d sampling period. The daily feed intake of each individual cow was monitored using Insentec feed bins (RIC system, Insentec, Marknesse, the Netherlands). Feeding behavior characteristics were measured during the entire sampling period using the feed bin attendance data. Milk samples were collected in the last 3 d of each experimental period. The addition of FETR linearly increased the in vitro DM digestibility and tended to improve the in vitro digestibility of barley silage. There was a cubic effect of the enzyme levels on the total-tract DM and neutral detergent fiber digestibility. Maximal digestibility was reached at 0.75 mL of FETR/kg of TMR. The milk fat yield, fat-corrected milk, and energy-corrected milk quadratically responded to the incremental levels of FETR. The milk protein percentage linearly improved in response to FETR. Increasing FETR levels resulted in a quadratic effect on feed efficiency. There was no effect of FETR level on feeding behavior. In conclusion, pretreating dairy cow barley silage-based diet with 0.75 mL of FETR/kg of TMR increased the milk production efficiency of dairy cows fed diet containing 34% barley silage (DM basis). The positive effect of adding FETR could benefit the dairy industry in western Canada, where barley silage-based diets are common.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.017
GPT teacher head0.262
Teacher spread0.245 · 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

Citations51
Published2018
Admission routes3
Has abstractyes

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