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Record W2974717387 · doi:10.3168/jds.2019-16869

Performance of dairy cows fed diets with similar proportions of undigested neutral detergent fiber with wheat straw substituted for alfalfa hay, corn silage, or both

2019· article· en· W2974717387 on OpenAlexaff
A. Kahyani, G.R. Ghorbani, M. Alikhani, E. Ghasemi, Ali Sadeghi‐Sefidmazgi, K. A. Beauchemin, S.M. Nasrollahi

Bibliographic record

VenueJournal of Dairy Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersIran National Science FoundationNational Science Foundation
KeywordsDry matterSilageNeutral Detergent FiberStrawForageHayAnimal scienceLactationChemistryBeet pulpAgronomyRumenTotal mixed rationLatin squareBiologyFood scienceIce calvingFermentation

Abstract

fetched live from OpenAlex

This study evaluated the effects of feeding diets that were formulated to contain similar proportions of undigested neutral detergent fiber (uNDF) from forage, with wheat straw (WS) substituted for corn silage (CS), alfalfa hay (AH), or both. The diets were fed to lactating dairy cows and intake, digestibility, blood metabolites, and milk production were examined. Thirty-two multiparous Holstein cows (body weight=642 ± 50 kg; days in milk=78 ± 11 d; milk production=56 ± 6 kg/d; mean ± standard deviation) were used in a randomized block design with 6-wk periods after a 10-d covariate period. Each period consisted of 14 d of adaptation followed by 28 d of data collection. The control diet contained CS and AH as forage sources (CSAH) with 17% of dietary dry matter as uNDF after 30 h of incubation (uNDF 30 ). Wheat straw was substituted for AH (WSCS), CS (WSAH), or both (WSCSAH) on an uNDF 30 basis, and beet pulp was used to obtain similar concentrations of NDF digestibility after 30 h of incubation (NDFD 30 = 44.5% of NDF) across all diets. The 4 diets also contained similar concentrations of net energy for lactation and metabolizable protein. Dry matter intake was greatest for WSCS (27.8 kg/d), followed by CSAH (25.7 kg/d), WSCSAH (25.2 kg/d), and WSAH (24.2 kg/d). However, yields of milk, 3.5% fat-corrected milk (FCM), and energy-corrected milk did not differ, resulting in higher FCM efficiency (kg of FCM yield/kg of dry matter intake) for WSAH (1.83) and WSCSAH (1.79), followed by CSAH (1.69) and WSCS (1.64). Milk protein percentage was greater for CSAH (2.84%) and WSCS (2.83%) than for WSAH (2.78%), and WSCSAH (2.81%) was intermediate. The opposite trend was observed for milk urea nitrogen, which was lower for CSAH (15.8 mg/dL), WSCS (15.8 mg/dL), and WSCSAH (17.0 mg/dL) than for WSAH (20 mg/dL). Total-tract NDF digestibility and ruminal pH were greater for diets containing WS than the diet without WS (CSAH), but digestibility of other nutrients was not affected by dietary treatments. Cows fed WSAH had less body reserves (body weight change=−13.5 kg/period) than the cows fed the other diets, whereas energy balance was greatest for those fed WSCS. The results showed that feeding high-producing dairy cows diets containing different forage sources but formulated to supply similar concentrations of uNDF 30 while maintaining NDFD 30, net energy for lactation, and metabolizable protein constant did not influence milk production. However, a combination of WS and CS (WSCS diet) compared with a diet with CS and AH improved feed intake, ruminal pH, total-tract NDF digestibility, and energy balance of dairy cows.

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 score0.003
Threshold uncertainty score0.006

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 communication0.0010.000
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 head0.027
GPT teacher head0.252
Teacher spread0.224 · 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

Citations23
Published2019
Admission routes1
Has abstractyes

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