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Record W4388540156 · doi:10.1093/jas/skad281.555

PSVIII-A-7 Effects of New Forage Barley and Oat Varieties on Silage Fermentation Characteristics, and Feed Intake, Milk Production and Composition, and N Balance in Dairy Cows

2023· article· en· W4388540156 on OpenAlexaffabout
C. M. Leach, Aaron D. Beattie, David A. Christensen, T. Mutsvangwa

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSilageLatin squareDry matterForageAnimal scienceFermentationComposition (language)FodderAgronomyRumenDairy cattleBiologyStarchChemistryFood science

Abstract

fetched live from OpenAlex

Abstract Forages are the foundation of dairy cow diets and typically comprise 50% of the dietary dry matter and ≥40% of the total NEL intake. New forage barley (CDC Renegade; designated RENE) and forage oat (CDC Arborg; ARBO) varieties are available for feeding dairy cows in western Canada. The objectives were to determine the ensiling characteristics of RENE and ARBO and to compare the effects of feeding them as the major forage source on feed intake, milk yield and composition, ruminal pH, and nitrogen (N) balance in dairy cows. Eight multiparous Holstein cows (82 ± 12 days-in-milk at the beginning of the study) were used in a 4 × 4 Latin square design study with 14 d of dietary adaptation and 7 d of data and sample collection. Cows in one Latin square were ruminally cannulated to determine dietary effects on ruminal pH and N balance. The four diets tested contained RENE, ARBO, Conlon (CONL), and Rosser (ROSS) silages as the major source of forage, with ROSS and CONL being included for comparison as they are commonly used barley varieties in western Canada. Silage fermentation characteristics were largely similar for the four forages, except for total short-chain fatty acid concentrations which tended (P = 0.08) to be greater for RENE and ROSS when compared with CONL and ARBO. Silage starch contents were greater (P < 0.01) for CONL and ROSS when compared with RENE and ARBO, which were similar. Silage aNDFom contents were greater (P < 0.01) for RENE and ARBO when compared with CONL and ROSS, which were similar. Dry matter intake (mean = 34.3 kg/d) and milk yield (mean = 48.6 kg/d) were unaffected by treatment (P ≥ 0.42). Milk fat content was greater (P = 0.03) for cows fed RENE compared with those fed CONL, with that of cows fed ROSS and ARBO being intermediate and not different to RENE and CONL. Milk fat yield was greater (P = 0.02) for cows fed RENE compared with those fed ROSS, with that of cows fed CONL and ARBO being intermediate and not different to RENE and ROSS. Intake of N, urinary and fecal excretion of N, total N excretion, milk N, and apparent N balance were unaffected by diet (P ≥ 0.21). Mean ruminal pH was greater (P = 0.02) in cows fed ARBO compared with those fed ROSS, with that of cows fed CONL and RENE being intermediate and not different to CONL and RENE. Our results show that the new forage varieties, RENE and ARBO, can support similar levels of milk yield compared with forage varieties such as CONL and ROSS.

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 score0.017
Threshold uncertainty score0.034

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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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