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Record W2743055994 · doi:10.2527/asasann.2017.241

241 Effects of low vs. high dietary lipid and source of lipid on performance of gestating beef cows and subsequent effects on progeny

2017· article· en· W2743055994 on OpenAlexaff
F. Añez-Osuna, G.B. Penner, John Campbell, C. F. Fitzsimmons, M. E. R. Dugan, P. G. Jefferson, H.A. Lardner, J. J. McKinnon

Bibliographic record

VenueJournal of Animal Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of AlbertaUniversity of Saskatchewan
Fundersnot available
KeywordsAnimal scienceBeef cattleIce calvingHayStrawCanolaRandomized block designBiologyDistillers grainsChemistryFood scienceAgronomyPregnancyLactation

Abstract

fetched live from OpenAlex

A two-year study was conducted to evaluate the effects of dietary lipid inclusion and source of lipid on performance of gestating beef cows and subsequent effects on progeny. Each year, 75 multiparous (≥3 calving) pregnant Angus cows were stratified by BW and BCS (Scottish System: 1 to 5) and randomly assigned to 15 pens (5 cows/pen). Subsequently, each pen was randomly assigned to one of three (n = 5) treatments: a low-lipid diet (LL; 1.4 ± 0.03% EE) consisting of grass hay, barley straw, and barley grain and two high-lipid diets (HL) where barley grain was substituted with a canola seed (CAN; 3.3 ± 0.02% EE) or a flaxseed (FLX; 3.3 ± 0.05% EE) based pelleted feed. Diets were formulated to meet the requirements of pregnant beef cows during the last two trimesters of gestation (184 ± 0.9 d) and adjusted for changes in environmental conditions and to be iso-caloric (DE: 2.6 ± 0.02 Mcal/kg) and iso-nitrogenous (CP: 10.5 ± 0.09%). Data were analyzed as a randomized complete block design with contrasts to separate the effects of lipid (LL vs. HL) and source of lipid (CAN vs. FLX). At the start of trial, all treatments had similar (P = 0.37) corrected (for conceptus) BW (659 ± 3.8 kg) and similar (P ≥ 0.33) proportion of thin (0.7 ± 0.69%), optimal (95.2 ± 3.04%), and over conditioned (4.1 ± 2.80%) cows. After 160 d on trial (24 ± 0.9 d pre-calving), corrected BW of LL cows (711 ± 2.2 kg) and proportion of fat cows (15.2 ± 8.8%) were greater (P ≤ 0.04) than those fed HL, with no difference (P ≥ 0.47) between CAN and FLX for corrected BW (698 ± 4.6 vs. 702 ± 4.4 kg) and proportion of over conditioned cows (3.7 ± 3.3 vs. 5.6 ± 4.3%). From calving to weaning, no differences (P ≥ 0.22) were observed in ADG, BW, BCS, milk yield, and milk composition of cows. Birth weight of bull-calves from LL cows (41 ± 0.5 kg) was lower (P < 0.01) than those from HL cows, while no difference (P = 0.70) was observed between bull-calves from CAN (45 ± 0.7 kg) and FLX (45 ± 1.2 kg) cows. At weaning, ADG and BW of steer-calves from LL cows (1.17 ± 0.02 kg/d and 251 ± 3.7 kg) were similar (P ≥ 0.74) to those from HL, while steer-calves from CAN cows had greater (P ≤ 0.04) ADG (1.20 ± 0.03 vs. 1.11 ± 0.04 kg/d) and BW (261 ± 5.4 and 245 ± 6.9 kg) than those from FLX cows. In conclusion, differences observed in corrected BW and BCS between cows fed low vs. high-lipid diets before calving and the difference between their bull-calves at birth suggest a differential partitioning of ME by gestating beef cows which is dependent on the form of dietary energy.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.016
GPT teacher head0.241
Teacher spread0.226 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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