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Record W2607625962 · doi:10.2527/asasann.2017.629

629 Effects of strategic supplementation of low quality diets and residual feed intake classification to optimize performance in gestating beef cattle

2017· article· en· W2607625962 on OpenAlexaff
Katelyn Spence, C. P. Campbell, J.P. Cant, Ángela Cánovas, I. B. Mandell

Bibliographic record

VenueJournal of Animal Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsResidual feed intakeAnimal scienceBeef cattleFeedlotStrawFeed conversion ratioSoybean mealGestationWeaningMealBiologyDry matterBreedPregnancyFood scienceBody weightAgronomyEndocrinology

Abstract

fetched live from OpenAlex

A wintering beef cow study was conducted to evaluate strategic supplementation of a straw-based diet with an energy-protein supplement during the last 75 days of gestation on beef cow performance and feed efficiency during gestation and subsequent pre-weaning calf performance. Gestating crossbred beef cows (predominantly Angus × Simmental; n = 118, 128 ± 31 days in gestation, 691.5 ± 235 kg BW) were evaluated on one of five nutritional regimens: 1) 70% haylage, 30% millet straw on a dry matter basis (DMB) fed ad libitum (HAYL), 2) millet straw fed ad libitum along with haylage at 0.8% DMB of cow BW (WSHAYL), 3) WSHAYL along with an energy-protein supplement once/week, 4) WSHAYL with supplementation twice/week, and 5) WSHAYL with supplementation three times/week. The supplement contained 54.6% corn gluten meal, 23.4% soybean meal, 21.0% calcium propionate, and 1.0% tallow and was fed at 0.32 g/kg of BW per day DMB. Cows were allocated to ensure similar days in gestation, age, residual feed intake (RFI) classification and breed composition across nutritional regimens. Cows were evaluated throughout second and third trimesters of gestation for feed intake, BW, average daily gain (ADG), residual feed intake (RFI), body condition score (BCS), ultrasound measurement of rib fat depth, serum blood metabolite concentrations, and pre-weaning calf performance traits. Cows were classified into low, medium, and high RFI groups (<0.5 SD; ±0.5 SD; >0.5 SD, respectively, based on a mean RFI of 0). Statistical analysis to examine differences in nutritional regimens and RFI classification was performed using PROC GLIMMX in SAS. Cows fed the HAYL diet had a higher percentage of high RFI cows and greater DMI vs. all other nutritional regimens (P < 0.001). Serum NEFA concentrations were lower in low RFI cows (P = 0.003) while urea concentrations tended to be greater in low RFI cows (P = 0.069). Serum AST concentrations were greater in HAYL cows vs. all other diets (P = 0.001). ADG was highest in HAYL cows vs. all other nutritional regimens (P < 0.001), while ADG was greater in low vs. high RFI cows (P < 0.001). Rib fat depths increased the most over gestation in HAYL vs. all other nutritional regimens (P < 0.001). Pre-weaning calf performance traits were not significantly affected by nutritional regimen or RFI classification. RFI classification was affected by nutritional regimen while wintering cow performance was related to individual cow RFI classification.

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 communication0.0010.000
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 head0.078
GPT teacher head0.335
Teacher spread0.257 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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