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Record W3162499191 · doi:10.1093/jas/skab054.065

118 Increased Growth and Carcass Attributes in Improvest®-treated Gilts Do Not Require Additional Dietary Lysine

2021· article· en· W3162499191 on OpenAlexaff
K. A. Vonnahme, Leanne Van De Weyer, Deb Amodie, John F. Patience, Steve Pollmann, Lucina Galina-Pantoja, M. A. Mellencamp

Bibliographic record

VenueJournal of Animal Science · 2021
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsZoetis (Canada)
Fundersnot available
KeywordsAnimal scienceLysineCompletely randomized designBiologyAmino acidBiochemistry

Abstract

fetched live from OpenAlex

Abstract Numerous studies have shown that gilts treated with Improvest® have greater carcass weights and increased ADG compared with untreated gilts. To develop the optimum nutritional program for Improvest-treated gilts, a randomized 5×2 factorial design of dietary lysine levels (90, 100, 110, 120, and 130% of NRC recommendations) with or without Improvest was performed. Gilts were housed in 120 pens (4 pigs/pen) at 8 weeks of age (day 0). Gilts and feed were weighed immediately prior to each dietary phase change (days 0, 21, 42, 70, 91, and 105). Improvest was administered at 9 and 19 weeks of age (4 weeks pre-harvest). There was no diet × treatment × day (P > 0.78) nor diet × treatment (P > 0.11) interactions for any variables. Gilts had similar BWT, ADG, and ADFI until after the 2nd dose of Improvest, when Improvest-treated gilts were heavier (123.62 vs. 121.59 ± 0.68 and 138.16 vs. 133.97 ± 0.71 kg, days 91 and 105; P < 0.01), had increased ADG (1.19 vs. 1.09 ± 0.01 and 1.03 vs. 0.88 ± 0.02 kg/day days 91 and 105; P < 0.01) and consumed more feed (2.99 vs. 2.84 ± 0.03 and 3.19 vs. 2.68 ± 0.04 kg/pig/day; days 91 and 105; P < 0.01) compared with untreated gilts. Carcass evaluation was conducted on 120 pigs (2 pigs/60 pens). No significant structures were present on ovaries of Improvest-treated gilts. Improvest-treated gilts were heavier (market and HCW; P ≤ 0.02) than controls. Improvest-treated gilts tended (P ≤ 0.08) to have heavier bone-in butt and bone-in ham weights. Belly weights were heavier (kg and %HCW; P ≤ 0.05) in Improvest-treated vs control gilts and were thicker (P = 0.01) but were similar (P > 0.3) in length and width. While IV was similar (P > 0.2) in belly fat, loin intramuscular fat was increased (P < 0.01) from Improvest-treated gilts. Without additional dietary amino acids, Improvest-treated gilts delivered greater gain after the 2nd dose, yielding significantly heavier carcasses and primal cuts, including bellies which were larger as a percentage of HCW, and increased loin intramuscular fat.

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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.059
GPT teacher head0.326
Teacher spread0.267 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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