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Record W4388181135 · doi:10.1093/jas/skad341.322

PSII-12 Growth Performance of Pigs Fed Diets Containing Supplemental Lysine and a Low or High Essential Amino Acid-Nitrogen to Total Nitrogen Ratio

2023· article· en· W4388181135 on OpenAlexaff
Carley M Camiré, Lucas Alves Rodrigues, Josiane C Panisson, Anna K. Shoveller, Daniel A Columbus

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsGenome PrairieUniversity of GuelphUniversity of Saskatchewan
Fundersnot available
KeywordsLysineAnimal scienceLimitingMealRandomized block designNitrogenWeight gainNutrientSoybean mealChemistryFeed conversion ratioFactorial experimentAmino acidBody weightBiologyFood scienceBiochemistryAgronomyMathematicsEndocrinology

Abstract

fetched live from OpenAlex

Abstract With the provision of low protein (LP) diets, it is possible that N, or non-essential amino acids (NEAA), become limiting. We have previously shown that the lysine (Lys) requirement for N retention is greater when pigs are fed a diet with sufficient N, as indicated by a low EAA-N:total N ratio (EAA-N:TN). The objective of this study was to investigate the effect of EAA-N:TN and Lys content on growth performance of growing pigs. A total of 240 growing pigs (20.6 ± 2.03 kg initial body weight) were randomly placed into groups of 5 pigs/pen (either 2 barrows and 3 gilts, or 3 barrows and 2 gilts) and randomly assigned to 1 of 4 dietary treatments (n = 12 pens/treatment) in 3 blocks in a 2 × 2 factorial design. Factors consisted of dietary EAA-N:TN [optimal ratio (LR) of 0.48 or high ratio (HR) of 0.55] and dietary Lys level of 1.03% SID or 1.22% SID, representing the NRC (2012) requirement and the requirement as determined previously, respectively. Diets were corn and soybean meal based and formulated to meet or exceed nutrient requirements according to NRC (2012). Pigs were individually weighed and feed intake determined weekly to determine average daily gain (ADG), average daily feed intake (ADFI), and gain:feed (G:F). Fecal samples were collected on d 14 for determination of N output. Data were analyzed using a mixed model with fixed effects of ratio, lysine, and their interaction and block as a random effect. Increasing dietary Lys resulted in increased overall ADG and ADFI, regardless of EAA-N:TN ratio (P < 0.01). Pigs fed the HR diets had improved ADG in week 4 (P < 0.05), whereas pigs fed the LR diets had improved ADG and G:F in week 1 (P < 0.01). There was an interactive effect of ratio and Lys on N output (P < 0.01), where N output decreased in the HR diets with 1.22% Lys. Overall, current Lys requirements may not be sufficient to maximize growth in 20-50 kg pigs, and greater Lys may be beneficial for reducing N output in LP diets.

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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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