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Record W4388539346 · doi:10.1093/jas/skad281.666

PSXI-22 Different Initial Body Weight and Dietary Supplementation of Tryptophan, Threonine, and Methionine on Feeding Behavior Index of Growing Pigs Under a Sanitary Challenge

2023· article· en· W4388539346 on OpenAlexaff
Graziela Alves Cunha da Valini, S. Méthot, Aline Remus, Luciano Hauschild

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAnimal scienceTryptophanMethionineBiologyBody weightMealFood scienceAmino acidBiochemistryEndocrinology

Abstract

fetched live from OpenAlex

Abstract Sanitary challenges (SC) can affect growth and revenue of pig production. The reduction in growth performance result from a decrease in daily feed intake (DFI). Besides, feeding behavior patterns may be also affected for pigs under SC. The extent of this impact might depend on the initial body weight (BW) of pigs. Additionally, supplementing tryptophan (Trp), threonine (Thr), and methionine (Met) above NRC requirements may attenuate inflammation and modulates DFI under SC. Therefore, this study aimed to evaluate initial BW variation and SC effect on feeding behavior of growing pigs fed supplemented diet with Trp, Thr, and Met at 100 or 120% of NRC recommended levels. Eighty gilts were categorized into two groups according to initial BW; light (23±0.8 kg) and heavy (29±1.0 kg). Both BW groups were group-housed for 14 days trial in a good or poor SC. Pigs within SC poor were orally inoculated with 2×109 CFU of Salmonella typhimurium, and fresh manure from a pig farm was spread on the floor. In contrast, pigs within SC good were not inoculated, nor was manure spread. Two diets (D) were provided within each SC: control (CN) or supplemented (AA+) diet with Trp, Thr, and Met:Lysine at 120% of NRC recommended levels. Pigs were individually fed through automatic feeders. Indexes of irregularity of feed intake (IIFI), meal duration (MD), and total intake (TI) were calculated based on real-time information registered by the feeders. For each pig, a monotonically increasing step function using relative cumulative DFI and relative time (after 14 days) was obtained, and linear regression models were fitted. The areas between the step function and the regression line were summed to obtain the IIFI. The means were compared using the MIXED procedure of SAS. There was an interaction for SCxD for TI, MD, and IIFI (P < 0.10, Table 1). Pigs within good SC fed AA+ had lower TI and shorter MD than CN diet (P < 0.05), however, pigs within poor SC fed CN or AA+ diet had no differences in TI and MD. Pigs within good SC fed AA+ had greater IIFI than CN diet, whereas pigs within poor SC fed CN had decreased IIFI than AA+ diet (P < 0.05). Furthermore, BW influenced TI, and MD, as heavy pigs had a greater TI and MD than the light pigs (P = 0.01), with no changes in IIFI (P > 0.10). Pigs in poor SC had a greater IIFI meaning they had fewer longer meals and greater DFI compared with pigs in good SC. Increasing Trp, Thr, and Met ratio influenced the pigs feeding behavior likely due to changes in TI. Additionally, the IIFI may be a tool to detect on set SC due to salmonella infection.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.315
Teacher spread0.264 · 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 routes1
Has abstractyes

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