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Record W4388539295 · doi:10.1093/jas/skad281.163

221 Increasing Functional Amino Acid Ratios Does Not Improve Growth Performance in Pigs Raised Under Poor Sanitary Conditions When Fed with Individual Precision Feeding Or Conventional Feeding Systems

2023· article· en· W4388539295 on OpenAlexaff
Pedro Righetti Arnaut, Luciano Hauschild, Aline Remus, C. Pomar, H.G. Brand, John K Htoo

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
KeywordsContext (archaeology)Animal scienceBiologyImmune systemHaptoglobinFeed conversion ratioNutrientHerdFood scienceBody weightEndocrinologyImmunologyEcology

Abstract

fetched live from OpenAlex

Abstract Immune system activation redirects dietary nutrients to defense mechanisms, thereby impairing growth performance of pigs. Supplementing pigs with functional amino acids (AA) such as Met, Thr and Trp was shown to support the immune system and reduce the negative effects on growth. However, pigs respond differently to immune stressors which increase herd variability. In this context, individual precision feeding (IPF) might be an alternative approach to reduce herd variability and increase nutrient efficiency in immune challenged pigs. This study aimed to evaluate growth performance, body composition, nitrogen (N) efficiency and haptoglobin and triglycerides serum concentration in growing pigs raised in poor sanitary conditions (PoorSC). The PoorSC was characterized by oral inoculation with 2 × 109 cfu of Salmonella typhimurium and manure spreading on the pen floor. Sixty gilts (23 ± 2.8 kg BW) were distributed in BW blocks according to a 2 dietary (D) × 2 feeding system (FS) factorial arrangement composed of to 2 diets [control (CN): INRA ideal AA ratio or supplemented (AA+) 120% of the ideal ratio for Met, Thr and Trp] and 2 feeding systems [conventional (GP) or IPF]. GP pigs were fed with a unique diet that matched the SID Lys requirement of the 80th-percentile pig at the beginning of the trial whereas the IPF pigs received a diet tailored daily to each pig requirement. All pigs were housed in the same pen and fed ad libitum during 28 experimental days with automatic feeding stations able to provide to each pig the assigned diet. Body composition was obtained by dual X-ray absorptiometry at days 0 and 28 and blood samples were collected at d 28. Data were analyzed with D and FS and their interaction as main fixed factors and body weight (BW) blocks as a random effect (Table 1). Haptoglobin serum concentration increased from d 0 to 28 regardless of FS and D (P < 0.10). IPF pigs fed with CN diet had the lightest BW at the end of the trial (P ≤ 0.10; FS × D), whereas BW was similar for the other treatments. However, across diets, IPF pigs had final BW, and protein, ADG, G:F, protein and lipid deposition, N intake and excretion and circulating triglycerides that were less than GP pigs. N utilization efficiency was similar across treatments. Additionally, increasing the provision of the studied functional AA did not improve pig performance. Thus, showing no benefits in increasing AA ratios for growth and immune response. The increased triglycerides concentration and low protein and lipid deposition suggests that IPF pigs prioritized the immune system to the expense of protein and lipid accretion. In conclusion, AA supplementation and IPF do not improve growth performance and N efficiency of pigs raised in poor sanitary conditions.

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 score0.005

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 studies0.0000.001
Scholarly communication0.0010.000
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 head0.045
GPT teacher head0.254
Teacher spread0.209 · 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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