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Record W4410535902 · doi:10.1093/jas/skaf102.036

195 Standardized ileal digestible lysine intake by gilts should be increased in late gestation to maximize whole-body nitrogen retention, piglet birth weight, and subsequent milk yield

2025· article· en· W4410535902 on OpenAlexaff
Vanessa Kloostra, C. Farmer, Lee‐Anne Huber

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
Fundersnot available
KeywordsLysineAnimal scienceGestationYield (engineering)Body weightNitrogenChemistryBiologyAgronomyFood sciencePregnancyBiochemistryEndocrinologyAmino acid

Abstract

fetched live from OpenAlex

Abstract One hundred fifty-seven gestating gilts were used to determine the standardized ileal digestible (SID) lysine (protein) intake in late gestation necessary to maximize whole-body N retention, piglet birth weight, and subsequent milk yield. On d 90 of gestation, gilts were assigned to one of seven isoenergetic diets with equally spaced and increasing SID lysine (protein) contents that ranged from 70 to 160% of NRC-(2012) estimated requirements, using soybean meal to supply additional lysine (13.3 to 30.5 g SID lysine per day; n=~22). Between d 105 and 108 of gestation, a N-balance was completed using total urine collection and fecal grab-sampling. After farrowing, all sows received a standard lactation diet until weaning (d20±1). Colostrum was collected (n=~14) ~24h after birth of the first piglet, confirmed by video recordings, and milk was collected on d 18 of lactation (n=~15). Linear and quadratic contrasts were constructed. Using the Bayesian information criteria to assess best fit, the linear broken line model was selected to determine optimal SID lysine (protein) intake. Gilt body weight gain in late gestation increased and body weight loss in the subsequent lactation tended to increase with increasing SID lysine (protein) intake (linear; P<0.001 and P=0.086, respectively). The gain in backfat depth during late gestation tended to decrease with increasing SID lysine (protein) intake (linear; P=0.067), but backfat depth loss during the subsequent lactation was not influenced by SID lysine (protein) intake. Nitrogen intake (52.5 to 79.5±0.9 g/d), excretion (29.6 to 43.8±2.1 g/d), and whole-body retention (N intake – N output; 21.1 to 36.9±2.3 g/d) increased with increasing SID lysine (protein) intake (linear; P<0.0001). Nitrogen retention was maximized at SID lysine intake of 22.0 g/d during late gestation (115% of NRC-estimated requirements). Litter size at birth (14.8±0.9) and the number of stillborns (0.7±0.3) were not affected by dietary treatment but piglet birth weight increased then decreased with increasing SID lysine (protein) intake (quadratic; P<0.01) and was maximized at SID lysine intake of 22.0 g/d during late gestation. Estimated milk yield and litter growth rate increased with SID lysine (protein) intake in late gestation (linear; P<0.05 and P=0.057, respectively). Estimated milk yield was maximized at SID lysine intake of 23.0 g/d during late gestation (120% of NRC-estimated requirements). Milk composition was not influenced by SID lysine (protein) intake in late gestation, but the dry matter content of colostrum decreased with increasing SID lysine (protein) intake (linear; P<0.01). Lactation feed intake tended to decrease then increase with increasing lysine intake (quadratic; P=0.067). Therefore, SID lysine supply in late gestating gilts should be increased by 15% above the current recommendations to maximize whole-body N retention in late gestation and piglet birth weight, and by 20% to maximize milk yield in the subsequent lactation.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.050
GPT teacher head0.329
Teacher spread0.279 · 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".

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Citations2
Published2025
Admission routes1
Has abstractyes

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