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Record W4393386732 · doi:10.1093/jas/skae094

The standardized ileal digestible lysine-to-net energy ratio in the diets of sows to optimize milk nitrogen retention is dynamic during lactation

2024· article· en· W4393386732 on OpenAlexafffund
Madelaine C Watzeck, Lee‐Anne Huber

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of Guelph
FundersMinistry of Agriculture, Food and Rural AffairsNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsLactationAnimal scienceWeaningChemistryMathematicsBiologyPregnancy

Abstract

fetched live from OpenAlex

Fifty-two multiparous sows (average parity 3.1 ± 0.9 and initial BW 245.6 ± 32.5 kg) were used to evaluate the effects of dietary standardized ileal digestible (SID) Lys-to-net energy (NE) ratios on nitrogen (N) utilization throughout a 24-d lactation period. Sows were randomly assigned to one of five isoenergetic feeding programs that provided equally spaced and increasing SID Lys-to-NE ratios between 2.79 and 5.50 g SID Lys/Mcal NE. The feeding programs were generated by blending the two extreme diets in varying proportions and were provided to sows immediately after farrowing (day 1) and until weaning at day 24 ± 1. Nitrogen balances were conducted between days 4 and 7, 12 and 15, and 20 and 23 ± 1 of lactation to represent weeks 1, 2, and 3, respectively, using total urine collection and fecal grab sampling. Contrast statements were used to determine the linear and quadratic effects of increasing Lys-to-NE ratios. Linear and quadratic broken-line and polynomial quadratic (QPM) models were used to determine the optimum dietary Lys-to-NE ratios for N retention in milk. The Bayesian information criterion was used to assess the best fit. Feeding program did not influence sow average daily feed intake (5.8 ± 0.1 kg), BW change (-8.2 ± 3.1 kg), or change in back fat thickness (-2.6 ± 0.7 mm) over the 24-d lactation period, but piglet average daily gain increased with dietary SID Lys-to-NE ratio (linear; P < 0.05). Sow N intake increased with increasing dietary Lys-to-NE ratio in weeks 2 and 3 (linear; P < 0.001). Whole-body N retention (N intake - N output in urine and feces) increased with increasing dietary Lys-to-NE ratio in all weeks (linear; P < 0.05). The N retention in milk tended to increase then decrease with increasing dietary Lys-to-NE ratio in weeks 1 and 2 (quadratic; P = 0.051 and P = 0.081) and the QPM showed optimal milk N retention at 4.28, 4.42, and 4.67 g Lys/Mcal NE for weeks 1, 2, and 3, respectively. Maternal N retention (N intake - N output in urine, feces, and milk) decreased and then increased in week 1 (quadratic; P < 0.01) and increased in weeks 2 and 3 (linear; P < 0.01) with increasing dietary Lys-to-NE ratio. Therefore, the SID Lys-to-NE ratio necessary to optimize milk N output is dynamic throughout lactation. A two-diet feeding program could be created to match optimal weekly or daily SID Lys-to-NE ratios, which could lead to improved piglet ADG and body weights at weaning.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
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)0.0000.000

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 head0.030
GPT teacher head0.342
Teacher spread0.312 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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