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Record W4205295067 · doi:10.1093/jas/skz181

Evaluation of the optimal standardized ileal digestible threonine:lysine ratio in lactating sow diets

2019· article· en· W4205295067 on OpenAlexaff
Laura L Greiner, Amanda Graham, Márcio Gonçalves, Uiseli Orlando, K. J. Touchette

Bibliographic record

VenueJournal of Animal Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsCegep de Saint Hyacinthe
Fundersnot available
KeywordsAnimal scienceLitterWeaningLactationMathematicsBiologyPregnancy

Abstract

fetched live from OpenAlex

Camborough PIC sows (n = 291) were fed 1 of 5 dietary treatments to evaluate the standardized ileal digestible (SID) Thr:Lys requirement during lactation. Sows were blocked by parity (1, 2, and 3+) and randomly allotted to 1 of 5 SID Thr:Lys ratios (52, 60, 68, 76, and 84). SID Lys was formulated to 1.03% and SID methionine and cystine (M + C):Lys was 55%. Sows were allowed 5.45 kg feed/day starting on the day of farrowing. All other nutrients met or exceeded the NRC (2012) requirements. Sows were allowed ad libitum access to water, and piglets were cross-fostered within treatment within 24 h of birth. Data collected during the study included sow prefarrow BW, sow weaning weight, starting litter weight, weaning litter weight, piglet mortality, weaning-to-estrus interval, and subsequent total born piglets. Data were analyzed as a randomized complete block design using PROC MIXED with sow as the experimental unit and treatment and parity as fixed effects. Requirement estimation models evaluated were quadratic polynomial, broken-line linear, and broken-line quadratic (BLQ) using PROC NLMIXED. Models that differed in their Bayesian information criterion (BIC) values by at least 2 points were considered to have meaningful differences in their data fit. The best-fit model was based on the best BIC value. As the SID Thr:Lys ratio increased, there was a quadratic response on ADFI (4.73, 4.57, 4.67, 4.55, and 4.60 kg/d; P = 0.001) and percent of sow BW loss (-6.4, -7.89, -7.35, -6.19, and -5.81; P = 0.004). In addition, there was a trend for weaning-to-estrus interval to be affected by the ratio (5.4, 4.4, 4.6, 4.5, and 4.8; P = 0.07). Daily litter gain was also quadratically improved as the SID Thr:Lys ratio increased (2.67, 2.67, 2.78, 2.77, and 2.68 kg/d; P-value = 0.001). For daily litter gain, the BLQ model was determined to be the best fit with an estimated SID Thr:Lys requirement of 65%. In conclusion, the optimal SID Thr:Lys ratio for litter growth was 65.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.295
Teacher spread0.260 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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