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Record W4410535943 · doi:10.1093/jas/skaf102.037

197 The apparent utilization of DL-methionine and the hydroxyl-analog of methionine for nitrogen retention of lactating sows

2025· article· en· W4410535943 on OpenAlexaff
Faith D Kurtz, Cierra Kozole, Francis Amann Eugenio, Yves Mercier, Lee‐Anne Huber

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiopolymer Synthesis and Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMethionineNitrogenChemistryAnimal scienceBiochemistryFood scienceBiologyOrganic chemistryAmino acid

Abstract

fetched live from OpenAlex

Abstract Eighty-seven sows [average parity: 1.49±0.50; body weight on lactation day 9: 195.5±14.9 kg] were recruited to evaluate the apparent utilization of dietary Met sources for N retention during lactation. On day 9 of lactation, sows were assigned to one of six dietary treatments (n=~15): [1] 70% of estimated standardized ileal digestible (SID) methionine + cysteine (Met+Cys) requirements provided via whole-protein sources (0.34% SID Met+Cys), [2] and [3] 80 and 90% SID Met+Cys requirements supplied by DL-methionine (DL-MET), [4] and [5] 80 and 90% SID Met+Cys requirements supplied by the hydroxy-analog of methionine (HMTBa; equimolar), or [6] 110% SID Met+Cys requirements supplied by whole-protein sources and DL-methionine (CON). In all diets, no crystalline cysteine was included. All other indispensable amino acids were supplied at estimated requirements. Sows received dietary treatments between days 10 and 20 (weaning) of lactation, and feed was offered according to a standard feeding curve. Litters were standardized to 13±2 pigs within 48 h of farrowing. A N-balance was conducted between days 16 and 19±2 (peak) of lactation using total urine collection and fecal grab sampling. Milk N output (g/d) was calculated using estimated milk yield based on litter growth rate and size and analyzed milk N concentration. Contrast statements were used to assess linear effects of increasing dietary Met within source, and all treatments were compared to CON via a Dunnett test. Dietary Met source did not influence sow average daily feed intake or body weight and back fat thickness changes between days 9 and 20 of lactation, but piglet average daily gain increased as dietary SID Met content increased for both DL-MET (224 to 244±7 g/d; P<0.05) and HMTBa (224 to 251±9 g/d; P<0.05), with only 90% HMTBa not different from CON (277±11 g/d). During the N balance period, sow N intake tended to increase with SID Met for both DL-MET (162.4 to 170.3±5.4 g/d; P=0.098) and HMTBa (162.4 to 169.8±4.2 g/d; P=0.075). Whole-body N retention (N intake – N output in urine and feces) increased with increasing SID Met content for both DL-MET (100.5 to 112.1±3.7 g/d; P<0.05) and HMTBa (100.5 to 110.8±4.5 g/d; P<0.05), but all were less than CON (123.5±4.3 g/d; P<0.05). The N output in milk increased with SID Met for both DL-MET (69.3 to 87.7±3.7 g/d; P<0.05) and HMTBa (69.3 to 86.0±4.7 g/d; P<0.05), but only the 70% diet was less than CON (94.2±4.3 g/d; P<0.05). Neither dietary Met source nor dose influenced maternal N retention (overall average 25.5±6.4 g/d) or apparent N utilization efficiency (N retention/N intake × 100; overall average 65.2±4.1%). Therefore, both DL-Met and HMTBa were used effectively to improve N utilization for milk production during peak lactation when SID Met+Cys was provided below estimated requirements.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.320
Teacher spread0.295 · 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 teacher head, 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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