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Record W4396651534 · doi:10.1093/jas/skae102.073

18 Effect of precision feeding standardized ileal digestible lysine to lactating sows compared with conventional feeding strategies in a commercial farm

2024· article· en· W4396651534 on OpenAlexaboutno aff
Mikayla S. Spinler, Jordan T Gebhardt, Joel M DeRouchey, Mike D Tokach, Robert D Goodband, H. L. Frobose, Amanda Uitermarkt, Vitor Hugo C Moita, Jason C Woodworth

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsnot available
Fundersnot available
KeywordsLysineAnimal scienceFood scienceBiologyBiochemistryAmino acid

Abstract

fetched live from OpenAlex

Abstract A total of 728 sows and litters were used in a 19-d lactation study to evaluate effects of precision feeding SID Lys and other amino acids on sow and litter performance and feed cost in a commercial farm. Sows were blocked by parity and allotted to 1 of 2 treatments at entry into farrowing. Treatments consisted of a control diet or a feed blending curve. Two diets were used to create treatment curves, a low Lys diet (0.60% SID Lys) or a high Lys diet (1.07% SID Lys). Sows on the control treatment were fed only the high Lys diet and sows on the blend curve were fed a blend of the low and high Lys diets using the Gestal Quattro Opti Feeder (Jyga Technologies, St-Lambert-de-Lauzon, Quebec, Canada) to target a specific Lys intake/d. Lysine intake targets were based on the NRC (2012) model requirements, except targets were increased by 20% to reach average Lys intake of approximately 63 g/d. The blend of the low and high Lys diet was adjusted on d 7 and 14 for sows fed the blend curve in an attempt to reach target Lys intake. Average Lys intake was 87% of target Lys intake because feed intake was lower than predicted. Sows fed the control diet had greater (P < 0.001; 72.0 vs 54.8 g/d) Lys intake compared with sows on blend curves because they were fed only the high Lys diet (Table). No differences (P > 0.05) in body weight (BW), backfat, loin depth, caliper score, or average daily feed intake (ADFI) were observed. There were no differences (P > 0.05) in litter size at d 2 after equalization or weaning; however, piglets and litters from sows fed the control treatment tended to have greater weaning weights (P = 0.090) and average daily gain (ADG; P = 0.071) compared with piglets and litters from sows fed the blend curve, likely due to insufficient Lys intake for sows on the blend curve to maximize litter growth performance. Feed cost per sow was less (P < 0.05) for sows fed the blend curve in both a low and high ingredient price scenario. No differences (P > 0.05) in feed cost per kg of litter weight gain were observed; however, feed cost per weaned pig was less (P < 0.05) for sows on the blend treatment. Serum urea nitrogen was greater (P < 0.05) at weaning compared with d 10 for control fed sows and was greater (P < 0.05) than blend-fed sows at both time points. Sows fed the control diet had greater milk crude protein (P = 0.05) compared with sows fed the blend curve. While precision feeding sows using diet blending during lactation can be used to reduce feed cost, future research should focus on using technology to automatically adjust diet blend for low or high-feed intake sows to avoid the over or under-feeding of nutrients.

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 score0.002
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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.304
Teacher spread0.277 · 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
Published2024
Admission routes1
Has abstractyes

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