PSVII-14 Effects of Feeding High Level of Crystalline L-Lysine on Performance of Nursery Pigs
Bibliographic record
Abstract
Abstract A total of 408 weaned pigs (19 d of age; 6.59 kg initial BW) were used in a 3-phase feeding program to evaluate effects of increasing levels of crystalline L- Lysine on performance of nursery pigs. Pigs were blocked by weaning BW and allotted to 44 pens which were assigned to one of 4 dietary treatments (9-10 pigs/pen; 11 pens/treatment), including the control diet supplemented with one of the four L-Lysine levels: 0.3% (L1), 0.5% (L2), 0.6% (L3), or 0.7% (L4). Diets were formulated to be isocaloric and contained 1.40, 1.32, and 1.25% Sid Lys for phase 1, 2, and 3, respectively. L-Val, L-His and L-Arg were included in the L2, L3, and L4 treatments in addition to DL-Met, L-Thr, L-Trp, and L-Ile which were offered in all diets. In Phase 1 (d 0-9), no effects of L-Lys levels on performance were observed (P > 0.10). In Phase 2 (d 9-21), increasing L-Lys from L2 to L4 Lys reduced ADG (Linear, P < 0.001), while L4 also reduced ADFI (Linear, P = 0.01) and feed efficiency (Linear, P < 0.001). In Phase 3 (d 21-42), L3 and L4 significantly improved feed efficiency (Linear, P = 0.001). Overall (d 0-42), feeding L-Lys at L4 tended to reduce ADG (Linear, P < 0.10) and ADFI (Linear, P < 0.10), while feeding L-Lys at L3 improved feed efficiency (Cubic, P < 0.05). Data of this study suggest that responses to high levels of L-Lys are more profound on feed efficiency during phase 2 and 3. Inclusion level of L-Lys at 0.3% is best for gain but 0.6% is the best for optimal feed efficiency. Increasing L-Lys level to 0.7% enhanced feed efficiency in phase 3, but reduced all performance measures in Ph1, 2, and overall.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".