Altering the essential amino acid-nitrogen:total nitrogen ratio with ammonium phosphate impacts nitrogen retention, lysine requirement and body composition of growing pigs
Bibliographic record
Abstract
Low protein (LP) diets have improved nitrogen (N) utilization while maintaining the performance of growing pigs. Regardless, LP diets may be limiting in N content to meet non-essential amino acid (NEAA) requirements, which may alter essential amino acid (EAA) utilization and requirements, as well as animal growth. Inclusion of a source of non-protein N (NPN) may be beneficial for improving utilization of EAA for lean gain in LP diets. Therefore, this thesis evaluated the effects of providing no NPN supplementation (NAP) or 1.7% NPN inclusion (AP) in an N-deficient diet, as indicated by a high EAA-N:total N ratio (EAA-N:TN) on the lysine (Lys) requirement for N retention (NR) and growth performance in pigs. An N balance study estimated 1.09% SID Lys requirement to maximize NR in NAP-fed pigs (EAA-N:TN of 0.36), while a 1.00% standardized ileal digestible (SID) Lys requirement was determined in AP-fed pigs (EAA-N:TN of 0.33). This result indicates that N is limiting in LP diets, and that Lys requirement and NR are greater with NPN supplementation. A subsequent growth performance study was conducted using the same dietary factor of NPN inclusion. Lysine content was based on NRC (2012) requirement and breakpoint values from the N-balance study and formulated for 20-40kg pigs. Average daily gain (ADG), average daily feed intake (ADFI), gain:feed (G:F), N output and carcass characteristics were assessed. Overall ADG and d 28 BW were improved with increasing Lys content, while G:F and lean depth were greater with NPN inclusion. Fecal N output was increased with NPN supplementation. Overall, N may be limiting in LP diets and ammonium phosphate is a suitable source of N for growing pigs, improving NR and maintaining growth in pigs fed diets deficient in NEAA-N. By improving the efficiency of N utilization and our knowledge of the importance of N to growing pigs, nutritionists will further improve diet formulation to reduce N excretion, diet costs and improve overall swine production.
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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) | 0.000 | 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) | 0.001 | 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".