PSVII-6 Precision feeding and reduced crude protein on nitrogen efficiency of pigs raised under tropical conditions
Bibliographic record
Abstract
Abstract Feeding pigs with low protein diets is suggested to attenuate the negative effects of heat stress in pigs reared in hot climate areas, without changes on pigs performance. This study aimed to evaluate the nitrogen balance of pigs raised under tropical conditions and fed in conventional group-phase feeding systems (CON) or fed individually with daily tailored diets (IPF) receiving diets formulated with low (LCP) or high (HCP) crude protein. Sixty male castrated pigs (39kg±0.98) were assigned to 4 treatments in a 2×2 factorial arrangement. The experiment lasted 56 days (phase 1: d 0–28, and 2: d 29–56). CON fed pigs received within each phase a constant blend of diets A (high nutrient) and B (low nutrient density) supplying the estimated nutrient requirements of the group, whereas IPF pigs received daily a personalized blend providing the estimated amount of nutrients. Body lean was assessed by a dual-energy X-ray absorptiometry at the beginning and at the end of each phase and converted to body protein. Data were analyzed using the MIXED procedure of SAS including the fixed effects of feeding system, feed formulation, and their interactions. Pigs receiving LCP diets reduced the CP intake in 27% (P < 0.001). However, IPF pigs consumed on average 15% less CP than CON pigs (P < 0.001). Regardless of the reduced CP intake, LCP fed pigs showed a greater N retention than pigs receiving HCP diets during the first phase (P < 0.01). Moreover, pigs fed LCP diets excreted 30% less N to the environment than pigs fed HCP diets (P < 0.001). When LCP diets are complemented with the use of IPF technique, the N excreted can be reduced 18% more than in CON system (P < 0.001). Our results indicate that LCP diets and IPF are feasible to improve the nitrogen utilization of pigs raised under tropical conditions.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".