The impact of daily multiphase feeding on animal performance, body composition, nitrogen and phosphorus excretions, and feed costs in growing–finishing pigs
Bibliographic record
Abstract
The effect of feeding pigs in a three-phase feeding (3PF) system or a daily-phase feeding (DPF) system on growth performance, body composition, and N and P excretions was studied on 8 pens of 10 pigs each. Feeds for the 3PF and DPF treatments were obtained by mixing two feeds, one with a high nutrient concentration and the other with a low nutrient concentration. The DPF pigs tended (P=0.08) to consume more feed (+3.7%) than the 3PF pigs, but only during the first feeding phase. The DPF pigs consumed 7.3% less protein (P<0.01) but a similar amount of total P. For the whole growing period, the DPF pigs tended (P=0.08) to gain more weight (+2.4%) than the 3PF pigs, mainly because of faster growth (P=0.02) during the first feeding period. At the end of the experiment, total body protein mass was similar in the two treatment groups, but the DPF pigs had 8% more body lipids (P=0.04) than the 3PF pigs. Daily multiphase feeding reduced N excretion by 12% (P<0.01) but did not significantly reduce P excretion. In addition, feed costs, nutrient intake and nutrient excretion under the two feeding strategies were simulated and compared after different approaches were used to formulate complete feeds for each phase of the 3PF system, as well as the two feeds used in the DPF program. Simulated feed intake and growth was similar to those observed in the animal experiment. In comparison with the simulated 3PF system, the feed cost for the DPF pigs was reduced by 1.0%, the simulated N and P intakes were reduced by 7.3% and 4.4%, respectively, and the expected N and P excretions were reduced by 12.6% and 6.6%, respectively. The concomitant adjustment of the dietary concentration of nutrients to match the evaluated requirements of pig populations can be an efficient approach to significantly reduce feeding costs and N and P excretions in pig production systems.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".