PSIV-35 Effects of Essential Oils on Nutrients and Energy Availability of Post Weaning Pigs Fed Different Energy Levels Diets.
Bibliographic record
Abstract
Essential oils have been considered as growth promoters in pigs for alleviating oxidative damage and stimulating antimicrobial effects. However, no studies have done in nutrient availability of post weaning pigs with feed supplementation of a mixture of cinnamaldehyde (60 g/kg), garlic meal (800g/kg) and maltodextrin (140mg/kg). A total of 32 pigs (L x Y x D) weaned at age 35d were allotted to 4 dietary treatments with 8 replicates (1 pigs/replicate). The dietary treatments were: 1) high energy diets (HE) (DE, 3400 kcal/kg), without essential oil; 2) HE + 600 mg/kg essential oil (HE-EO); 3) low energy diets (LE) (DE, 3200 kcal/kg), without essential oil; 4) LE + 600 mg/kg essential oil (LE-EO). The pigs were housed individually in digestion cages (0.8 m x 0.6 m) and fed for 7 days. The fecal and urine samples were collected on day 8–12 for analyzing digestibility of dry matter (DM), organic matter (OM), crude protein (CP), ether extract (EE), energy (GE), biological value (BV) and net protein utilization (NPU). There were no significant differences (P > 0.05) on apparent digestibility of OM, CP, EE, and GE; BV and NPU with addition of essential oils. However, LA diets had higher (P < 0.05) apparent digestibility of OM, CP, EE and GE; and BV and NPU. The apparent of digestibility of all amino acids (Lys, Met, His, Leu, Ile, Phe, Thr, Val, Asp, Ser, Glu, Gly, Ala, Tyr, & Pro) were increased (P < 0.05) with the addition of essential oils. HA diet had higher (P < 0.05) the apparent digestibility of Lys, Gly, and Ala, and lower (P < 0.05) the apparent digestibility of His and Pro. The results demonstrated that mixture of cinnamaldehyde, garlic meal and maltodextrin have potential to improve utilization of amino acids of post weaning pigs.
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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".