PSV-19 Effect of yeast bioactive compounds on the reproductive performance of sows
Bibliographic record
Abstract
Abstract Prebiotics has been used in sow diets as an alternative to minimize the impacts of hyperprolificity, such as variability coefficient and poor litter performance. However, the additive inclusion is generally high and costly. The objective of this study was to verify the effect of the low inclusion of yeast bioactive compounds (YBC), in gestation and lactation diets, on sows reproductive performance. Five hundred sows were assigned in two treatments in a block design considering parity as a random factor, using each sow as an experimental unit with for gestation (n = 500) and lactation period (n = 80). The treatments were control diet (CON) and diet with 0.036% of YBC inclusion (YBC). Back fat thickness was measured at 30 and 70 days of gestation, at farrowing day, at 14 days of lactation and weaning day. Sows were weighted at the farrowing barn entry day and at weaning. The corporal mobilization was accessed following the equation: Body change = Weight at weaning - [Weight at lactation entry - (Litter weight at birth + Placenta weight)]. After cross-fostering and at weaning the litters were weighed to calculate the daily weight gain. Differences were considered significant when p ≤ 0.05 and tendencies were considered when p > 0.05 and p < 0.10. No difference was found regarding the reproductive performance (total born, born alive, mummified and stillborns) (P > 0.05). YBC tended to have greater litter final weight than CON group, 59.08 kg versus 56.70 kg (P = 0.057). Backfat thickness tended to be lower (5.20%) in YBC (16.03 mm) than CON group (16.91 mm) during gestation period (P = 0.075). However, at weaning day no difference for backfat thickness was found between treatments (P > 0.05). YBC had lower loss weight during lactation than CON group, 0.0 kg versus 4.99 kg, respectively (P = 0.011). Low inclusion of YBC enhances litter performance and improves body condition of lactating sows.
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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".